Cost
$0.32per task
Cost per task. One Intelligence Index task at list price, every token counted. Run at max effort.
Model family by DeepSeek
DeepSeek V4.1
DeepSeek's V4.1 family for frontier reasoning and software work.
Where it sits in DeepSeek's lineup
- DeepSeek V4.1DeepSeek's V4.1 family for frontier reasoning and software work.This model
- DeepSeek V4DeepSeek's V4 family of open-weight mixture-of-experts models.DeepSeek V4 Pro
- Made by
- DeepSeek
- Releases
- 1 tracked
- Current release
- DeepSeek V4.1 Flash
Strengths and weaknesses
Compare with other models Up to 3 beside DeepSeek V4.1 Flash
- DeepSeek V4.1 Flash
Suggested comparisons
The models a buyer weighs against DeepSeek V4.1 Flash, picked on list price and on Artificial Analysis's Intelligence Index of overall quality. Add one to draw it beside DeepSeek V4.1 Flash.
DeepSeek V4.1 Flash
Among the 40 current releases on this chart, DeepSeek V4.1 Flash ranks 10th of 38 on Tool use, third of 8 on Instruction following and 13th of 38 on Long context. On Computer use, Moonshot AI's runs on OSWorld 2.1 put DeepSeek V4.1 Flash 10.3 points under Kimi K3.1 Pro. Answers in full: published only for another harness, setting or build, listed in the table.
Each axis is one public benchmark at one setting, on its own fixed 0 to 100 scale, so adding a model never moves another. A dotted bridge crosses a missing result, which is never a zero. A hollow mark is a result from another source: the maker's own figure or another lab's run, where the benchmark's usual source has not tested the model yet. The readout names it.
On the chart
- DeepSeek V4.1 FlashThis pageResults on 11 of 12 axes$0.30 / $1.20Peak-hours rate; off-peak $0.15 / $0.60, as DeepSeek lists it.177 tokens/sFirst token in 0.9 s
Prices and speeds read between Oct 27, 2026 and Oct 28, 2026.
DeepSeek V4.1 Flash on each axis11 of 12 with a result
The share of Terminal-Bench 4.0's long terminal tasks the model finishes on its own: services, kernels, proofs and data pipelines, graded on the final artifact with no partial credit.
Terminal-Bench 4.0, pass@1 averaged over 3 runs, mini-swe-agent harness
- DeepSeek V4.1 Flash31.8%Vals.ai ranked the October 17 build 19th on its leaderboard of Oct 24, 2026.
The share of SciCode's scientific programming subproblems the model's code solves on the first attempt.
SciCode, subproblem accuracy, pass@1, highest effort run
- DeepSeek V4.1 Flash55.9%
The share of FrontierMath's held-out research-grade problems (tiers 1 to 3) the model answers correctly.
FrontierMath Tiers 1-3, accuracy, pass@1, highest effort run
- DeepSeek V4.1 Flash71.2%
The share of GPQA Diamond's graduate-level biology, chemistry and physics questions the model answers correctly.
GPQA Diamond, accuracy, pass@1, highest effort run
- DeepSeek V4.1 Flash93.2%
The share of Humanity's Last Exam's 2,158 text-only questions, expert-written at the edge of human knowledge, the model answers correctly without tools.
Humanity's Last Exam, accuracy, text-only questions, no tools
- DeepSeek V4.1 Flash43.3%
The share of each AutomationBench task's objectives the model completes by calling REST APIs across simulated business apps (Gmail, Sheets, Slack, Salesforce, Zendesk, Jira, HubSpot), averaged over tasks. A task that breaks one of its policy guardrails scores zero.
AutomationBench-AA, score, Artificial Analysis run
- DeepSeek V4.1 Flash66.6%
How much of each OSWorld 2.1 workflow the model completes by operating a real Ubuntu desktop through screenshots, mouse and keyboard: all 108 long tasks across apps, files, mail and browsers, on the September 2026 v2.1 release of the task files. A point is the mean share of each task's weighted checks the model passes (the partial score, as a percentage). The OSWorld team's own runs come first. Where the team has not run a release, the point is another lab's run or the maker's own published figure, marked with who ran it and the benchmark it ran: OSWorld 2.1 in the maker's harness, OSWorld 2.0's offline set or the earlier OSWorld-Verified. Those points are drawn so the release has a figure, and they are not ranked against the team's runs.
OSWorld 2.1, partial score, full 108-task set, v2.1 release. Where it has no run of a model, the maker's own figure or another lab's run stands in, marked with its benchmark.
- DeepSeek V4.1 Flash69.3%Moonshot AI's runBenchmark: OSWorld 2.1, metric and task set not named by Moonshot, v2.1 release, where the axis reads partial score, full 108-task set. From another source, so it is drawn and marked but not ranked with the others.Moonshot AI's run of the October 17 build at max effort in its Kimi Agent harness, from the Kimi K3.1 Pro launch table. Moonshot does not name the metric.
The share of AA-LCR's questions the model answers correctly by reasoning across long sets of real documents, about 100K tokens each.
AA-LCR v1.1, accuracy, Artificial Analysis run
- DeepSeek V4.1 Flash82.7%
The share of MMMU-Pro's college-level questions over charts, diagrams and photos the model answers correctly.
MMMU-Pro, overall accuracy, no tools
- DeepSeek V4.1 Flash80.6%
The share of AA-Omniscience's 6,000 knowledge questions across 42 economically relevant topics the model answers correctly from memory, without search.
AA-Omniscience Accuracy, accuracy, Artificial Analysis run
- DeepSeek V4.1 Flash39.6%Hallucination rate 64.1% in the same run (lower is better)
The share of SpeechMap's 2,120 sensitive and controversial but legal requests the model answers in full: arguments, essays and explanations on contested themes in politics, religion, race, sex, history and similar topics, four wordings per theme across 530 themes. SpeechMap's judge rates each response complete, evasive (hedged or redirected), a denial, or an error (the provider's API blocked the request). Only complete answers count, so the point is the share answered in full: 100 minus the share hedged, refused or blocked by the provider. Higher means more lawful requests answered in full. The share blocked at the provider is printed apart in the table, because an API error is not the model declining. Where SpeechMap runs a release both with reasoning off and with reasoning on (a -reasoning or -thinking entry), the reasoning-on entry is used; a release with one entry uses that entry.
SpeechMap, % Complete over 2,120 contested requests, reasoning-on entry
- DeepSeek V4.1 FlashPublished only for another harness, setting or build, listed in the tableNot drawn: SpeechMap.AI 67.2% on an earlier build. The table below lists it.
The share of MultiChallenge's multi-turn conversations in which the model keeps every instruction it was given earlier in the conversation.
MultiChallenge, accuracy, Scale AI run
- DeepSeek V4.1 Flash74.9%On Oct 28, 2026, Scale AI ranked the October 17 build 5th.Plus or minus 5.3 points (95% interval)
Cost, speed, capacity, quality and accuracy for DeepSeek V4.1 Flash, with where each figure sits among the 40 models GILD tracks. These measures stand beside the chart and never feed it.
Speed
179tokens a second
Output speed. How fast it writes once the answer starts. Run at max effort.
- First token
- 1.0 s
- Whole answer
- 15 s
Capacity
1Mtokens
Context window. The most one request can hold, as the maker states it.
- Max output
- 384K
- Reads
- Text, Images
Quality
39.5of 100
Intelligence Index. One composite score across independent evaluations. Run at max effort.
- GDPval knowledge work
- 1,600 Elo
- Terminal-Bench 4.0
- 26.8%
- Epoch Capabilities Index
- 156
Hallucination
64.1%wrong when it should say “I don’t know”
Hallucination rate. Of the questions it can't get right, how often it answers anyway. Lower is better. Run at max effort.
- Knowledge accuracy
- 39.6%
Where you can get it
9of 19 routes
Routes offering it. Of the clouds, gateways and coding products GILD tracks, those offering it today.
- Open weights
- Yes
- Licence
- MIT
Figures from Artificial Analysis, DeepSeek, Epoch AI and GILD's route matrix, read Oct 26 to 28, 2026. Each measure's definition and source open under . Not yet published for DeepSeek V4.1 Flash: Cached input.
Every value with its benchmark, run and source
| Axis | Benchmark and setting | DeepSeek V4.1 Flash | Run | Source | Date |
|---|---|---|---|---|---|
| Agentic coding | Terminal-Bench 4.0Pass@1 averaged over 3 runs, mini-swe-agent harness. Vals.ai ranked the October 17 build 19th on its leaderboard of Oct 24, 2026. | 31.8% | DeepSeek V4.1 Flash 1017Effort: not published. Harness: mini-swe-agent. Run on the Oct 17, 2026 build.Not drawn: Vals.ai 19.7% on an earlier build, Oct 24, 2026. Source | Vals.ai | Oct 24, 2026 |
| Code | SciCodeSubproblem accuracy, pass@1, highest effort run | 55.9% | DeepSeek V4.1 Flash 1017 (Max)Effort: max. Harness: none. Run on the Oct 17, 2026 build.Not drawn: Artificial Analysis 51.9% on an earlier build, Oct 28, 2026. Source | Artificial Analysis | Oct 28, 2026 |
| Math | FrontierMath Tiers 1-3Accuracy, pass@1, highest effort run | 71.2% | Effort: max. Harness: none. Run on the Oct 17, 2026 build.Not drawn: Epoch AI 67.4% on an earlier build, Oct 8, 2026. Source | Epoch AI | Oct 19, 2026 |
| Science | GPQA DiamondAccuracy, pass@1, highest effort run | 93.2% | Effort: max. Harness: none. Run on the Oct 17, 2026 build.Not drawn: Epoch AI 89.8% on an earlier build, Oct 9, 2026. Source | Epoch AI | Oct 19, 2026 |
| Hard reasoning | Humanity's Last ExamAccuracy, text-only questions, no tools | 43.3% | DeepSeek V4.1 Flash 1017 (Max)Effort: max. Harness: none. Run on the Oct 17, 2026 build.Not drawn: Artificial Analysis 39.2% on an earlier build, Oct 28, 2026. Source | Artificial Analysis | Oct 28, 2026 |
| Tool use | AutomationBench-AAScore, Artificial Analysis run | 66.6% | DeepSeek V4.1 Flash 1017 (Max)Effort: max. Harness: Artificial Analysis AutomationBench harness. Run on the Oct 17, 2026 build.Not drawn: Artificial Analysis 68.9% on an earlier build, Oct 28, 2026. Source | Artificial Analysis | Oct 28, 2026 |
| Computer use | OSWorld 2.1Metric and task set not named by Moonshot, v2.1 release. Moonshot AI's run of the October 17 build at max effort in its Kimi Agent harness, from the Kimi K3.1 Pro launch table. Moonshot does not name the metric.Stands in for OSWorld 2.1, partial score, full 108-task set, v2.1 release, which has no run of DeepSeek V4.1 Flash yet. | 69.3% | DeepSeek-V4.1-Flash-1017 (max)Effort: max. Harness: Kimi Agent harness. Run on the Oct 17, 2026 build.Not drawn: MiniMax 54.3% on an earlier build, Oct 19, 2026. Source | Moonshot AIRun by Moonshot AI | Oct 23, 2026 |
| Long context | AA-LCR v1.1Accuracy, Artificial Analysis run | 82.7% | DeepSeek V4.1 Flash 1017 (Max)Effort: max. Harness: none. Run on the Oct 17, 2026 build.Not drawn: Artificial Analysis 84% on an earlier build, Oct 28, 2026. Source | Artificial Analysis | Oct 28, 2026 |
| Multimodal | MMMU-ProOverall accuracy, no tools | 80.6% | DeepSeek V4.1 Flash 1017 (Max)Effort: max. Harness: none. Run on the Oct 17, 2026 build.Not drawn: Artificial Analysis 77% on an earlier build, Oct 28, 2026. Source | Artificial Analysis | Oct 28, 2026 |
| Factuality | AA-Omniscience AccuracyAccuracy, Artificial Analysis run | 39.6%Hallucination rate 64.1% in the same run (lower is better) | DeepSeek V4.1 Flash 1017 (Max)Effort: max. Harness: none. Run on the Oct 17, 2026 build.Not drawn: Artificial Analysis 46.4% on an earlier build, Oct 27, 2026. Source | Artificial Analysis | Oct 28, 2026 |
| Answers in full | SpeechMap% Complete over 2,120 contested requests, reasoning-on entry | Published only for another harness, setting or build, listed in the table | Not drawn: SpeechMap.AI 67.2% on an earlier build, Oct 27, 2026. Source | ||
| Instruction following | MultiChallengeAccuracy, Scale AI run. On Oct 28, 2026, Scale AI ranked the October 17 build 5th. | 74.9%Plus or minus 5.3 points (95% interval) | Deepseek V4p1 Flash 1017Effort: not published. Harness: none. Run on the Oct 17, 2026 build. | Scale AI SEAL | Oct 28, 2026 |
Price and speed
- DeepSeek V4.1 Flash lists at $0.30 per million input tokens and $1.20 per million output tokens. Peak-hours rate; off-peak $0.15 / $0.60, as DeepSeek lists it. DeepSeek pricing, Oct 27, 2026.
- DeepSeek V4.1 Flash, at max effort, writes 176.7 output tokens per second at the median across the providers serving it, and its first token arrives 0.9 s after the request. Artificial Analysis, Oct 28, 2026.
- Fastest on the chart is the shortest time to a 500-token answer: time to first token plus 500 tokens at the median output speed.
Every model with a result, axis by axis
57 models. A maker's own figure and another lab's run are marked with their benchmark; a missing result reads "Not yet published", never zero.
| Model | Agentic coding | Code | Math | Science | Hard reasoning | Tool use | Computer use | Long context | Multimodal | Factuality | Answers in full | Instructions |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| DeepSeek V4.1 Flash | 31.8% | 55.9% | 71.2% | 93.2% | 43.3% | 66.6% | 69.3%Run by Moonshot AIOSWorld 2.1 | 82.7% | 80.6% | 39.6% | Not yet published | 74.9% |
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| DeepSeek V4 Pro | 14.1% | 51% | 64.6% | 91.7% | 41% | 56.7% | Not yet published | 80.3% | Not yet published | 45.2% | 72% | Not yet published |
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| Claude Haiku 5.5 | 36.4% | 55% | 75.1% | 89.6% | 44.4% | 35.4% | 72.4%Reported by AnthropicOSWorld 2.1 | 82.7% | Not yet published | 34.7% | 78.8% | 67.7% |
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| Claude Sonnet 5.5 | 64.1% | 61% | 88.8% | 95.6% | 55% | 71.8% | 80.1%Reported by Anthropic | 82.7% | Not yet published | 51.5% | 81.6% | Not yet published |
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| Claude Opus 5.5 | 65.2% | 66.9% | 91.2% | 90.6% | 61.4% | 69.5% | 81.8%Reported by Anthropic | 84.7% | 87.7% | 65.5% | 82.8% | Not yet published |
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| Claude Fable 5.1 | 58.1% | 63.1% | 90.2% | 93.4%Run by Vals.ai | 59.1% | 59.4% | 80.7%Reported by Anthropic | 85.3% | 86.3%Run by Moonshot AI | 68.4% | 72.4% | Not yet published |
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| Claude Opus 5 | 53.5% | 56.4% | 85.6% | 93.9% | 54.9% | 56.6% | 77.7% | 79.3% | 84.7% | 60.9% | 73.7% | Not yet published |
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| Claude Sonnet 5 | 10.6% | 54.3% | 65.6% | 80.3% | 41.3% | 36.5% | 57%Reported by Anthropic | 82% | 77.3% | 40.1% | Not yet published | Not yet published |
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| Claude Fable 5 | 41.4% | 61% | 87% | 85.9% | 55.5% | 54.1% | Not yet published | 82.3% | Not yet published | 65.4% | 64.8% | 63.5%Run by Artificial AnalysisIFBench |
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| Claude Opus 4.8 | 23.2% | 54.4% | 80% | 91% | 48.7% | 45.6% | 54.8%Run by OSWorld teamOSWorld 2.0 | 77.7% | Not yet published | 48.8% | 67.4% | 62.2%Run by Artificial AnalysisIFBench |
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| Claude Opus 4.7 | Not yet published | 54.5% | 70.2% | 86.4% | 42.3% | Not yet published | 48.9%Run by OSWorld teamOSWorld 2.0 | 78.7% | 78.8% | 48.9% | 70.2% | 58.6%Run by Artificial AnalysisIFBench |
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| Claude Sonnet 4.6 | 3%Run by Artificial AnalysisTerminal-Bench 4.0 | 50.1% | 71.1%Run by Epoch AIOTIS Mock AIME 2024-2025 | 78.8% | 33.6% | 20.1% | 41.5%Run by OSWorld teamOSWorld 2.0 | 80% | 73.3% | 40.9% | 35.8% | 56.6%Run by Artificial AnalysisIFBench |
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| Claude Opus 4.6 | Not yet published | Not yet published | 66% | 88.4% | 39.9% | Not yet published | Not yet published | 78% | 75.4% | 47% | 59.9% | 37.2% |
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| Claude Opus 4.5 | Not yet published | Not yet published | 34.4% | 86% | 30.1% | Not yet published | Not yet published | 77.3% | 74% | 46.6% | 57.5% | 59% |
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| Claude Haiku 4.5 | Not yet published | 42.2% | 66.7%Run by Epoch AIOTIS Mock AIME 2024-2025 | 71.2% | 10.4% | 3.2% | Not yet published | 74.3% | 58.6% | 18% | 24.7% | 50.5% |
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| Claude Sonnet 4.5 | Not yet published | 45.7% | 23.9% | 82.3% | 17.8% | 14.1% | Not yet published | 72.3% | 68.7% | 32.9% | 31.4% | 55.3% |
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| GPT-6.1 Terra | 49.5% | 55.1% | 90.9% | 94.3% | 46.2% | 60.2% | 74.2%Reported by OpenAIOSWorld 2.1 | 82.7% | 84.7% | 47.6% | Not yet published | 74.2% |
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| GPT-6.1 Sol | 55.1% | 54.2% | 93.7% | 95.4% | 52.9% | 64.9% | 78%Reported by OpenAIOSWorld 2.1 | 83% | 86% | 61.8% | 69.5% | 82% |
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| GPT-6 Luna | 13.6% | 54.6% | 78.9% | 90.5% | 38.5% | 53.2% | 48.9%Run by AnthropicOSWorld 2.1 | 83.3% | 79.7% | 39.6% | 63.4% | Not yet published |
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| GPT-6 Astra | 59.6% | 56.5% | 93.7% | 95.8% | 54.7% | 68.5% | 75.8%Run by Meta | 80.7% | 86.9% | 61.6% | 68.2% | Not yet published |
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| GPT-5.6 Sol | 37.9% | 57.1% | 89.1% | 93.5% | 49.5% | 60.1% | 62.7%Run by OSWorld teamOSWorld 2.0 | 84% | 83.4% | 69.7%Run by Epoch AISimpleQA Verified | Not yet published | 72.7%Run by Artificial AnalysisIFBench |
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| GPT-5.6 Terra | 22.7% | 55% | 86% | 93.3% | 42.9% | 59.6% | Not yet published | 83% | 80.7% | 42.3% | Not yet published | 71.2%Run by Artificial AnalysisIFBench |
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| GPT-5.6 Luna | 11.6% | 53.6% | 82.1% | 91.6% | 39.5% | 50.2% | Not yet published | 83.7% | 78.6% | 41%Run by Epoch AISimpleQA Verified | Not yet published | Not yet published |
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| GPT-5.5 | 14.6%Run by Artificial AnalysisTerminal-Bench 4.0 | 55.8% | 85.3% | 93.5%Run by Artificial Analysis | 45.8% | 47.3% | 49.5%Run by OSWorld teamOSWorld 2.0 | 84.3% | 79.9% | 63%Run by Epoch AISimpleQA Verified | Not yet published | 75.9%Run by Artificial AnalysisIFBench |
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| GPT-5.4 | Not yet published | Not yet published | 78.6% | 93.3% | 43.7% | Not yet published | Not yet published | 82% | 78.4% | Not yet published | Not yet published | 73.9%Run by Artificial AnalysisIFBench |
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| gpt-oss-120b | 14.2%Run by Terminal-Bench (via Epoch AI)Terminal-Bench 2.0 | 34% | 88.9%Run by Epoch AIOTIS Mock AIME 2024-2025 | 75.8% | 19.6% | 0.2% | Not yet published | 52% | Not yet published | 16.8%Reported by OpenAISimpleQA | 36.3% | 45.3% |
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| GPT-6 Sol | 44.4% | 57.6% | 89.8% | 94.3% | 47.9% | 61.6% | 64.4%Reported by OpenAIOSWorld 2.0 | 83.7% | 82.9% | 54.5% | 64% | Not yet published |
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| GPT-5.3-Codex | Not yet published | Not yet published | Not yet published | 91.5%Run by Artificial Analysis | 42.5% | Not yet published | Not yet published | 83.3% | 78.5% | Not yet published | Not yet published | 75.4%Run by Artificial AnalysisIFBench |
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| Gemini 4 Argon | 57.6% | 61.8% | 86% | 96.4% | 57.1% | 77.5% | 69.2%Reported by GoogleOSWorld 2.0 | 79.7% | Not yet published | 48.3% | 87% | 78.7% |
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| Gemini 3.8 Flash | 19.7% | 56.6% | 68.4% | 95.4% | 47.8% | 59.9% | 59%Reported by GoogleOSWorld 2.0 | 81.3% | 85.6% | 50.5% | 86.1% | Not yet published |
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| Gemma 4 31B | Not yet published | 45.5% | Not yet published | 85.7%Run by Artificial AnalysisGPQA Diamond | 23.6% | 4.9% | Not yet published | 69.7% | 73.4% | 10.4%Run by Epoch AISimpleQA Verified | 82.3% | 75.6%Run by Artificial AnalysisIFBench |
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| Gemini 3.1 Pro Preview | 2.5% | 58.7% | 59.6% | 94.4% | 47% | 35.4% | Not yet published | 82% | 82.4% | 54.9% | 59.9% | 71.4% |
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| Gemini 3.6 Flash | 7.1%Run by Artificial AnalysisTerminal-Bench 4.0 | 53.4% | 58.9% | 94.1% | 40.8% | 53% | 83%Reported by GoogleOSWorld-Verified | 80% | 83.2% | 66.2%Run by Epoch AISimpleQA Verified | 87.2% | Not yet published |
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| Kimi K3.1 Pro | 63.6% | 60.8% | Not yet published | 94.2%Reported by Moonshot AI | 52.5% | 73.3% | 79.6%Reported by Moonshot AIOSWorld 2.1 | 86.3% | 83.9% | 48.9% | Not yet published | Not yet published |
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| Kimi K3 | 17.2% | 59.5% | 72.2% | 93.1% | 46.9% | 58.3% | Not yet published | 88.7% | 80.5% | 50.6%Run by Epoch AISimpleQA Verified | 65.9% | Not yet published |
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| Kimi K2.7 Code | 1%Run by Artificial AnalysisTerminal-Bench 4.0 | 47.8% | 54% | 87.9% | 35% | 24.5% | Not yet published | 79.3% | Not yet published | 36.5%Run by Epoch AISimpleQA Verified | Not yet published | 63.1%Run by Artificial AnalysisIFBench |
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| Mistral Large 4 | 24.7%Run by Artificial AnalysisTerminal-Bench 4.0 | Not yet published | Not yet published | Not yet published | Not yet published | 57.8% | Not yet published | Not yet published | Not yet published | 26% | Not yet published | Not yet published |
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| Mistral Medium 3.5 | 0%Run by Artificial AnalysisTerminal-Bench 4.0 | 40.2% | Not yet published | 74.8%Run by Artificial AnalysisGPQA Diamond | 13.8% | 6.3% | Not yet published | 69.3% | 64.9% | 23% | 70.5% | 68.8%Run by Artificial AnalysisIFBench |
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| Grok 4.7 | 28.8% | 57.4% | 53% | 92.7% | 43.1% | 65.6% | Not yet published | 76.7% | Not yet published | 42.7% | 64.1% | Not yet published |
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| Grok 4.6 | 17.2% | 56.5% | 66% | 93.2% | 42.9% | 66.7% | Not yet published | 80.3% | Not yet published | 48.9%Run by Epoch AISimpleQA Verified | 83.6% | Not yet published |
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| Grok 4.5 | 8.6% | 55% | 57.2% | 93.4% | 42.7% | 57.9% | Not yet published | 79.3% | 80.4% | 48.3%Run by Epoch AISimpleQA Verified | 93.1% | Not yet published |
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| MiniMax M3.1 Flash | 25.3% | 53.4% | Not yet published | Not yet published | 48% | 72.5% | 61.7%Reported by MiniMaxOSWorld 2.0 | 79.7% | 79.1% | 45.1% | Not yet published | Not yet published |
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| Mercury 3 | 3% | Not yet published | Not yet published | Not yet published | Not yet published | Not yet published | Not yet published | Not yet published | Not yet published | Not yet published | Not yet published | Not yet published |
| GLM-5.3-Flash | 37.4% | 51.6% | 55.8% | 90.2% | 39.9% | 60.4% | 59.1%Reported by Z.aiOSWorld 2.0 | 80% | 86%Run by Vals.aiMMMU-Pro | 28.2% | 65.4% | Not yet published |
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| GLM-5.3 | 38.9% | 59% | 68.8% | 90.9% | 42.3% | 62.2% | Not yet published | 79.7% | Not yet published | 32.3% | 71.5% | Not yet published |
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| GLM-5.2 | 1%Run by Artificial AnalysisTerminal-Bench 4.0 | 51.2% | 59.2% | Not yet published | 41.1% | 28.4% | Not yet published | 78.3% | Not yet published | 34.2%Run by Epoch AISimpleQA Verified | Not yet published | 73.3%Run by Artificial AnalysisIFBench |
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| Muse Spark Open | 6.6% | 58.4% | 69.8% | 88.6% | 43.9% | 49.7% | 80.4%Reported by MetaOSWorld-Verified | 78.3% | 80.9% | 42% | Not yet published | 74.2% |
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| Muse Wonder | 49.5% | 60.3% | 82.1% | Not yet published | 50.1% | 68.1% | 72.6%Reported by Meta | 80.7% | Not yet published | 38% | 42.7% | Not yet published |
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| Muse Spark 1.3 | 10.6% | 58.8% | 74% | 93.5%Run by Artificial AnalysisGPQA Diamond | 48.7% | 57.9% | 69.6% | 83% | 82% | 38% | 25.8% | Not yet published |
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| Llama 4 Scout | Not yet published | 21.3% | 7.8%Run by Epoch AIOTIS Mock AIME 2024-2025 | 51.8% | 3.8% | 0.2% | Not yet published | 27.7% | 52.9% | Not yet published | 70.1% | 39.5%Run by Artificial AnalysisIFBench |
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| Llama 4 Maverick | Not yet published | 31.7% | 20.6%Run by Epoch AIOTIS Mock AIME 2024-2025 | 67% | 4.9% | 0.2% | Not yet published | 50% | 62.1% | Not yet published | 58.3% | 43%Run by Artificial AnalysisIFBench |
| ||||||||||||
| Qwen3.8 27B | 5.6%Run by Artificial AnalysisTerminal-Bench 4.0 | 46.6% | Not yet published | 90.5%Run by Artificial AnalysisGPQA Diamond | 33.9% | 48.2% | 84.3%Reported by AlibabaOSWorld-Verified | 82% | 76.3% | 17.3% | Not yet published | 79.5%Reported by AlibabaIFBench |
| ||||||||||||
| Qwen3.8 Max | 38.9% | 52.1% | 65.6% | 92.3% | 43.1% | 56.2% | Not yet published | 80.3% | 82.8% | 29.5% | 65.3% | Not yet published |
| ||||||||||||
| MiMo-V2.6-Pro | 31.3% | 60.9% | Not yet published | Not yet published | 49.4% | 58.6% | 82%Reported by XiaomiOSWorld-Verified | 86.3% | Not yet published | 34.8% | 66.5% | Not yet published |
| ||||||||||||
| MiMo-V2.6-Flash | 24.2% | 51.3% | Not yet published | Not yet published | 35.1% | 64.1% | 80.8%Reported by XiaomiOSWorld-Verified | 74.3% | 73.1% | 27.2% | 66.9% | Not yet published |
| ||||||||||||
| Ling 3.1 Flash | 32.8%Run by Artificial AnalysisTerminal-Bench 4.0 | 56.8% | Not yet published | Not yet published | 43.5% | 67.5% | Not yet published | 82.3% | Not yet published | 26.5% | Not yet published | Not yet published |
| ||||||||||||
| Step 5 Preview | 31.8% | 58.9% | Not yet published | 93.5%Reported by StepFunGPQA Diamond | 46.5% | 51% | Not yet published | 88.3% | 76.4% | 36.4% | 59.7% | Not yet published |
| ||||||||||||
Agentic codingTerminal-Bench 4.0
- Claude Opus 5.565.2%
- Claude Sonnet 5.564.1%
- Kimi K3.1 Pro63.6%
- GPT-6 Astra59.6%
- Claude Fable 5.158.1%
- Gemini 4 Argon57.6%
- GPT-6.1 Sol55.1%
- Claude Opus 553.5%
- GPT-6.1 Terra49.5%
- Muse Wonder49.5%
- GPT-6 Sol44.4%
- Claude Fable 541.4%
- GLM-5.338.9%
- Qwen3.8 Max38.9%
- GPT-5.6 Sol37.9%
- GLM-5.3-Flash37.4%
- Claude Haiku 5.536.4%
- DeepSeek V4.1 Flash31.8%
- Step 5 Preview31.8%
- MiMo-V2.6-Pro31.3%
- Grok 4.728.8%
- MiniMax M3.1 Flash25.3%
- MiMo-V2.6-Flash24.2%
- Claude Opus 4.823.2%
- GPT-5.6 Terra22.7%
- Gemini 3.8 Flash19.7%
- Kimi K317.2%
- Grok 4.617.2%
- DeepSeek V4 Pro14.1%
- GPT-6 Luna13.6%
- GPT-5.6 Luna11.6%
- Claude Sonnet 510.6%
- Muse Spark 1.310.6%
- Grok 4.58.6%
- Muse Spark Open6.6%
- Mercury 33%
- Gemini 3.1 Pro Preview2.5%
- Ling 3.1 Flash32.8%Artificial Analysis's run, Terminal-Bench 4.0
- Mistral Large 424.7%Artificial Analysis's run, Terminal-Bench 4.0
- GPT-5.514.6%Artificial Analysis's run, Terminal-Bench 4.0
- gpt-oss-120b14.2%Terminal-Bench's run, Terminal-Bench 2.0
- Gemini 3.6 Flash7.1%Artificial Analysis's run, Terminal-Bench 4.0
- Qwen3.8 27B5.6%Artificial Analysis's run, Terminal-Bench 4.0
- Claude Sonnet 4.63%Artificial Analysis's run, Terminal-Bench 4.0
- Kimi K2.7 Code1%Artificial Analysis's run, Terminal-Bench 4.0
- GLM-5.21%Artificial Analysis's run, Terminal-Bench 4.0
- Mistral Medium 3.50%Artificial Analysis's run, Terminal-Bench 4.0
The other models in the grid have no result on Terminal-Bench 4.0 yet.
CodeSciCode
- Claude Opus 5.566.9%
- Claude Fable 5.163.1%
- Gemini 4 Argon61.8%
- Claude Sonnet 5.561%
- Claude Fable 561%
- MiMo-V2.6-Pro60.9%
- Kimi K3.1 Pro60.8%
- Muse Wonder60.3%
- Kimi K359.5%
- GLM-5.359%
- Step 5 Preview58.9%
- Muse Spark 1.358.8%
- Gemini 3.1 Pro Preview58.7%
- Muse Spark Open58.4%
- GPT-6 Sol57.6%
- Grok 4.757.4%
- GPT-5.6 Sol57.1%
- Ling 3.1 Flash56.8%
- Gemini 3.8 Flash56.6%
- GPT-6 Astra56.5%
- Grok 4.656.5%
- Claude Opus 556.4%
- DeepSeek V4.1 Flash55.9%
- GPT-5.555.8%
- GPT-6.1 Terra55.1%
- Claude Haiku 5.555%
- GPT-5.6 Terra55%
- Grok 4.555%
- GPT-6 Luna54.6%
- Claude Opus 4.754.5%
- Claude Opus 4.854.4%
- Claude Sonnet 554.3%
- GPT-6.1 Sol54.2%
- GPT-5.6 Luna53.6%
- Gemini 3.6 Flash53.4%
- MiniMax M3.1 Flash53.4%
- Qwen3.8 Max52.1%
- GLM-5.3-Flash51.6%
- MiMo-V2.6-Flash51.3%
- GLM-5.251.2%
- DeepSeek V4 Pro51%
- Claude Sonnet 4.650.1%
- Kimi K2.7 Code47.8%
- Qwen3.8 27B46.6%
- Claude Sonnet 4.545.7%
- Gemma 4 31B45.5%
- Claude Haiku 4.542.2%
- Mistral Medium 3.540.2%
- gpt-oss-120b34%
- Llama 4 Maverick31.7%
- Llama 4 Scout21.3%
The other models in the grid have no result on SciCode yet.
MathFrontierMath Tiers 1-3
- GPT-6.1 Sol93.7%
- GPT-6 Astra93.7%
- Claude Opus 5.591.2%
- GPT-6.1 Terra90.9%
- Claude Fable 5.190.2%
- GPT-6 Sol89.8%
- GPT-5.6 Sol89.1%
- Claude Sonnet 5.588.8%
- Claude Fable 587%
- GPT-5.6 Terra86%
- Gemini 4 Argon86%
- Claude Opus 585.6%
- GPT-5.585.3%
- GPT-5.6 Luna82.1%
- Muse Wonder82.1%
- Claude Opus 4.880%
- GPT-6 Luna78.9%
- GPT-5.478.6%
- Claude Haiku 5.575.1%
- Muse Spark 1.374%
- Kimi K372.2%
- DeepSeek V4.1 Flash71.2%
- Claude Opus 4.770.2%
- Muse Spark Open69.8%
- GLM-5.368.8%
- Gemini 3.8 Flash68.4%
- Claude Opus 4.666%
- Grok 4.666%
- Claude Sonnet 565.6%
- Qwen3.8 Max65.6%
- DeepSeek V4 Pro64.6%
- Gemini 3.1 Pro Preview59.6%
- GLM-5.259.2%
- Gemini 3.6 Flash58.9%
- Grok 4.557.2%
- GLM-5.3-Flash55.8%
- Kimi K2.7 Code54%
- Grok 4.753%
- Claude Opus 4.534.4%
- Claude Sonnet 4.523.9%
- gpt-oss-120b88.9%Epoch AI's run, OTIS Mock AIME 2024-2025
- Claude Sonnet 4.671.1%Epoch AI's run, OTIS Mock AIME 2024-2025
- Claude Haiku 4.566.7%Epoch AI's run, OTIS Mock AIME 2024-2025
- Llama 4 Maverick20.6%Epoch AI's run, OTIS Mock AIME 2024-2025
- Llama 4 Scout7.8%Epoch AI's run, OTIS Mock AIME 2024-2025
The other models in the grid have no result on FrontierMath Tiers 1-3 yet.
ScienceGPQA Diamond
- Gemini 4 Argon96.4%
- GPT-6 Astra95.8%
- Claude Sonnet 5.595.6%
- GPT-6.1 Sol95.4%
- Gemini 3.8 Flash95.4%
- Gemini 3.1 Pro Preview94.4%
- GPT-6.1 Terra94.3%
- GPT-6 Sol94.3%
- Gemini 3.6 Flash94.1%
- Claude Opus 593.9%
- GPT-5.6 Sol93.5%
- Grok 4.593.4%
- GPT-5.6 Terra93.3%
- GPT-5.493.3%
- DeepSeek V4.1 Flash93.2%
- Grok 4.693.2%
- Kimi K393.1%
- Grok 4.792.7%
- Qwen3.8 Max92.3%
- DeepSeek V4 Pro91.7%
- GPT-5.6 Luna91.6%
- Claude Opus 4.891%
- GLM-5.390.9%
- Claude Opus 5.590.6%
- GPT-6 Luna90.5%
- GLM-5.3-Flash90.2%
- Claude Haiku 5.589.6%
- Muse Spark Open88.6%
- Claude Opus 4.688.4%
- Kimi K2.7 Code87.9%
- Claude Opus 4.786.4%
- Claude Opus 4.586%
- Claude Fable 585.9%
- Claude Sonnet 4.582.3%
- Claude Sonnet 580.3%
- Claude Sonnet 4.678.8%
- gpt-oss-120b75.8%
- Claude Haiku 4.571.2%
- Llama 4 Maverick67%
- Llama 4 Scout51.8%
- Kimi K3.1 Pro94.2%Moonshot AI's own figure
- GPT-5.593.5%Artificial Analysis's run
- Muse Spark 1.393.5%Artificial Analysis's run, GPQA Diamond
- Step 5 Preview93.5%StepFun's own figure, GPQA Diamond
- Claude Fable 5.193.4%Vals.ai's run
- GPT-5.3-Codex91.5%Artificial Analysis's run
- Qwen3.8 27B90.5%Artificial Analysis's run, GPQA Diamond
- Gemma 4 31B85.7%Artificial Analysis's run, GPQA Diamond
- Mistral Medium 3.574.8%Artificial Analysis's run, GPQA Diamond
The other models in the grid have no result on GPQA Diamond yet.
Hard reasoningHumanity's Last Exam
- Claude Opus 5.561.4%
- Claude Fable 5.159.1%
- Gemini 4 Argon57.1%
- Claude Fable 555.5%
- Claude Sonnet 5.555%
- Claude Opus 554.9%
- GPT-6 Astra54.7%
- GPT-6.1 Sol52.9%
- Kimi K3.1 Pro52.5%
- Muse Wonder50.1%
- GPT-5.6 Sol49.5%
- MiMo-V2.6-Pro49.4%
- Claude Opus 4.848.7%
- Muse Spark 1.348.7%
- MiniMax M3.1 Flash48%
- GPT-6 Sol47.9%
- Gemini 3.8 Flash47.8%
- Gemini 3.1 Pro Preview47%
- Kimi K346.9%
- Step 5 Preview46.5%
- GPT-6.1 Terra46.2%
- GPT-5.545.8%
- Claude Haiku 5.544.4%
- Muse Spark Open43.9%
- GPT-5.443.7%
- Ling 3.1 Flash43.5%
- DeepSeek V4.1 Flash43.3%
- Grok 4.743.1%
- Qwen3.8 Max43.1%
- GPT-5.6 Terra42.9%
- Grok 4.642.9%
- Grok 4.542.7%
- GPT-5.3-Codex42.5%
- Claude Opus 4.742.3%
- GLM-5.342.3%
- Claude Sonnet 541.3%
- GLM-5.241.1%
- DeepSeek V4 Pro41%
- Gemini 3.6 Flash40.8%
- Claude Opus 4.639.9%
- GLM-5.3-Flash39.9%
- GPT-5.6 Luna39.5%
- GPT-6 Luna38.5%
- MiMo-V2.6-Flash35.1%
- Kimi K2.7 Code35%
- Qwen3.8 27B33.9%
- Claude Sonnet 4.633.6%
- Claude Opus 4.530.1%
- Gemma 4 31B23.6%
- gpt-oss-120b19.6%
- Claude Sonnet 4.517.8%
- Mistral Medium 3.513.8%
- Claude Haiku 4.510.4%
- Llama 4 Maverick4.9%
- Llama 4 Scout3.8%
The other models in the grid have no result on Humanity's Last Exam yet.
Tool useAutomationBench-AA
- Gemini 4 Argon77.5%
- Kimi K3.1 Pro73.3%
- MiniMax M3.1 Flash72.5%
- Claude Sonnet 5.571.8%
- Claude Opus 5.569.5%
- GPT-6 Astra68.5%
- Muse Wonder68.1%
- Ling 3.1 Flash67.5%
- Grok 4.666.7%
- DeepSeek V4.1 Flash66.6%
- Grok 4.765.6%
- GPT-6.1 Sol64.9%
- MiMo-V2.6-Flash64.1%
- GLM-5.362.2%
- GPT-6 Sol61.6%
- GLM-5.3-Flash60.4%
- GPT-6.1 Terra60.2%
- GPT-5.6 Sol60.1%
- Gemini 3.8 Flash59.9%
- GPT-5.6 Terra59.6%
- Claude Fable 5.159.4%
- MiMo-V2.6-Pro58.6%
- Kimi K358.3%
- Grok 4.557.9%
- Muse Spark 1.357.9%
- Mistral Large 457.8%
- DeepSeek V4 Pro56.7%
- Claude Opus 556.6%
- Qwen3.8 Max56.2%
- Claude Fable 554.1%
- GPT-6 Luna53.2%
- Gemini 3.6 Flash53%
- Step 5 Preview51%
- GPT-5.6 Luna50.2%
- Muse Spark Open49.7%
- Qwen3.8 27B48.2%
- GPT-5.547.3%
- Claude Opus 4.845.6%
- Claude Sonnet 536.5%
- Claude Haiku 5.535.4%
- Gemini 3.1 Pro Preview35.4%
- GLM-5.228.4%
- Kimi K2.7 Code24.5%
- Claude Sonnet 4.620.1%
- Claude Sonnet 4.514.1%
- Mistral Medium 3.56.3%
- Gemma 4 31B4.9%
- Claude Haiku 4.53.2%
- gpt-oss-120b0.2%
- Llama 4 Scout0.2%
- Llama 4 Maverick0.2%
The other models in the grid have no result on AutomationBench-AA yet.
Computer useOSWorld 2.1
- Claude Opus 577.7%
- Muse Spark 1.369.6%
- Qwen3.8 27B84.3%Alibaba's own figure, OSWorld-Verified
- Gemini 3.6 Flash83%Google's own figure, OSWorld-Verified
- MiMo-V2.6-Pro82%Xiaomi's own figure, OSWorld-Verified
- Claude Opus 5.581.8%Anthropic's own figure
- MiMo-V2.6-Flash80.8%Xiaomi's own figure, OSWorld-Verified
- Claude Fable 5.180.7%Anthropic's own figure
- Muse Spark Open80.4%Meta's own figure, OSWorld-Verified
- Claude Sonnet 5.580.1%Anthropic's own figure
- Kimi K3.1 Pro79.6%Moonshot AI's own figure, OSWorld 2.1
- GPT-6.1 Sol78%OpenAI's own figure, OSWorld 2.1
- GPT-6 Astra75.8%Meta's run
- GPT-6.1 Terra74.2%OpenAI's own figure, OSWorld 2.1
- Muse Wonder72.6%Meta's own figure
- Claude Haiku 5.572.4%Anthropic's own figure, OSWorld 2.1
- DeepSeek V4.1 Flash69.3%Moonshot AI's run, OSWorld 2.1
- Gemini 4 Argon69.2%Google's own figure, OSWorld 2.0
- GPT-6 Sol64.4%OpenAI's own figure, OSWorld 2.0
- GPT-5.6 Sol62.7%OSWorld team's run, OSWorld 2.0
- MiniMax M3.1 Flash61.7%MiniMax's own figure, OSWorld 2.0
- GLM-5.3-Flash59.1%Z.ai's own figure, OSWorld 2.0
- Gemini 3.8 Flash59%Google's own figure, OSWorld 2.0
- Claude Sonnet 557%Anthropic's own figure
- Claude Opus 4.854.8%OSWorld team's run, OSWorld 2.0
- GPT-5.549.5%OSWorld team's run, OSWorld 2.0
- Claude Opus 4.748.9%OSWorld team's run, OSWorld 2.0
- GPT-6 Luna48.9%Anthropic's run, OSWorld 2.1
- Claude Sonnet 4.641.5%OSWorld team's run, OSWorld 2.0
The other models in the grid have no result on OSWorld 2.1 yet.
Long contextAA-LCR v1.1
- Kimi K388.7%
- Step 5 Preview88.3%
- Kimi K3.1 Pro86.3%
- MiMo-V2.6-Pro86.3%
- Claude Fable 5.185.3%
- Claude Opus 5.584.7%
- GPT-5.584.3%
- GPT-5.6 Sol84%
- GPT-5.6 Luna83.7%
- GPT-6 Sol83.7%
- GPT-6 Luna83.3%
- GPT-5.3-Codex83.3%
- GPT-6.1 Sol83%
- GPT-5.6 Terra83%
- Muse Spark 1.383%
- DeepSeek V4.1 Flash82.7%
- Claude Haiku 5.582.7%
- Claude Sonnet 5.582.7%
- GPT-6.1 Terra82.7%
- Claude Fable 582.3%
- Ling 3.1 Flash82.3%
- Claude Sonnet 582%
- GPT-5.482%
- Gemini 3.1 Pro Preview82%
- Qwen3.8 27B82%
- Gemini 3.8 Flash81.3%
- GPT-6 Astra80.7%
- Muse Wonder80.7%
- DeepSeek V4 Pro80.3%
- Grok 4.680.3%
- Qwen3.8 Max80.3%
- Claude Sonnet 4.680%
- Gemini 3.6 Flash80%
- GLM-5.3-Flash80%
- Gemini 4 Argon79.7%
- MiniMax M3.1 Flash79.7%
- GLM-5.379.7%
- Claude Opus 579.3%
- Kimi K2.7 Code79.3%
- Grok 4.579.3%
- Claude Opus 4.778.7%
- GLM-5.278.3%
- Muse Spark Open78.3%
- Claude Opus 4.678%
- Claude Opus 4.877.7%
- Claude Opus 4.577.3%
- Grok 4.776.7%
- Claude Haiku 4.574.3%
- MiMo-V2.6-Flash74.3%
- Claude Sonnet 4.572.3%
- Gemma 4 31B69.7%
- Mistral Medium 3.569.3%
- gpt-oss-120b52%
- Llama 4 Maverick50%
- Llama 4 Scout27.7%
The other models in the grid have no result on AA-LCR v1.1 yet.
MultimodalMMMU-Pro
- Claude Opus 5.587.7%
- GPT-6 Astra86.9%
- GPT-6.1 Sol86%
- Gemini 3.8 Flash85.6%
- Claude Opus 584.7%
- GPT-6.1 Terra84.7%
- Kimi K3.1 Pro83.9%
- GPT-5.6 Sol83.4%
- Gemini 3.6 Flash83.2%
- GPT-6 Sol82.9%
- Qwen3.8 Max82.8%
- Gemini 3.1 Pro Preview82.4%
- Muse Spark 1.382%
- Muse Spark Open80.9%
- GPT-5.6 Terra80.7%
- DeepSeek V4.1 Flash80.6%
- Kimi K380.5%
- Grok 4.580.4%
- GPT-5.579.9%
- GPT-6 Luna79.7%
- MiniMax M3.1 Flash79.1%
- Claude Opus 4.778.8%
- GPT-5.6 Luna78.6%
- GPT-5.3-Codex78.5%
- GPT-5.478.4%
- Claude Sonnet 577.3%
- Step 5 Preview76.4%
- Qwen3.8 27B76.3%
- Claude Opus 4.675.4%
- Claude Opus 4.574%
- Gemma 4 31B73.4%
- Claude Sonnet 4.673.3%
- MiMo-V2.6-Flash73.1%
- Claude Sonnet 4.568.7%
- Mistral Medium 3.564.9%
- Llama 4 Maverick62.1%
- Claude Haiku 4.558.6%
- Llama 4 Scout52.9%
- Claude Fable 5.186.3%Moonshot AI's run
- GLM-5.3-Flash86%Vals.ai's run, MMMU-Pro
The other models in the grid have no result on MMMU-Pro yet.
FactualityAA-Omniscience Accuracy
- Claude Fable 5.168.4%
- Claude Opus 5.565.5%
- Claude Fable 565.4%
- GPT-6.1 Sol61.8%
- GPT-6 Astra61.6%
- Claude Opus 560.9%
- Gemini 3.1 Pro Preview54.9%
- GPT-6 Sol54.5%
- Claude Sonnet 5.551.5%
- Gemini 3.8 Flash50.5%
- Claude Opus 4.748.9%
- Kimi K3.1 Pro48.9%
- Claude Opus 4.848.8%
- Gemini 4 Argon48.3%
- GPT-6.1 Terra47.6%
- Claude Opus 4.647%
- Claude Opus 4.546.6%
- DeepSeek V4 Pro45.2%
- MiniMax M3.1 Flash45.1%
- Grok 4.742.7%
- GPT-5.6 Terra42.3%
- Muse Spark Open42%
- Claude Sonnet 4.640.9%
- Claude Sonnet 540.1%
- DeepSeek V4.1 Flash39.6%
- GPT-6 Luna39.6%
- Muse Wonder38%
- Muse Spark 1.338%
- Step 5 Preview36.4%
- MiMo-V2.6-Pro34.8%
- Claude Haiku 5.534.7%
- Claude Sonnet 4.532.9%
- GLM-5.332.3%
- Qwen3.8 Max29.5%
- GLM-5.3-Flash28.2%
- MiMo-V2.6-Flash27.2%
- Ling 3.1 Flash26.5%
- Mistral Large 426%
- Mistral Medium 3.523%
- Claude Haiku 4.518%
- Qwen3.8 27B17.3%
- GPT-5.6 Sol69.7%Epoch AI's run, SimpleQA Verified
- Gemini 3.6 Flash66.2%Epoch AI's run, SimpleQA Verified
- GPT-5.563%Epoch AI's run, SimpleQA Verified
- Kimi K350.6%Epoch AI's run, SimpleQA Verified
- Grok 4.648.9%Epoch AI's run, SimpleQA Verified
- Grok 4.548.3%Epoch AI's run, SimpleQA Verified
- GPT-5.6 Luna41%Epoch AI's run, SimpleQA Verified
- Kimi K2.7 Code36.5%Epoch AI's run, SimpleQA Verified
- GLM-5.234.2%Epoch AI's run, SimpleQA Verified
- gpt-oss-120b16.8%OpenAI's own figure, SimpleQA
- Gemma 4 31B10.4%Epoch AI's run, SimpleQA Verified
The other models in the grid have no result on AA-Omniscience Accuracy yet.
Answers in fullSpeechMap
- Grok 4.593.1%
- Gemini 3.6 Flash87.2%
- Gemini 4 Argon87%
- Gemini 3.8 Flash86.1%
- Grok 4.683.6%
- Claude Opus 5.582.8%
- Gemma 4 31B82.3%
- Claude Sonnet 5.581.6%
- Claude Haiku 5.578.8%
- Claude Opus 573.7%
- Claude Fable 5.172.4%
- DeepSeek V4 Pro72%
- GLM-5.371.5%
- Mistral Medium 3.570.5%
- Claude Opus 4.770.2%
- Llama 4 Scout70.1%
- GPT-6.1 Sol69.5%
- GPT-6 Astra68.2%
- Claude Opus 4.867.4%
- MiMo-V2.6-Flash66.9%
- MiMo-V2.6-Pro66.5%
- Kimi K365.9%
- GLM-5.3-Flash65.4%
- Qwen3.8 Max65.3%
- Claude Fable 564.8%
- Grok 4.764.1%
- GPT-6 Sol64%
- GPT-6 Luna63.4%
- Claude Opus 4.659.9%
- Gemini 3.1 Pro Preview59.9%
- Step 5 Preview59.7%
- Llama 4 Maverick58.3%
- Claude Opus 4.557.5%
- Muse Wonder42.7%
- gpt-oss-120b36.3%
- Claude Sonnet 4.635.8%
- Claude Sonnet 4.531.4%
- Muse Spark 1.325.8%
- Claude Haiku 4.524.7%
The other models in the grid have no result on SpeechMap yet.
Instruction followingMultiChallenge
- GPT-6.1 Sol82%
- Gemini 4 Argon78.7%
- DeepSeek V4.1 Flash74.9%
- GPT-6.1 Terra74.2%
- Muse Spark Open74.2%
- Gemini 3.1 Pro Preview71.4%
- Claude Haiku 5.567.7%
- Claude Opus 4.559%
- Claude Sonnet 4.555.3%
- Claude Haiku 4.550.5%
- gpt-oss-120b45.3%
- Claude Opus 4.637.2%
- Qwen3.8 27B79.5%Alibaba's own figure, IFBench
- GPT-5.575.9%Artificial Analysis's run, IFBench
- Gemma 4 31B75.6%Artificial Analysis's run, IFBench
- GPT-5.3-Codex75.4%Artificial Analysis's run, IFBench
- GPT-5.473.9%Artificial Analysis's run, IFBench
- GLM-5.273.3%Artificial Analysis's run, IFBench
- GPT-5.6 Sol72.7%Artificial Analysis's run, IFBench
- GPT-5.6 Terra71.2%Artificial Analysis's run, IFBench
- Mistral Medium 3.568.8%Artificial Analysis's run, IFBench
- Claude Fable 563.5%Artificial Analysis's run, IFBench
- Kimi K2.7 Code63.1%Artificial Analysis's run, IFBench
- Claude Opus 4.862.2%Artificial Analysis's run, IFBench
- Claude Opus 4.758.6%Artificial Analysis's run, IFBench
- Claude Sonnet 4.656.6%Artificial Analysis's run, IFBench
- Llama 4 Maverick43%Artificial Analysis's run, IFBench
- Llama 4 Scout39.5%Artificial Analysis's run, IFBench
The other models in the grid have no result on MultiChallenge yet.
Releases
Every DeepSeek V4.1 release we track, newest first.
What practitioners report
Strongest on Speed, weakest on Developer experience.
Each figure is the share of accounts naming DeepSeek V4.1 Flash that speak well of it on that axis. An axis is scored once praise and concerns are both on record from at least five accounts by three authors. An account from the maker, a company that sells or serves the model, or the maker's expert program is listed and counts toward no figure.
| Axis | Favorable | Accounts |
|---|---|---|
| Quality and reasoningWhether its answers and code are right on the author's own task: reasoning, accuracy, instruction following, and consistency. | 61% | 25 favorable, 16 not, 40 authors |
| Tool use and structured outputWhether it calls tools correctly, returns valid structured output, and keeps agent loops on track. | 59% | 10 favorable, 7 not, 17 authors |
| Long contextHow it holds up over long documents, large codebases, long sessions, and many images or PDFs. | 58% | 7 favorable, 5 not, 12 authors |
| Developer experienceHow it is to build with: prompting, steering, effort settings, and support across SDKs and providers. | 35% | 8 favorable, 15 not, 23 authors |
| CostWhat the work costs: price per task, token use, and what caching and batch save. | 66% | 25 favorable, 13 not, 37 authors |
| SpeedResponse time, time to first token, and throughput. | 68% | 21 favorable, 10 not, 30 authors |
| ReliabilityWhether requests keep succeeding: overloaded errors, outages, rate limits, and changes that broke what worked. | 42% | 5 favorable, 7 not, 12 authors |
Every model on these seven axes
| Axis | DeepSeek V4.1 Flash | DeepSeek V4 Pro | Claude Haiku 5.5 | Claude Sonnet 5.5 | Claude Opus 5.5 | Claude Fable 5.1 | Claude Opus 5 | Claude Sonnet 5 | Claude Fable 5 | Claude Opus 4.8 | Claude Opus 4.7 | Claude Sonnet 4.6 | Claude Opus 4.6 | Claude Opus 4.5 | Claude Haiku 4.5 | Claude Sonnet 4.5 | GPT-6.1 Terra | GPT-6.1 Sol | GPT-6 Luna | GPT-6 Astra | GPT-5.6 Sol | GPT-5.6 Terra | GPT-5.6 Luna | GPT-5.5 | GPT-5.4 | gpt-oss-120b | GPT-6 Sol | GPT-5.3-Codex | Gemini 4 Argon | Gemini 3.8 Flash | Gemma 4 31B | Gemini 3.1 Pro Preview | Gemini 3.6 Flash | Kimi K3.1 Pro | Kimi K3 | Kimi K2.7 Code | Mistral Large 4 | Mistral Medium 3.5 | Grok 4.7 | Grok 4.6 | Grok 4.5 | MiniMax M3.1 Flash | Mercury 3 | GLM-5.3-Flash | GLM-5.3 | GLM-5.2 | Muse Spark Open | Muse Wonder | Muse Spark 1.3 | Llama 4 Scout | Llama 4 Maverick | Qwen3.8 27B | Qwen3.8 Max | MiMo-V2.6-Pro | MiMo-V2.6-Flash | Ling 3.1 Flash | Step 5 Preview |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Quality and reasoning | 61%25 favorable, 16 not, 40 authors | Only concerns on record0 favorable, 4 not, 4 authors | 73%19 favorable, 7 not, 26 authors | 64%14 favorable, 8 not, 22 authors | 68%17 favorable, 8 not, 25 authors | 54%15 favorable, 13 not, 28 authors | 50%6 favorable, 6 not, 12 authors | 56%9 favorable, 7 not, 16 authors | 68%13 favorable, 6 not, 18 authors | 68%17 favorable, 8 not, 25 authors | 57%12 favorable, 9 not, 21 authors | 67%12 favorable, 6 not, 18 authors | 70%19 favorable, 8 not, 27 authors | 62%13 favorable, 8 not, 20 authors | 58%14 favorable, 10 not, 24 authors | 69%11 favorable, 5 not, 16 authors | 33%3 favorable, 6 not, 8 authors | 55%12 favorable, 10 not, 22 authors | 55%16 favorable, 13 not, 29 authors | 44%12 favorable, 15 not, 26 authors | 33%3 favorable, 6 not, 9 authors | 38%3 favorable, 5 not, 8 authors | Needs 5 accounts from 3 authors3 favorable, 1 not, 4 authors | 33%4 favorable, 8 not, 12 authors | 33%2 favorable, 4 not, 6 authors | 58%22 favorable, 16 not, 38 authors | 31%10 favorable, 22 not, 32 authors | Needs 5 accounts from 3 authors1 favorable, 3 not, 4 authors | 63%22 favorable, 13 not, 35 authors | 56%27 favorable, 21 not, 45 authors | 80%24 favorable, 6 not, 28 authors | 56%20 favorable, 16 not, 36 authors | Needs 5 accounts from 3 authors1 favorable, 3 not, 4 authors | 59%20 favorable, 14 not, 32 authors | Only praise on record3 favorable, 0 not, 3 authors | 50%3 favorable, 3 not, 6 authors | 58%11 favorable, 8 not, 18 authors | 36%5 favorable, 9 not, 14 authors | 43%16 favorable, 21 not, 36 authors | 86%6 favorable, 1 not, 7 authors | 60%3 favorable, 2 not, 5 authors | 62%13 favorable, 8 not, 21 authors | 86%18 favorable, 3 not, 21 authors | 67%14 favorable, 7 not, 21 authors | 76%47 favorable, 15 not, 61 authors | 71%5 favorable, 2 not, 7 authors | Needs 5 accounts from 3 authors2 favorable, 1 not, 3 authors | 20%1 favorable, 4 not, 5 authors | Only praise on record2 favorable, 0 not, 2 authors | 53%8 favorable, 7 not, 15 authors | 44%8 favorable, 10 not, 17 authors | 71%24 favorable, 10 not, 34 authors | 57%4 favorable, 3 not, 7 authors | 22%2 favorable, 7 not, 9 authors | 40%4 favorable, 6 not, 10 authors | Only concerns on record0 favorable, 1 not, 1 author | Needs 5 accounts from 3 authors2 favorable, 1 not, 3 authors |
| Tool use and structured output | 59%10 favorable, 7 not, 17 authors | Only concerns on record0 favorable, 1 not, 1 author | 67%6 favorable, 3 not, 9 authors | 40%4 favorable, 6 not, 10 authors | 46%6 favorable, 7 not, 13 authors | 30%3 favorable, 7 not, 10 authors | Needs 5 accounts from 3 authors3 favorable, 1 not, 4 authors | 70%7 favorable, 3 not, 10 authors | 57%4 favorable, 3 not, 7 authors | 50%4 favorable, 4 not, 8 authors | 50%4 favorable, 4 not, 8 authors | 29%2 favorable, 5 not, 7 authors | 33%4 favorable, 8 not, 12 authors | 70%7 favorable, 3 not, 10 authors | 43%3 favorable, 4 not, 6 authors | 50%3 favorable, 3 not, 6 authors | 40%2 favorable, 3 not, 5 authors | 40%4 favorable, 6 not, 10 authors | 33%3 favorable, 6 not, 9 authors | 62%8 favorable, 5 not, 13 authors | No accounts yet | Only concerns on record0 favorable, 2 not, 2 authors | Only praise on record1 favorable, 0 not, 1 author | Only praise on record1 favorable, 0 not, 1 author | No accounts yet | 27%4 favorable, 11 not, 15 authors | 56%5 favorable, 4 not, 9 authors | No accounts yet | 25%2 favorable, 6 not, 8 authors | 47%7 favorable, 8 not, 15 authors | 67%4 favorable, 2 not, 6 authors | 54%7 favorable, 6 not, 12 authors | Only concerns on record0 favorable, 1 not, 1 author | Needs 5 accounts from 3 authors3 favorable, 1 not, 4 authors | Only concerns on record0 favorable, 1 not, 1 author | No accounts yet | 38%5 favorable, 8 not, 13 authors | Only concerns on record0 favorable, 5 not, 5 authors | 38%6 favorable, 10 not, 16 authors | Only praise on record2 favorable, 0 not, 2 authors | Only concerns on record0 favorable, 1 not, 1 author | 67%4 favorable, 2 not, 6 authors | 80%8 favorable, 2 not, 10 authors | 33%2 favorable, 4 not, 6 authors | 57%4 favorable, 3 not, 7 authors | No accounts yet | No accounts yet | Only concerns on record0 favorable, 1 not, 1 author | Needs 5 accounts from 3 authors1 favorable, 1 not, 2 authors | Needs 5 accounts from 3 authors1 favorable, 2 not, 3 authors | Only concerns on record0 favorable, 4 not, 4 authors | 46%6 favorable, 7 not, 13 authors | Only praise on record1 favorable, 0 not, 1 author | Only concerns on record0 favorable, 5 not, 5 authors | Only concerns on record0 favorable, 1 not, 1 author | Only concerns on record0 favorable, 1 not, 1 author | Only concerns on record0 favorable, 1 not, 1 author |
| Long context | 58%7 favorable, 5 not, 12 authors | No accounts yet | 29%2 favorable, 5 not, 7 authors | 60%3 favorable, 2 not, 5 authors | 80%8 favorable, 2 not, 10 authors | 63%5 favorable, 3 not, 8 authors | 67%4 favorable, 2 not, 6 authors | 50%3 favorable, 3 not, 6 authors | 33%2 favorable, 4 not, 6 authors | 60%6 favorable, 4 not, 10 authors | 50%4 favorable, 4 not, 7 authors | 71%5 favorable, 2 not, 7 authors | 64%7 favorable, 4 not, 11 authors | 40%4 favorable, 6 not, 10 authors | 40%2 favorable, 3 not, 5 authors | 50%4 favorable, 4 not, 8 authors | Only concerns on record0 favorable, 1 not, 1 author | 38%3 favorable, 5 not, 8 authors | 20%1 favorable, 4 not, 5 authors | 27%3 favorable, 8 not, 11 authors | No accounts yet | No accounts yet | Only concerns on record0 favorable, 1 not, 1 author | Only concerns on record0 favorable, 1 not, 1 author | Needs 5 accounts from 3 authors2 favorable, 1 not, 3 authors | 25%2 favorable, 6 not, 8 authors | Only concerns on record0 favorable, 3 not, 3 authors | No accounts yet | 25%2 favorable, 6 not, 8 authors | 38%5 favorable, 8 not, 13 authors | 20%1 favorable, 4 not, 5 authors | 44%7 favorable, 9 not, 16 authors | Only praise on record1 favorable, 0 not, 1 author | Needs 5 accounts from 3 authors3 favorable, 1 not, 4 authors | Only praise on record1 favorable, 0 not, 1 author | Only concerns on record0 favorable, 1 not, 1 author | Needs 5 accounts from 3 authors1 favorable, 3 not, 4 authors | No accounts yet | 42%5 favorable, 7 not, 12 authors | No accounts yet | No accounts yet | 40%2 favorable, 3 not, 5 authors | 60%3 favorable, 2 not, 5 authors | No accounts yet | 40%2 favorable, 3 not, 5 authors | No accounts yet | No accounts yet | Only concerns on record0 favorable, 1 not, 1 author | Only concerns on record0 favorable, 1 not, 1 author | Only concerns on record0 favorable, 3 not, 3 authors | Needs 5 accounts from 3 authors2 favorable, 1 not, 3 authors | 75%6 favorable, 2 not, 8 authors | Only praise on record1 favorable, 0 not, 1 author | Needs 5 accounts from 3 authors1 favorable, 1 not, 2 authors | Needs 5 accounts from 3 authors1 favorable, 1 not, 2 authors | No accounts yet | No accounts yet |
| Developer experience | 35%8 favorable, 15 not, 23 authors | No accounts yet | 25%2 favorable, 6 not, 8 authors | 38%5 favorable, 8 not, 13 authors | 38%6 favorable, 10 not, 16 authors | 50%7 favorable, 7 not, 14 authors | 25%3 favorable, 9 not, 12 authors | 29%2 favorable, 5 not, 7 authors | 25%3 favorable, 9 not, 12 authors | 53%10 favorable, 9 not, 19 authors | 29%4 favorable, 10 not, 14 authors | 57%4 favorable, 3 not, 7 authors | 45%5 favorable, 6 not, 11 authors | 67%8 favorable, 4 not, 12 authors | Needs 5 accounts from 3 authors2 favorable, 2 not, 4 authors | 50%3 favorable, 3 not, 6 authors | Only concerns on record0 favorable, 2 not, 2 authors | 27%3 favorable, 8 not, 11 authors | 25%2 favorable, 6 not, 8 authors | 41%7 favorable, 10 not, 17 authors | No accounts yet | Only concerns on record0 favorable, 1 not, 1 author | No accounts yet | No accounts yet | No accounts yet | 14%1 favorable, 6 not, 7 authors | 25%3 favorable, 9 not, 12 authors | No accounts yet | 33%3 favorable, 6 not, 9 authors | 39%7 favorable, 11 not, 17 authors | Only concerns on record0 favorable, 7 not, 7 authors | 40%8 favorable, 12 not, 20 authors | No accounts yet | 9%1 favorable, 10 not, 11 authors | No accounts yet | Only concerns on record0 favorable, 1 not, 1 author | 13%2 favorable, 14 not, 16 authors | Only concerns on record0 favorable, 9 not, 9 authors | 25%5 favorable, 15 not, 20 authors | No accounts yet | No accounts yet | Only concerns on record0 favorable, 7 not, 7 authors | 11%1 favorable, 8 not, 9 authors | Only concerns on record0 favorable, 3 not, 3 authors | 33%5 favorable, 10 not, 15 authors | No accounts yet | Only concerns on record0 favorable, 1 not, 1 author | Only concerns on record0 favorable, 1 not, 1 author | No accounts yet | Only concerns on record0 favorable, 6 not, 6 authors | Only concerns on record0 favorable, 1 not, 1 author | 17%1 favorable, 5 not, 6 authors | Only concerns on record0 favorable, 1 not, 1 author | Only concerns on record0 favorable, 1 not, 1 author | Only concerns on record0 favorable, 1 not, 1 author | No accounts yet | No accounts yet |
| Cost | 66%25 favorable, 13 not, 37 authors | Only praise on record2 favorable, 0 not, 2 authors | 69%20 favorable, 9 not, 29 authors | 45%10 favorable, 12 not, 22 authors | 56%15 favorable, 12 not, 27 authors | 20%4 favorable, 16 not, 20 authors | 43%3 favorable, 4 not, 7 authors | 39%7 favorable, 11 not, 17 authors | 8%1 favorable, 11 not, 12 authors | 40%6 favorable, 9 not, 14 authors | 50%7 favorable, 7 not, 13 authors | 50%6 favorable, 6 not, 12 authors | 33%7 favorable, 14 not, 20 authors | 53%8 favorable, 7 not, 15 authors | 29%4 favorable, 10 not, 12 authors | 38%3 favorable, 5 not, 8 authors | 80%8 favorable, 2 not, 9 authors | 74%14 favorable, 5 not, 19 authors | 79%22 favorable, 6 not, 26 authors | 29%7 favorable, 17 not, 23 authors | 57%4 favorable, 3 not, 7 authors | Only concerns on record0 favorable, 1 not, 1 author | 50%3 favorable, 3 not, 6 authors | Needs 5 accounts from 3 authors1 favorable, 3 not, 4 authors | 63%5 favorable, 3 not, 8 authors | 60%3 favorable, 2 not, 5 authors | 55%12 favorable, 10 not, 21 authors | Needs 5 accounts from 3 authors2 favorable, 1 not, 3 authors | 35%7 favorable, 13 not, 20 authors | 58%14 favorable, 10 not, 23 authors | Only praise on record7 favorable, 0 not, 7 authors | 50%8 favorable, 8 not, 16 authors | Only concerns on record0 favorable, 1 not, 1 author | 40%10 favorable, 15 not, 25 authors | 71%5 favorable, 2 not, 7 authors | Needs 5 accounts from 3 authors1 favorable, 3 not, 4 authors | 27%3 favorable, 8 not, 11 authors | Only concerns on record0 favorable, 8 not, 8 authors | 19%5 favorable, 21 not, 26 authors | 20%1 favorable, 4 not, 5 authors | Only praise on record4 favorable, 0 not, 4 authors | 80%12 favorable, 3 not, 15 authors | 50%6 favorable, 6 not, 12 authors | 76%16 favorable, 5 not, 21 authors | 35%8 favorable, 15 not, 23 authors | 71%5 favorable, 2 not, 7 authors | Only concerns on record0 favorable, 1 not, 1 author | Only concerns on record0 favorable, 9 not, 9 authors | Needs 5 accounts from 3 authors2 favorable, 1 not, 3 authors | Only praise on record1 favorable, 0 not, 1 author | Only praise on record1 favorable, 0 not, 1 author | Needs 5 accounts from 3 authors2 favorable, 2 not, 4 authors | Only concerns on record0 favorable, 2 not, 2 authors | Needs 5 accounts from 3 authors1 favorable, 1 not, 2 authors | Only praise on record3 favorable, 0 not, 3 authors | Only praise on record1 favorable, 0 not, 1 author | Only praise on record1 favorable, 0 not, 1 author |
| Speed | 68%21 favorable, 10 not, 30 authors | Only concerns on record0 favorable, 1 not, 1 author | 74%14 favorable, 5 not, 19 authors | 88%14 favorable, 2 not, 16 authors | 46%6 favorable, 7 not, 13 authors | 44%4 favorable, 5 not, 9 authors | 60%3 favorable, 2 not, 5 authors | 44%4 favorable, 5 not, 9 authors | 57%4 favorable, 3 not, 7 authors | 31%4 favorable, 9 not, 13 authors | 63%5 favorable, 3 not, 8 authors | 17%1 favorable, 5 not, 6 authors | 36%4 favorable, 7 not, 11 authors | 73%8 favorable, 3 not, 11 authors | 78%7 favorable, 2 not, 9 authors | 75%6 favorable, 2 not, 8 authors | 83%5 favorable, 1 not, 5 authors | 37%7 favorable, 12 not, 19 authors | 45%5 favorable, 6 not, 11 authors | 41%7 favorable, 10 not, 17 authors | Only praise on record1 favorable, 0 not, 1 author | Needs 5 accounts from 3 authors1 favorable, 1 not, 2 authors | 80%4 favorable, 1 not, 5 authors | Needs 5 accounts from 3 authors1 favorable, 1 not, 2 authors | No accounts yet | 85%23 favorable, 4 not, 27 authors | 57%4 favorable, 3 not, 7 authors | Only praise on record1 favorable, 0 not, 1 author | 45%5 favorable, 6 not, 11 authors | 61%19 favorable, 12 not, 31 authors | 53%10 favorable, 9 not, 17 authors | 35%6 favorable, 11 not, 16 authors | Needs 5 accounts from 3 authors2 favorable, 1 not, 3 authors | 21%4 favorable, 15 not, 19 authors | Only concerns on record0 favorable, 2 not, 2 authors | No accounts yet | 21%3 favorable, 11 not, 14 authors | Only concerns on record0 favorable, 2 not, 2 authors | 29%5 favorable, 12 not, 17 authors | Needs 5 accounts from 3 authors1 favorable, 2 not, 3 authors | Only praise on record2 favorable, 0 not, 2 authors | 44%4 favorable, 5 not, 9 authors | 65%13 favorable, 7 not, 20 authors | 33%3 favorable, 6 not, 9 authors | 20%3 favorable, 12 not, 15 authors | Needs 5 accounts from 3 authors1 favorable, 1 not, 2 authors | Only concerns on record0 favorable, 1 not, 1 author | Only concerns on record0 favorable, 1 not, 1 author | Needs 5 accounts from 3 authors1 favorable, 1 not, 2 authors | Needs 5 accounts from 3 authors3 favorable, 1 not, 4 authors | No accounts yet | 33%7 favorable, 14 not, 21 authors | Needs 5 accounts from 3 authors1 favorable, 3 not, 4 authors | Only concerns on record0 favorable, 4 not, 4 authors | Only concerns on record0 favorable, 1 not, 1 author | Only concerns on record0 favorable, 2 not, 2 authors | Only concerns on record0 favorable, 1 not, 1 author |
| Reliability | 42%5 favorable, 7 not, 12 authors | Needs 5 accounts from 3 authors1 favorable, 1 not, 2 authors | 20%1 favorable, 4 not, 5 authors | 18%2 favorable, 9 not, 11 authors | 13%1 favorable, 7 not, 8 authors | 9%1 favorable, 10 not, 11 authors | 13%1 favorable, 7 not, 8 authors | 63%5 favorable, 3 not, 7 authors | 22%2 favorable, 7 not, 9 authors | 17%2 favorable, 10 not, 12 authors | 18%2 favorable, 9 not, 11 authors | 17%1 favorable, 5 not, 6 authors | 20%3 favorable, 12 not, 15 authors | 38%6 favorable, 10 not, 16 authors | 29%2 favorable, 5 not, 7 authors | 40%4 favorable, 6 not, 10 authors | Only concerns on record0 favorable, 1 not, 1 author | 13%1 favorable, 7 not, 8 authors | Only concerns on record0 favorable, 5 not, 5 authors | 14%2 favorable, 12 not, 14 authors | Only concerns on record0 favorable, 4 not, 4 authors | Only concerns on record0 favorable, 1 not, 1 author | No accounts yet | Only concerns on record0 favorable, 2 not, 2 authors | Only concerns on record0 favorable, 4 not, 4 authors | Only concerns on record0 favorable, 4 not, 4 authors | 17%1 favorable, 5 not, 6 authors | Only concerns on record0 favorable, 3 not, 3 authors | 5%1 favorable, 18 not, 19 authors | 15%3 favorable, 17 not, 20 authors | Only concerns on record0 favorable, 5 not, 5 authors | 14%3 favorable, 19 not, 22 authors | Only concerns on record0 favorable, 1 not, 1 author | 8%1 favorable, 12 not, 13 authors | Only concerns on record0 favorable, 1 not, 1 author | Needs 5 accounts from 3 authors1 favorable, 1 not, 2 authors | 38%3 favorable, 5 not, 8 authors | Only concerns on record0 favorable, 4 not, 4 authors | 22%2 favorable, 7 not, 9 authors | Only concerns on record0 favorable, 1 not, 1 author | No accounts yet | 60%3 favorable, 2 not, 5 authors | 33%2 favorable, 4 not, 5 authors | Only concerns on record0 favorable, 7 not, 7 authors | Only concerns on record0 favorable, 4 not, 4 authors | Only concerns on record0 favorable, 1 not, 1 author | No accounts yet | Only concerns on record0 favorable, 2 not, 2 authors | Only concerns on record0 favorable, 1 not, 1 author | Needs 5 accounts from 3 authors1 favorable, 3 not, 4 authors | Only concerns on record0 favorable, 1 not, 1 author | Only concerns on record0 favorable, 9 not, 9 authors | Only concerns on record0 favorable, 1 not, 1 author | Only concerns on record0 favorable, 2 not, 2 authors | No accounts yet | No accounts yet | Only concerns on record0 favorable, 1 not, 1 author |
The 115 accounts behind DeepSeek V4.1 Flash's figures
GILD searched Hacker News, GitHub, Reddit, X, Artificial Analysis, OpenRouter, LMArena, Vals AI and the web for accounts that name DeepSeek V4.1 Flash.
Quality and reasoning 61%
- Favorable
amongst the leading models in intelligence
Artificial Analysis - DeepSeek V4.1 Flash. Artificial Analysis, independent benchmark publisher, self-described, Oct 26, 2026. DeepSeek V4.1 Flash (reasoning).
- Favorable
DeepSeek Flash V4.1 often performs at the level of GPT 5.6 Sol for non-orchestration tasks (programming and maths)
Comment on: I am often wrong. fractorial, Hacker News commenter, self-described, Sep 20, 2026. DeepSeek V4.1 Flash in a self-built Go coding harness.
- Favorable
IME GLM is inferior compared to Deepseek v4.1 Flash
Comment on: Why isn't the industry freaking out about DeepSeek 4.1 Flash?. runtime_terror, Hacker News commenter, self-described, Oct 8, 2026. DeepSeek V4.1 Flash on real work.
- Favorable
the speedy work it does is pretty much always correct
Comment on: MiniMax M3.1 Flash. TheArcane, Hacker News commenter, self-described, Oct 20, 2026. DeepSeek V4.1 Flash through platform.deepseek.com.
- Favorable
Took DeepSeek v4.1 flash around an hour to get a full OpenWRT build-and-flash pipeline up and running
Comment on: Using AI to reverse engineer hardware. cookiengineer, Hacker News commenter, self-described, Oct 16, 2026. DeepSeek V4.1 Flash as a reverse-engineering agent.
- Unfavorable
they're more likely to go down rabbit holes, confidently assert falsehoods, or fix bugs with changes to my test harness rather than my code
Comment on: Why isn't the industry freaking out about DeepSeek 4.1 Flash?. aftbit, Hacker News commenter, self-described, Oct 9, 2026. DeepSeek V4.1 Flash (DS V4.1 Flash) on coding tasks.
- Unfavorable
DeepSeek v4.1 Flash hallucinates like crazy.
Comment on: DeepSeek-v4.1-Flash-1017. pmoriarty, Hacker News commenter, self-described, Oct 17, 2026. DeepSeek V4.1 Flash.
- Unfavorable
it took ~4x longer in a review, found less and planned worse than GPT 6.1 Sol
Comment on: DeepSeek-v4.1-Flash-1017. AmazingTurtle, Hacker News commenter, self-described, Oct 17, 2026. DeepSeek V4.1 Flash via the DeepSeek API reviewing a C++ game engine codebase.
- Favorable
seems about as capable at mid-level tasks
Comment on: DeepSeek V4.1 Flash 1017 (Max). lhl, Hacker News commenter, self-described, Oct 19, 2026. DeepSeek V4.1 Flash and DeepSeek V4.1 Flash 1017 on fast local infrastructure.
- Unfavorable
Absolutely falls apart at things Opus/Sol currently excel at with low reasoning
Comment on: SlopCodeBench 10/2026 – Opus 5.5, Astra wins overall, xhigh considered harmful. ac29, Hacker News commenter, self-described, Oct 21, 2026. DeepSeek V4.1 Flash, the 1017 checkpoint, over a weekend.
- Unfavorable
none of them were capable of making progress on the main project I am working on
Comment on: Anthropic S-1. ac29, Hacker News commenter, self-described, Oct 26, 2026. DeepSeek V4.1 Flash, the 1017 checkpoint, on a main project.
- Unfavorable
DeepSeek 4.1 flash fails at lower thinking levels
Comment on: DeepSeek-v4.1-Flash-1017. a11r, Hacker News commenter, self-described, Oct 17, 2026. DeepSeek V4.1 Flash (original 4.1 flash) on moderately difficult coding tasks.
- Favorable
With, in my experience, practically the same results.
Comment on: DeepInfer: High-performance inference framework for DeepSeek models. inciampati, Hacker News commenter, self-described, Oct 20, 2026. DeepSeek V4.1 Flash.
- Favorable
it reaches about 98% of the quality score
Abhinav Amrute on DeepSeek V4.1 Flash. Abhinav Amrute (@AbhinavAmrute), builder of Blitsum, X user, self-described, Oct 25, 2026. DeepSeek V4.1 Flash.
- Unfavorable
It needs someone to hold its hand and verify every change it makes and how it affects other parts of the software.
BURKOV on DeepSeek 4.1 Flash. BURKOV (@burkov), PhD in AI and author of The Hundred-Page LMs Book per his X bio, self-described, Sep 17, 2026. DeepSeek V4.1 Flash (DeepSeek 4.1 Flash) on a software task.
- Unfavorable
The first V4.1 Flash was worse even than V4 Pro in real coding tasks and MILES behind Opus 5.5.
Luke (DevMindscape) on the first V4.1 Flash. Luke (@lk_devmindscape), builder of the Gritcode coding agent, X user, self-described, Oct 25, 2026. DeepSeek V4.1 Flash, the original release, on real coding tasks.
- Favorable
it fixed first serious bugs which the previous version failed gloriously
Constantin Diez on DeepSeek V4.1 Flash 1017 on DGX Spark. Constantin Diez (@ConstantinDiez), X user, self-described, Oct 25, 2026. DeepSeek V4.1 Flash and the 1017 update on 2x DGX Spark.
- Favorable
it now feels clearly ahead of GLM 5.3 Flash for me on normal coding work
Yum on DeepSeek V4.1 Flash 1017 in OpenCode. Yum (@yuhasbeentaken), growth engineer who benchmarks AI agents, X user, self-described, Oct 19, 2026. DeepSeek V4.1 Flash, the 1017 checkpoint, in OpenCode Go.
- Favorable
4.1 Flash is smart enough
jarnMod on DeepSeek 4.1 Flash. jarnMod (@jarnMod), developer and fund operator per X bio, self-described, Oct 22, 2026. DeepSeek V4.1 Flash for agentic work.
- Unfavorable
Coding tasks are lousy.
Hacker News comment by harlequinetcie on DeepSeek Flash v4.1. harlequinetcie, Hacker News commenter, self-described, Oct 19, 2026. DeepSeek V4.1 Flash (DeepSeek Flash v4.1) in a custom agent architecture.
- Unfavorable
its a big mistake to have a flash model implement without a strong model reviewing
Comment on: Prompting Claude Opus 5.5. gregwebs, Hacker News commenter, self-described, Sep 28, 2026. DeepSeek V4.1 Flash (Deepseek Flash v4.1) implementing Opus plans.
- Favorable
Flash 4.1 1017 is also a very good model IMO
Comment on: Kimi K3.1 Pro and K3.1 Pro Highspeed. ZiLxxi, Hacker News commenter, self-described, Oct 24, 2026. DeepSeek V4.1 Flash, the 1017 checkpoint, through DeepSeek API credits.
- Unfavorable
there was an unnacceptable quality loss
Comment on: Why isn't the industry freaking out about DeepSeek 4.1 Flash?. p1necone, Hacker News commenter, self-described, Oct 8, 2026. DeepSeek V4.1 Flash (Deepseek-V4.1-Flash) as orchestrator and implementer on a compiler project.
- Favorable
this is a really strong model
Comment on: DeepSeek v4.1 Flash. LaurensBER, Hacker News commenter, self-described, Sep 10, 2026. DeepSeek V4.1 Flash at launch.
- Favorable
got a high scoring result
Comment on: DeepSeek v4.1 Flash. raesene9, Hacker News commenter, self-described, Sep 10, 2026. DeepSeek V4.1 Flash on a personal Kubernetes security benchmark.
- Unfavorable
Deepseek v4.1 flash is able to solve it some of the time
Comment on: DeepSeek v4.1 Flash. pampas, Hacker News commenter, self-described, Sep 10, 2026. DeepSeek V4.1 Flash on the Redactle puzzle LLM leaderboard.
- Unfavorable
This is definitely not on par with GPT-6 astra. Not with GPT-5.6 sol either.
Comment on: DeepSeek v4.1 Flash. WiSaGaN, Hacker News commenter, self-described, Sep 10, 2026. DeepSeek V4.1 Flash at launch.
- Favorable
It's also really solid and comparable in real world use to a sonnet for my work.
Comment on: DeepSeek v4.1 Flash. gigatexal, Hacker News commenter, self-described, Sep 10, 2026. DeepSeek V4.1 Flash at work.
- Favorable
DeepSeek V4.1 Flash 1017 (Max) is amongst the leading models in intelligence
Artificial Analysis - DeepSeek V4.1 Flash 1017. Artificial Analysis, independent benchmark publisher, self-described, Oct 26, 2026. DeepSeek V4.1 Flash, the 1017 checkpoint (Max).
- Favorable
if I don't look at the model name, I honestly could not tell you if I'm using DeepSeek or Opus
Why Isn't The Industry Freaking Out About DeepSeek 4.1 Flash?. Jono, author of the Jono's Corner blog, self-described, Oct 7, 2026. DeepSeek V4.1 Flash (DeepSeek 4.1 Flash) on an OpenCode Go plan across a dozen projects.
- Favorable
Below is the Pareto of performance vs price on DeepSWE, a favorite agentic software engineering benchmark today, which DeepSeek dominates.
Latest open artifacts (#25): DeepSeek v4.1 Flash 1017, American-made models. Florian Brand, researcher at Prime Intellect, writing for Interconnects, self-described, Oct 20, 2026. DeepSeek V4.1 Flash, the 1017 checkpoint (DeepSeek-V4.1-Flash-1017).
- Favorable
This model is very, very good. It is a really good executor.
Yume_X on DeepSeek V4.1 Flash on two DGX Sparks. Yume_X (@yume_arasaki), X user running local AI on DGX Sparks, self-described, Sep 14, 2026. DeepSeek V4.1 Flash, EXL3 build on two DGX Sparks, thinking off.
- Favorable
DeepSeek V4.1 Flash is the new #1 open-weight model on the Vals Index.
Vals AI on DeepSeek V4.1 Flash. Vals AI, public LLM evaluation publisher, self-described, Sep 10, 2026. DeepSeek V4.1 Flash on the Vals Index, high reasoning effort.
- Favorable
For a model very very small compared to Kimi-K3.1-pro, the difference is huge.
AJ on Kimi-K3.1-Pro vs DeepSeek-v4.1-Flash-1017. AJ (@ItsmeAjayKV), independent AI researcher, X user, self-described, Oct 24, 2026. DeepSeek V4.1 Flash, the 1017 checkpoint, on a 3D generation task without a harness.
- Favorable
it earned full marks on my scoring keys and cost less with the settings I used
DeepSeek V4.1-Flash-1017 vs. Claude Haiku 5.5: More accurate at a fraction of the price. Jessica Wachtel, writer at The New Stack, self-described, Oct 22, 2026. DeepSeek V4.1 Flash, the 1017 checkpoint, via OpenRouter pinned to DeepSeek's servers, default settings, off-peak.
- Favorable
DeepSeek V4.1 Flash 1017 codes about as well as Claude Sonnet 5.5 and Haiku 5.5 at their default settings, for a fraction of the price.
DeepSeek vs Claude for coding: V4.1 Flash 1017 against Opus 5.5, Sonnet 5.5 and Haiku 5.5. Bito, AI coding tools company, on its own coding benchmark, self-described, Oct 19, 2026. DeepSeek V4.1 Flash, the 1017 checkpoint, inside Claude Code.
- Unfavorable
with almost 2x more parameters than V4 Flash, I've expected a bit more
Tested on coding and agentic work - not that impressive. curiousily, Hugging Face user, self-described, Sep 11, 2026. DeepSeek V4.1 Flash via OpenRouter on coding and agentic tests.
- Favorable
This can actually build a working app from a spec - something I was not expecting to see from a model in this cost range.
Praise and critique for this model. mindplay, Hugging Face user, self-described, Sep 20, 2026. DeepSeek V4.1 Flash (DeepSeek 4.1 Flash) building an Android app from a spec.
- Unfavorable
You can really see a drastic drop in intelligence
Dumb model... total degradation! Even a 9B model is more coherent than this.. RomanHammer, Hugging Face user, self-described, Oct 13, 2026. DeepSeek V4.1 Flash.
- Favorable
it has proven much better than glm 5.3 so far
wow, this thing is a beast - and i've NEVER said that about a deepseek model. aaron-newsome, Hugging Face user running the model locally, self-described, Oct 20, 2026. DeepSeek V4.1 Flash, the 1017 checkpoint, on 4x RTX PRO 6000 across dozens of tickets.
- Unfavorable
Opus is enough smarter than DSF that it's worth the extra steps
Comment on: Why isn't the industry freaking out about DeepSeek 4.1 Flash?. Jonathan Ellis (jbellis), SlopCop founder and CEO, DataStax co-founder and former CTO, Oct 8, 2026. DeepSeek V4.1 Flash (DeepSeek Flash, DSF) as subagents managed by Opus in mjolnir.
- Favorable
I had DS working on the same project as Sol and DS was correcting Sol's work routinely.
Comment on: DeepSeek-v4.1-Flash-1017. cromka, Hacker News commenter, self-described, Oct 20, 2026. DeepSeek V4.1 Flash (Deepseek 4.1) on a shared project with GPT Sol.
- Favorable
The end result is much better with improved choreography, visual effects and overall feel.
Daniel Zambrini on Deepseek V4.1 Flash 1017 vs the earlier checkpoint. Daniel Zambrini (@DanielZambrini), X user, self-described, Oct 19, 2026. DeepSeek V4.1 Flash, the 1017 checkpoint, against the earlier V4.1 Flash checkpoint on an animation task.
- Favorable
Its best result is #1 of 35 on SkillsBench
DeepSeek V4.1 Flash Benchmarks, Cost and Capabilities | Vals AI. Vals AI, public LLM evaluation publisher, self-described, Sep 10, 2026. DeepSeek V4.1 Flash at max reasoning effort via the DeepSeek provider.
- Favorable
even at IQ1_S the model nailed most of my regular benchmarks
Ran DeepSeek V4.1 Flash 1017 on a single RTX 5090. jesdga95, r/LocalLLaMA poster developing the Basalt inference engine, self-described, Oct 21, 2026. DeepSeek V4.1 Flash, the 1017 checkpoint (Unsloth UD-IQ1_S), on an RTX 5090 plus RTX 5060 Ti.
Tool use and structured output 59%
- Favorable
I've ran Chief/Builder/Reviewer swarms autonomously for multiple days
Comment on: DeepSeek-v4.1-Flash-1017. ilitirit, Hacker News commenter, self-described, Oct 17, 2026. DeepSeek V4.1 Flash in multi-day agent swarm experiments.
- Unfavorable
even has basic problems with failing tool calls
Comment on: SlopCodeBench 10/2026 – Opus 5.5, Astra wins overall, xhigh considered harmful. ac29, Hacker News commenter, self-described, Oct 21, 2026. DeepSeek V4.1 Flash, the 1017 checkpoint, over a weekend.
- Favorable
the list price didn't really change, but the model loops less
Yum on more DeepSeek V4.1 Flash 1017 findings. Yum (@yuhasbeentaken), growth engineer who benchmarks AI agents, X user, self-described, Oct 19, 2026. DeepSeek V4.1 Flash, the 1017 checkpoint, in OpenCode free and Go.
- Favorable
Good enough for agentic work
jarnMod on DeepSeek 4.1 Flash. jarnMod (@jarnMod), developer and fund operator per X bio, self-described, Oct 22, 2026. DeepSeek V4.1 Flash for agentic work.
- Unfavorable
It is failing frequently and writing it's own tool calling format instead.
Comment on: DeepSeek v4.1 Flash. irthomasthomas, Hacker News commenter, self-described, Sep 10, 2026. DeepSeek V4.1 Flash through the DeepSeek API at launch.
- Favorable
It can now debug pages by clicking browser itself
Comment on: DeepSeek v4.1 Flash. BrucecarlL, Hacker News commenter, self-described, Sep 10, 2026. DeepSeek V4.1 Flash debugging pages through the browser.
- Unfavorable
i got error about tools calling on opencode desktop when it use frank/DeepSeek-V4.1-Flash
deepseek v4.1 flash bug tools calling. pichead, GitHub user filing an OpenCode issue, self-described, Sep 24, 2026. DeepSeek V4.1 Flash on the OpenCode Go plan in OpenCode Desktop.
- Unfavorable
Deepseek 4.1 flash is stopping constantly mid tasks with different DSML errors
deepseek 4.1 flash. darereda, GitHub user filing an OpenCode issue, self-described, Oct 1, 2026. DeepSeek V4.1 Flash (Deepseek 4.1 flash) in OpenCode.
- Unfavorable
raw internal tool-call delimiters repeatedly leak into the visible conversation instead of being correctly parsed
[P1] Fireworks DeepSeek V4.1 Flash 1017 leaks raw tool-call tokens and prematurely terminates agent turns. carterlasalle, GitHub user filing an oh-my-pi issue, self-described, Oct 18, 2026. DeepSeek V4.1 Flash, the 1017 checkpoint, via Fireworks AI in oh-my-pi v18.12.2.
- Favorable
We run all our Personal Assistants now on flash (thinking high) by default and it works incredibly well.
Comment on: Why isn't the industry freaking out about DeepSeek 4.1 Flash?. lmf4lol, Hacker News commenter, self-described, Oct 8, 2026. DeepSeek V4.1 Flash (v4.1-flash, thinking high) running personal assistants.
- Favorable
Luna is very slow and bad at agentic tasks. DS runs circles around it
Comment on: Why isn't the industry freaking out about DeepSeek 4.1 Flash?. pimeys, Hacker News commenter, self-described, Oct 8, 2026. DeepSeek V4.1 Flash (DS) on agentic tasks against Luna.
- Favorable
Tools: clean at every depth, real tool calls, zero XML leakage
Yume_X on DeepSeek V4.1 Flash on two DGX Sparks. Yume_X (@yume_arasaki), X user running local AI on DGX Sparks, self-described, Sep 14, 2026. DeepSeek V4.1 Flash, EXL3 build on two DGX Sparks, thinking off.
- Favorable
DeepSeek started strong, beating Haiku's accuracy on the first test. DeepSeek scored 6 of 6.
DeepSeek V4.1-Flash-1017 vs. Claude Haiku 5.5: More accurate at a fraction of the price. Jessica Wachtel, writer at The New Stack, self-described, Oct 22, 2026. DeepSeek V4.1 Flash, the 1017 checkpoint, via OpenRouter pinned to DeepSeek's servers, default settings, off-peak.
- Favorable
It ran the same long multi-turn sessions, tool calls and file edits as the Claude models
DeepSeek vs Claude for coding: V4.1 Flash 1017 against Opus 5.5, Sonnet 5.5 and Haiku 5.5. Bito, AI coding tools company, on its own coding benchmark, self-described, Oct 19, 2026. DeepSeek V4.1 Flash, the 1017 checkpoint, inside Claude Code.
- Unfavorable
It repeatedly announces that it will emit an answer or tool call, but produces neither.
V4.1-Flash native reasoning loops: prompt/history contract and model-team triage request. Hui-cd, GitHub user running the open weights on four DGX Sparks, self-described, Oct 8, 2026. DeepSeek V4.1 Flash open weights on vLLM across four DGX Spark nodes.
- Unfavorable
as raw internal markup in `message.content`, instead of either the structured `tool_calls` field or a plain refusal.
[BUG] deepseek-flash emits internal DSML tool-call markup in content when tools array is omitted but history carries tool_calls. monperrus, GitHub user filing a DeepSeek issue, self-described, Sep 26, 2026. DeepSeek V4.1 Flash through the DeepSeek API model name deepseek-flash.
- Favorable
Also works: tool calls, images, up to 1M context
Ran DeepSeek V4.1 Flash 1017 on a single RTX 5090. jesdga95, r/LocalLLaMA poster developing the Basalt inference engine, self-described, Oct 21, 2026. DeepSeek V4.1 Flash, the 1017 checkpoint (Unsloth UD-IQ1_S), on an RTX 5090 plus RTX 5060 Ti.
Long context 58%
- Unfavorable
DeepSeek v4.1 flash seems to do this thing where it starts saying that we should wrap up the current work
Comment on: The State of Context Engineering. kadoban, Hacker News commenter, self-described, Oct 25, 2026. DeepSeek V4.1 Flash in long coding sessions.
- Favorable
solves a lot of problems that other models still have
Comment on: LittleJS is 2D and 3D now. cookiengineer, Hacker News commenter, self-described, Oct 15, 2026. DeepSeek V4.1 Flash (FP4).
- Favorable
Needle passed at 100% depth
Mia on DeepSeek V4.1 Flash 1017 across 4x DGX Spark. Mia (@MiaAI_lab), runs open models locally, X user, self-described, Oct 25, 2026. DeepSeek V4.1 Flash, the 1017 checkpoint with official weights, on four DGX Sparks via TensorFold.
- Unfavorable
i'm seeing compression kick in around 300K context instead of being able to stretch it close to 1M
Yum on DeepSeek V4.1 Flash 1017 in OpenCode. Yum (@yuhasbeentaken), growth engineer who benchmarks AI agents, X user, self-described, Oct 19, 2026. DeepSeek V4.1 Flash, the 1017 checkpoint, in OpenCode Go.
- Unfavorable
not taking all the relevant context into account when making decisions
Comment on: Why isn't the industry freaking out about DeepSeek 4.1 Flash?. p1necone, Hacker News commenter, self-described, Oct 8, 2026. DeepSeek V4.1 Flash (Deepseek-V4.1-Flash) as orchestrator and implementer on a compiler project.
- Favorable
that is already a weeklong project where I share the same context
Comment on: DeepSeek-v4.1-Flash-1017. pimeys, Hacker News commenter, self-described, Oct 18, 2026. DeepSeek V4.1 Flash through Coralbricks in the omp harness.
- Unfavorable
The wait gets worse as more images accumulate in context.
deepseek-v4.1-flash: 10-60 s to first token once images are in context. slovx2, GitHub user filing a Command Code issue, self-described, Oct 10, 2026. DeepSeek V4.1 Flash (deepseek/deepseek-v4.1-flash) in the Command Code CLI.
- Favorable
Needle retrieval: 12/12 across the ladder, out to 548,000 prompt tokens
Yume_X on DeepSeek V4.1 Flash on two DGX Sparks. Yume_X (@yume_arasaki), X user running local AI on DGX Sparks, self-described, Sep 14, 2026. DeepSeek V4.1 Flash, EXL3 build on two DGX Sparks, thinking off.
- Favorable
DeepSeek got all 1,600 fields right.
DeepSeek V4.1-Flash-1017 vs. Claude Haiku 5.5: More accurate at a fraction of the price. Jessica Wachtel, writer at The New Stack, self-described, Oct 22, 2026. DeepSeek V4.1 Flash, the 1017 checkpoint, via OpenRouter pinned to DeepSeek's servers, default settings, off-peak.
- Unfavorable
it runs out of context, detects that but **does not compact** automatically
claude code auto compress fails with "deepseek-v4.1-flash:1017-cloud". fce2, GitHub user filing an Ollama issue, self-described, Oct 23, 2026. DeepSeek V4.1 Flash, the 1017 checkpoint (deepseek-v4.1-flash:1017-cloud), via Ollama in Claude Code.
- Favorable
Both runs scored 36/36 on the exam.
DeepSeek V4.1 Flash manages agent memory 10× less efficiently than V4 Flash (Hermes, MarathonMemBench). ovsale, Hugging Face user and author of MarathonMemBench, self-described, Sep 14, 2026. DeepSeek V4.1 Flash in Hermes on the MarathonMemBench long-conversation memory benchmark.
- Favorable
up to 1M context (a 1M prompt takes ~26 min, ouch)
Ran DeepSeek V4.1 Flash 1017 on a single RTX 5090. jesdga95, r/LocalLLaMA poster developing the Basalt inference engine, self-described, Oct 21, 2026. DeepSeek V4.1 Flash, the 1017 checkpoint (Unsloth UD-IQ1_S), on an RTX 5090 plus RTX 5060 Ti.
Developer experience 35%
- Unfavorable
It's also notably fast, however very verbose.
Artificial Analysis - DeepSeek V4.1 Flash. Artificial Analysis, independent benchmark publisher, self-described, Oct 26, 2026. DeepSeek V4.1 Flash (reasoning).
- Unfavorable
they have been overthinkers
Comment on: DeepSeek-v4.1-Flash-1017. a11r, Hacker News commenter, self-described, Oct 17, 2026. DeepSeek V4.1 Flash (original 4.1 flash) on moderately difficult coding tasks.
- Favorable
Works well with Copilot
Comment on: DeepSeek-v4.1-Flash-1017. summarity, Hacker News commenter, self-described, Oct 17, 2026. DeepSeek V4.1 Flash, the 1017 checkpoint, through OpenRouter in GitHub Copilot CLI.
- Unfavorable
others like to give q4 or even q2 instead of full or q8 quantisation.
lordstorm on DeepSeek v4.1 flash 1017 providers. lordstorm (@lordsturm), X user, self-described, Oct 25, 2026. DeepSeek V4.1 Flash, the 1017 checkpoint, across API providers.
- Favorable
switched to deepseek-v4.1-flash from within opencode and a minute later had my confirmation, along with a really nice explanation
Comment on: Wanted to download an ISO, ended up writing a kernel exploit. wereHamster, Hacker News commenter, self-described, Oct 15, 2026. DeepSeek V4.1 Flash (deepseek-v4.1-flash) inside opencode.
- Unfavorable
it can just be /really/ annoying in some roles and to chat with some of the time
Comment on: MiniMax M3.1 Flash. bitexploder, Hacker News commenter, self-described, Oct 19, 2026. DeepSeek V4.1 Flash (DeepSeek Flash 4.1).
- Unfavorable
Vanilla pi harness fails.
Hacker News comment by harlequinetcie on DeepSeek Flash v4.1. harlequinetcie, Hacker News commenter, self-described, Oct 19, 2026. DeepSeek V4.1 Flash (DeepSeek Flash v4.1) in a custom agent architecture.
- Favorable
it plays incredibly well with deepseek flash 4.1
Comment on: GPT 6.1 Sol: Near-Astra intelligence for a fifth of the price. taylorfinley, Hacker News commenter, self-described, Sep 29, 2026. DeepSeek V4.1 Flash (deepseek flash 4.1) in the Oh My Pi harness.
- Unfavorable
being way too wordy and rambly in documentation despite prompting to avoid it
Comment on: Why isn't the industry freaking out about DeepSeek 4.1 Flash?. p1necone, Hacker News commenter, self-described, Oct 8, 2026. DeepSeek V4.1 Flash (Deepseek-V4.1-Flash) as orchestrator and implementer on a compiler project.
- Unfavorable
you will not believe this is the same model. Because it isn't.
Comment on: One Month Without AI. elwebmaster, Hacker News commenter, self-described, Sep 26, 2026. DeepSeek V4.1 Flash (deepseek-4.1 flash) on OpenRouter, Qwen Cloud and the DeepSeek API.
- Favorable
It also seems to be more willing to just do whatever you ask of it.
Comment on: DeepSeek v4.1 Flash. LaurensBER, Hacker News commenter, self-described, Sep 10, 2026. DeepSeek V4.1 Flash at launch.
- Unfavorable
the reasoning token counts suggest to me that it doesn't actually support seven different levels
Comment on: DeepSeek v4.1 Flash. simonw, Hacker News commenter, self-described, Sep 10, 2026. DeepSeek V4.1 Flash on OpenRouter at seven reasoning levels.
- Favorable
Works correctly in opencode, but seems like they inject a system prompt
Comment on: DeepSeek v4.1 Flash. Mashimo, Hacker News commenter, self-described, Sep 10, 2026. DeepSeek V4.1 Flash in opencode (opencode-go/deepseek-flash).
- Unfavorable
the model responds with very long texts and enters an infinite loop
DeepSeek V4.1 Flash Free model responds with long text and enters infinite loop. AFOQ-M, GitHub user filing an OpenCode issue, self-described, Oct 23, 2026. DeepSeek V4.1 Flash Free in the OpenCode application.
- Unfavorable
it generated 210M tokens, which is very verbose in comparison to the median of 140M
Artificial Analysis - DeepSeek V4.1 Flash 1017. Artificial Analysis, independent benchmark publisher, self-described, Oct 26, 2026. DeepSeek V4.1 Flash, the 1017 checkpoint (Max).
- Unfavorable
DeepSeek is horrible at grilling sessions
Comment on: Why isn't the industry freaking out about DeepSeek 4.1 Flash?. gregwebs, Hacker News commenter, self-described, Oct 8, 2026. DeepSeek V4.1 Flash (DeepSeek 4.1 flash) as coding orchestrator and verifier.
- Favorable
with no setup beyond pointing Claude Code at the model
DeepSeek vs Claude for coding: V4.1 Flash 1017 against Opus 5.5, Sonnet 5.5 and Haiku 5.5. Bito, AI coding tools company, on its own coding benchmark, self-described, Oct 19, 2026. DeepSeek V4.1 Flash, the 1017 checkpoint, inside Claude Code.
- Unfavorable
but the model's chat template does not, so the request returns HTTP 400
[Bug]: vLLM + DeepSeek V4.1 chat template rejects reasoning_effort "medium"/"minimal". lbaauw, GitHub user filing a Hermes Agent issue, self-described, Oct 22, 2026. DeepSeek V4.1 Flash, the 1017 checkpoint, on a local vLLM server via Hermes Agent.
- Unfavorable
V4.1-Flash: 33–50 agent turns for a one-field config edit
V4.1-Flash: 33–50 agent turns for a one-field config edit (verification with no stopping criterion). jiokasd3323, Hugging Face user, self-described, Sep 11, 2026. DeepSeek V4.1 Flash in the open-source deepseek-harness agent.
- Unfavorable
Twelve times more memory for the same conversation, and the extra is not facts.
DeepSeek V4.1 Flash manages agent memory 10× less efficiently than V4 Flash (Hermes, MarathonMemBench). ovsale, Hugging Face user and author of MarathonMemBench, self-described, Sep 14, 2026. DeepSeek V4.1 Flash in Hermes on the MarathonMemBench long-conversation memory benchmark.
- Unfavorable
find it often gets caught up in long thinking runs
Comment on: MiniMax M3.1 Flash. seabombs, Hacker News commenter, self-described, Oct 20, 2026. DeepSeek V4.1 Flash (DS-4.1-Flash) and the 1017 update.
- Favorable
set it to high and life improved immediately
Comment on: Catch a Bird – I made it for my own sanity. appstorelottery, Hacker News commenter, self-described, Oct 15, 2026. DeepSeek V4.1 Flash (DeepSeek Flash 4.1) reasoning setting.
- Favorable
once I have a plan, I usually delegate to deepseek flash. its quick and doesn't stray
Comment on: SlopCodeBench 10/2026 – Opus 5.5, Astra wins overall, xhigh considered harmful. cultofmetatron, Hacker News commenter, self-described, Oct 21, 2026. DeepSeek V4.1 Flash (deepseek flash) implementing Astra plans.
- Unfavorable
DeepSeek V4.1 Flash may be chatty
Comment on: Sonnet 5.5. jchw, Hacker News commenter, self-described, Sep 28, 2026. DeepSeek V4.1 Flash.
- Unfavorable
Mainline and ik_llama.cpp can't load this model yet.
DeepSeek-V4.1-Flash (UD-Q4_K_XL) on 4x 3090 + EPYC: 12 → 25 tok/s prose, 39 tok/s code.. C0smo777, r/LocalLLaMA poster, self-described, Oct 20, 2026. DeepSeek V4.1 Flash, the 1017 checkpoint (Unsloth UD-Q4_K_XL), in llama.cpp on 4x RTX 3090 and EPYC.
Cost 66%
- Favorable
reasonably priced when comparing to other open weight models of similar size
Artificial Analysis - DeepSeek V4.1 Flash. Artificial Analysis, independent benchmark publisher, self-described, Oct 26, 2026. DeepSeek V4.1 Flash (reasoning).
- Favorable
DS 4.1's speed and price more than make up for the "intelligence" gap
Comment on: DeepSeek-v4.1-Flash-1017. ilitirit, Hacker News commenter, self-described, Oct 17, 2026. DeepSeek V4.1 Flash in multi-day agent swarm experiments.
- Favorable
all that cost me 0.86$
Comment on: Using AI to reverse engineer hardware. cookiengineer, Hacker News commenter, self-described, Oct 16, 2026. DeepSeek V4.1 Flash as a reverse-engineering agent.
- Unfavorable
Deepseek v4.1 Flash is far from the pareto line. You can get the same performance for half the cost from Luna or Haiku 5.5 now
Comment on: Why isn't the industry freaking out about DeepSeek 4.1 Flash?. criley2, Hacker News commenter, self-described, Oct 9, 2026. DeepSeek V4.1 Flash against Luna, Haiku 5.5 and Sol 6.1.
- Unfavorable
spends a huge amount of tokens (an order of magnitude more) at the highest thinking levels
Comment on: DeepSeek-v4.1-Flash-1017. a11r, Hacker News commenter, self-described, Oct 17, 2026. DeepSeek V4.1 Flash (original 4.1 flash) on moderately difficult coding tasks.
- Unfavorable
Somehow GPT 6.1 Sol (medium) is cheaper per task ($0.21 vs $0.26)
Comment on: DeepSeek V4.1 Flash 1017 (Max). Tiberium, Hacker News commenter, self-described, Oct 19, 2026. DeepSeek V4.1 Flash, the 1017 checkpoint at max effort, on Artificial Analysis.
- Favorable
Deepseek v4.1 flash goes a LONG way for $20.
Comment on: Why isn't the industry freaking out about DeepSeek 4.1 Flash?. computerex, Hacker News commenter, self-described, Oct 9, 2026. DeepSeek V4.1 Flash.
- Favorable
I rip about 200 million tokens at least a day and spend maybe $3 with deepseek flash v4.1
Comment on: Why isn't the industry freaking out about DeepSeek 4.1 Flash?. Primer81, Hacker News commenter, self-described, Oct 9, 2026. DeepSeek V4.1 Flash as a daily coding driver.
- Favorable
it's still cheap and mostly good enough
Comment on: GPT-6 Sol and Luna. flippingheck, Hacker News commenter, self-described, Sep 23, 2026. DeepSeek V4.1 Flash (DeepSeek 4.1 Flash).
- Favorable
98% of the quality at 1/50 of the price
Abhinav Amrute on DeepSeek V4.1 Flash. Abhinav Amrute (@AbhinavAmrute), builder of Blitsum, X user, self-described, Oct 25, 2026. DeepSeek V4.1 Flash.
- Favorable
it easily hit 99%+ cache hit rate
Yifeng Chen on deepseek v4.1 flash cache hits. Yifeng Chen (@__fantasyman), content creator, X user, self-described, Oct 25, 2026. DeepSeek V4.1 Flash via Command Code in the Pi harness.
- Favorable
the value on OpenCode Go is kind of absurd
Yum on DeepSeek V4.1 Flash 1017 in OpenCode. Yum (@yuhasbeentaken), growth engineer who benchmarks AI agents, X user, self-described, Oct 19, 2026. DeepSeek V4.1 Flash, the 1017 checkpoint, in OpenCode Go.
- Favorable
DeepSeek Flash v4.1 is now 22x cheaper
Hacker News comment by harlequinetcie on DeepSeek Flash v4.1. harlequinetcie, Hacker News commenter, self-described, Oct 19, 2026. DeepSeek V4.1 Flash (DeepSeek Flash v4.1) in a custom agent architecture.
- Unfavorable
Deepseek v4.1 is actually the more expensive model to use
Comment on: Prompting Claude Opus 5.5. criley2, Hacker News commenter, self-described, Sep 28, 2026. DeepSeek V4.1 Flash (Deepseek Flash v4.1) implementing with Opus 5.5 reviewing.
- Favorable
The cost is 20-40x less for Deepseek Flash v4.1
Comment on: Prompting Claude Opus 5.5. gregwebs, Hacker News commenter, self-described, Sep 28, 2026. DeepSeek V4.1 Flash (Deepseek Flash v4.1) implementing Opus plans.
- Unfavorable
Luna still outperformed DeepSeek Flash 4.1 in cost per task on Artificial Analysis
Comment on: MiMo v2.6. user43928, Hacker News commenter, self-described, Sep 21, 2026. DeepSeek V4.1 Flash (DeepSeek Flash 4.1) on Artificial Analysis cost per task.
- Unfavorable
So for output-heavy workloads and long reasoning, DS costs more than GLM.
Comment on: MiniMax M3.1 Flash. 0xbadcafebee, Hacker News commenter, self-described, Oct 19, 2026. DeepSeek V4.1 Flash (DS 4.1 Flash) on OpenRouter pricing.
- Favorable
am usually around $1 usage for the day
Comment on: Kimi K3.1 Pro and K3.1 Pro Highspeed. ZiLxxi, Hacker News commenter, self-described, Oct 24, 2026. DeepSeek V4.1 Flash, the 1017 checkpoint, through DeepSeek API credits.
- Favorable
a $200 subscription wasn't enough to get through 20-30 tasks while $30 of DeepSeek was
Comment on: Claude Opus 5.5. knapcio, Hacker News commenter, self-described, Sep 23, 2026. DeepSeek V4.1 Flash (DS4.1) as the main work model.
- Favorable
This cache it improvement makes the model x2-x2.5 more efficient on a long horizon tasks in terms of cost.
Comment on: DeepSeek v4.1 Flash. k9294, Hacker News commenter, self-described, Sep 10, 2026. DeepSeek V4.1 Flash priced on a real 447-turn coding task.
- Favorable
finding it very difficult to spend more than $75 in a month
Comment on: Why isn't the industry freaking out about DeepSeek 4.1 Flash?. lifeisloving, Hacker News commenter, self-described, Oct 8, 2026. DeepSeek V4.1 Flash (deepseek v4.1) with heavy tool and MCP use.
- Unfavorable
it burns through more reasoning tokens than any other model
Comment on: DeepSeek v4.1 Flash. pampas, Hacker News commenter, self-described, Sep 10, 2026. DeepSeek V4.1 Flash on the Redactle puzzle LLM leaderboard.
- Unfavorable
Official Deepseek v4.1 Flash API costs are more than GPT 5.6 Luna.
Comment on: DeepSeek v4.1 Flash. gkbrk, Hacker News commenter, self-described, Sep 10, 2026. DeepSeek V4.1 Flash official API pricing.
- Favorable
probably will set as a new baseline for modern API based LLM because it's so cheap
Comment on: DeepSeek v4.1 Flash. WiSaGaN, Hacker News commenter, self-described, Sep 10, 2026. DeepSeek V4.1 Flash at launch.
- Unfavorable
considerably (3x) more expensive
Comment on: DeepSeek v4.1 Flash. XCSme, Hacker News commenter, self-described, Sep 10, 2026. DeepSeek V4.1 Flash on the aibenchy comparison.
- Favorable
My tasks rarely go over a dollar
Comment on: DeepSeek-v4.1-Flash-1017. pimeys, Hacker News commenter, self-described, Oct 18, 2026. DeepSeek V4.1 Flash through Coralbricks in the omp harness.
- Unfavorable
The day's bill is **4.3x** the estimate at published rates.
Nous Portal: deepseek-v4.1-flash cache reads billed at ~full input price. LohasGuy, GitHub user filing a Hermes Agent issue, self-described, Sep 30, 2026. DeepSeek V4.1 Flash (deepseek/deepseek-v4.1-flash) on a Nous Portal subscription via Hermes Agent.
- Favorable
reasonably priced when comparing to other open weight models of similar size
Artificial Analysis - DeepSeek V4.1 Flash 1017. Artificial Analysis, independent benchmark publisher, self-described, Oct 26, 2026. DeepSeek V4.1 Flash, the 1017 checkpoint (Max).
- Favorable
it brought our bill down by A LOT
Comment on: Why isn't the industry freaking out about DeepSeek 4.1 Flash?. lmf4lol, Hacker News commenter, self-described, Oct 8, 2026. DeepSeek V4.1 Flash (v4.1-flash, thinking high) running personal assistants.
- Favorable
$0.003-0.006 per 1M input tokens is shockingly cheap
Comment on: Why isn't the industry freaking out about DeepSeek 4.1 Flash?. girvo, Hacker News commenter, self-described, Oct 8, 2026. DeepSeek V4.1 Flash direct from DeepSeek in the Pi harness.
- Favorable
I have rarely exceeded $1 in expected costs in a session.
Why Isn't The Industry Freaking Out About DeepSeek 4.1 Flash?. Jono, author of the Jono's Corner blog, self-described, Oct 7, 2026. DeepSeek V4.1 Flash (DeepSeek 4.1 Flash) on an OpenCode Go plan across a dozen projects.
- Favorable
The model has gained a lot of (well-deserved) attention for its performance at a small price.
Latest open artifacts (#25): DeepSeek v4.1 Flash 1017, American-made models. Florian Brand, researcher at Prime Intellect, writing for Interconnects, self-described, Oct 20, 2026. DeepSeek V4.1 Flash, the 1017 checkpoint (DeepSeek-V4.1-Flash-1017).
- Favorable
the cheapest model in the open-weight top 10
Vals AI on DeepSeek V4.1 Flash. Vals AI, public LLM evaluation publisher, self-described, Sep 10, 2026. DeepSeek V4.1 Flash on the Vals Index, high reasoning effort.
- Favorable
DeepSeek came in at $0.07 to Haiku's $0.30
DeepSeek V4.1-Flash-1017 vs. Claude Haiku 5.5: More accurate at a fraction of the price. Jessica Wachtel, writer at The New Stack, self-described, Oct 22, 2026. DeepSeek V4.1 Flash, the 1017 checkpoint, via OpenRouter pinned to DeepSeek's servers, default settings, off-peak.
- Favorable
DeepSeek costs $0.14 a session and Sonnet $1.28, so about a ninth of the money.
DeepSeek vs Claude for coding: V4.1 Flash 1017 against Opus 5.5, Sonnet 5.5 and Haiku 5.5. Bito, AI coding tools company, on its own coding benchmark, self-described, Oct 19, 2026. DeepSeek V4.1 Flash, the 1017 checkpoint, inside Claude Code.
- Unfavorable
continuing to generate with that model costs roughly twice as much
[Plugin]: OpenCode off-peak gate for DeepSeek V4.1 Flash. capyBearista, GitHub user proposing an OpenCode plugin, self-described, Oct 26, 2026. DeepSeek V4.1 Flash (opencode-go/deepseek-v4.1-flash) as Fixer subagents in OpenCode.
- Unfavorable
One run has token accounting: 2,946,619 input tokens
V4.1-Flash: 33–50 agent turns for a one-field config edit (verification with no stopping criterion). jiokasd3323, Hugging Face user, self-described, Sep 11, 2026. DeepSeek V4.1 Flash in the open-source deepseek-harness agent.
- Favorable
this model represents a clear shift in capabilities at this humble price
Praise and critique for this model. mindplay, Hugging Face user, self-described, Sep 20, 2026. DeepSeek V4.1 Flash (DeepSeek 4.1 Flash) building an Android app from a spec.
- Unfavorable
I've already spent 10 dollars in about 30 minutes
excessive consumption. xdjc, Hugging Face user, self-described, Oct 22, 2026. DeepSeek V4.1 Flash, the 1017 checkpoint.
- Favorable
I find it challenging to hit the $20 mark
Comment on: MiniMax M3.1 Flash. switchbak, Hacker News commenter, self-described, Oct 19, 2026. DeepSeek V4.1 Flash (DS) through OpenRouter and Fireworks at API rates.
- Favorable
the DeepSeek 4.1 models are currently the ultimate cost-effective model the rest have to match with
Comment on: MiniMax M3.1 Flash. sinuhe69, Hacker News commenter, self-described, Oct 19, 2026. DeepSeek V4.1 Flash (Flash 4.1) on OpenRouter.
- Favorable
It is the cheapest model in the top 15.
DeepSeek V4.1 Flash Benchmarks, Cost and Capabilities | Vals AI. Vals AI, public LLM evaluation publisher, self-described, Sep 10, 2026. DeepSeek V4.1 Flash at max reasoning effort via the DeepSeek provider.
Speed 68%
- Favorable
At 175 tokens per second, DeepSeek V4.1 Flash (Max) is notably fast
Artificial Analysis - DeepSeek V4.1 Flash. Artificial Analysis, independent benchmark publisher, self-described, Oct 26, 2026. DeepSeek V4.1 Flash (reasoning).
- Favorable
There's something to be said for the speed with which it gets word done
Comment on: MiniMax M3.1 Flash. TheArcane, Hacker News commenter, self-described, Oct 20, 2026. DeepSeek V4.1 Flash through platform.deepseek.com.
- Unfavorable
deepseek v4.1 flash via deepseek API: took 20m to find one p1 issue
Comment on: DeepSeek-v4.1-Flash-1017. AmazingTurtle, Hacker News commenter, self-described, Oct 17, 2026. DeepSeek V4.1 Flash via the DeepSeek API reviewing a C++ game engine codebase.
- Favorable
I run it on very fast local infra (200+ tok/s)
Comment on: DeepSeek V4.1 Flash 1017 (Max). lhl, Hacker News commenter, self-described, Oct 19, 2026. DeepSeek V4.1 Flash and DeepSeek V4.1 Flash 1017 on fast local infrastructure.
- Unfavorable
faster per task (2.9 vs 4.9 minutes) vs v4.1 Flash 1017 (max)
Comment on: DeepSeek V4.1 Flash 1017 (Max). Tiberium, Hacker News commenter, self-described, Oct 19, 2026. DeepSeek V4.1 Flash, the 1017 checkpoint at max effort, on Artificial Analysis.
- Favorable
I regularly get ~300 tokens/sec with DeepSeek Flash
Comment on: DeepInfer: High-performance inference framework for DeepSeek models. RussianCow, Hacker News commenter, self-described, Oct 20, 2026. DeepSeek V4.1 Flash (DS V4.1 Flash) on agentic tasks.
- Favorable
DeepSeek V4.1 Flash is an order of magnitude faster
Comment on: MiniMax M3.1 Flash. RussianCow, Hacker News commenter, self-described, Oct 19, 2026. DeepSeek V4.1 Flash compared with MiniMax M3.1 Flash.
- Favorable
DeepSeek V4.1 Flash is astoundingly fun to use because it's so quick
Comment on: DeepInfer: High-performance inference framework for DeepSeek models. inciampati, Hacker News commenter, self-described, Oct 20, 2026. DeepSeek V4.1 Flash.
- Favorable
It is terribly fast! And smart. And cheap.
Comment on: Token-maxxing is dead, OpenRouter's token usage plateaus. brazukadev, Hacker News commenter, self-described, Oct 22, 2026. DeepSeek V4.1 Flash, the 1017 checkpoint, over two days.
- Favorable
V4.1 Flash is fast and perfect for everything
Comment on: DeepInfer: High-performance inference framework for DeepSeek models. VonLuderitz, Hacker News commenter, self-described, Oct 20, 2026. DeepSeek V4.1 Flash through the DeepSeek API.
- Favorable
It's faster, outputting roughly 176 to 221 tokens per second compared to GPT-6 Astra's 57 tokens per second
Abhinav Amrute on DeepSeek V4.1 Flash. Abhinav Amrute (@AbhinavAmrute), builder of Blitsum, X user, self-described, Oct 25, 2026. DeepSeek V4.1 Flash.
- Favorable
Speed is quite good actually
Constantin Diez on DeepSeek V4.1 Flash 1017 on DGX Spark. Constantin Diez (@ConstantinDiez), X user, self-described, Oct 25, 2026. DeepSeek V4.1 Flash and the 1017 update on 2x DGX Spark.
- Favorable
the combination of speed + Go limits is probably the biggest reason i keep coming back to it
Yum on more DeepSeek V4.1 Flash 1017 findings. Yum (@yuhasbeentaken), growth engineer who benchmarks AI agents, X user, self-described, Oct 19, 2026. DeepSeek V4.1 Flash, the 1017 checkpoint, in OpenCode free and Go.
- Unfavorable
my project finishes in 5 minutes instead of 20
Comment on: Prompting Claude Opus 5.5. criley2, Hacker News commenter, self-described, Sep 28, 2026. DeepSeek V4.1 Flash (Deepseek Flash v4.1) implementing with Opus 5.5 reviewing.
- Unfavorable
Afaik you cannot serve a single DeepSeek Flash 4.1 stream at 750 t/s
Comment on: Everyone should slow down AI development except for me. user43928, Hacker News commenter, self-described, Sep 13, 2026. DeepSeek V4.1 Flash (DeepSeek Flash 4.1).
- Unfavorable
DeepSeek V4.1 can run on my setup, but it's slow.
Comment on: IBM CEO says open weight models are now good and cheap on-prem. _ache_, Hacker News commenter, self-described, Oct 26, 2026. DeepSeek V4.1 Flash on a local dual R9700 GPU setup.
- Unfavorable
you will see trash coming out of openrouter at 1-5 tokens/second
Comment on: One Month Without AI. elwebmaster, Hacker News commenter, self-described, Sep 26, 2026. DeepSeek V4.1 Flash (deepseek-4.1 flash) on OpenRouter, Qwen Cloud and the DeepSeek API.
- Favorable
it's still 100% faster for a very good price, so I won't complain
Comment on: DeepSeek v4.1 Flash. k__, Hacker News commenter, self-described, Sep 10, 2026. DeepSeek V4.1 Flash on OpenRouter at launch.
- Unfavorable
Thinking, even set to low, adds way too much latency to be useful for this task.
Comment on: DeepSeek v4.1 Flash. jamesponddotco, Hacker News commenter, self-described, Sep 10, 2026. DeepSeek V4.1 Flash as a voice assistant.
- Favorable
a Flash model, that is 2x a 2.5x faster then the older Flash version
Comment on: DeepSeek v4.1 Flash. benjiro29, Hacker News commenter, self-described, Sep 10, 2026. DeepSeek V4.1 Flash (DS v4.1 Flash) at launch.
- Favorable
It was fast, cheap, and got a high scoring result
Comment on: DeepSeek v4.1 Flash. raesene9, Hacker News commenter, self-described, Sep 10, 2026. DeepSeek V4.1 Flash on a personal Kubernetes security benchmark.
- Favorable
but also faster and slightly more token efficient
Comment on: DeepSeek v4.1 Flash. XCSme, Hacker News commenter, self-described, Sep 10, 2026. DeepSeek V4.1 Flash on the aibenchy comparison.
- Favorable
it is really fast. What's more?
Comment on: DeepSeek v4.1 Flash. BrucecarlL, Hacker News commenter, self-described, Sep 10, 2026. DeepSeek V4.1 Flash debugging pages through the browser.
- Unfavorable
every later model request in the session waits 10–60 s before the first token
deepseek-v4.1-flash: 10-60 s to first token once images are in context. slovx2, GitHub user filing a Command Code issue, self-described, Oct 10, 2026. DeepSeek V4.1 Flash (deepseek/deepseek-v4.1-flash) in the Command Code CLI.
- Favorable
At 169 tokens per second, DeepSeek V4.1 Flash 1017 (Max) is notably fast
Artificial Analysis - DeepSeek V4.1 Flash 1017. Artificial Analysis, independent benchmark publisher, self-described, Oct 26, 2026. DeepSeek V4.1 Flash, the 1017 checkpoint (Max).
- Favorable
If I run it all day long it costs $1-2. Its fast.
Comment on: Why isn't the industry freaking out about DeepSeek 4.1 Flash?. gregwebs, Hacker News commenter, self-described, Oct 8, 2026. DeepSeek V4.1 Flash (DeepSeek 4.1 flash) as coding orchestrator and verifier.
- Favorable
DeepSeek was faster on triage and slightly faster across the three runs combined
DeepSeek V4.1-Flash-1017 vs. Claude Haiku 5.5: More accurate at a fraction of the price. Jessica Wachtel, writer at The New Stack, self-described, Oct 22, 2026. DeepSeek V4.1 Flash, the 1017 checkpoint, via OpenRouter pinned to DeepSeek's servers, default settings, off-peak.
- Unfavorable
Speed goes to Sonnet by a mile. A long session took Sonnet 6.8 minutes and DeepSeek 15.4.
DeepSeek vs Claude for coding: V4.1 Flash 1017 against Opus 5.5, Sonnet 5.5 and Haiku 5.5. Bito, AI coding tools company, on its own coding benchmark, self-described, Oct 19, 2026. DeepSeek V4.1 Flash, the 1017 checkpoint, inside Claude Code.
- Favorable
the inference speed is impressive >200t/s
Tested on coding and agentic work - not that impressive. curiousily, Hugging Face user, self-described, Sep 11, 2026. DeepSeek V4.1 Flash via OpenRouter on coding and agentic tests.
- Favorable
this model is stupid fast
wow, this thing is a beast - and i've NEVER said that about a deepseek model. aaron-newsome, Hugging Face user running the model locally, self-described, Oct 20, 2026. DeepSeek V4.1 Flash, the 1017 checkpoint, on 4x RTX PRO 6000 across dozens of tickets.
- Favorable
benefit from its far superior latencies
Comment on: MiniMax M3.1 Flash. switchbak, Hacker News commenter, self-described, Oct 19, 2026. DeepSeek V4.1 Flash (DS) through OpenRouter and Fireworks at API rates.
- Favorable
On Flash 4.1, I constantly get ~180 tok/s and the real work got done fast, too.
Comment on: MiniMax M3.1 Flash. sinuhe69, Hacker News commenter, self-described, Oct 19, 2026. DeepSeek V4.1 Flash (Flash 4.1) on OpenRouter.
- Unfavorable
Even though the tok/s is good, it stills feels slow because of this.
Comment on: MiniMax M3.1 Flash. seabombs, Hacker News commenter, self-described, Oct 20, 2026. DeepSeek V4.1 Flash (DS-4.1-Flash) and the 1017 update.
- Favorable
finishing tasks in well under half the time
DeepSeek V4.1 Flash Benchmarks, Cost and Capabilities | Vals AI. Vals AI, public LLM evaluation publisher, self-described, Sep 10, 2026. DeepSeek V4.1 Flash at max reasoning effort via the DeepSeek provider.
Reliability 42%
- Favorable
I'm guaranteed it's not being changed on me
Comment on: DeepSeek V4.1 Flash 1017 (Max). lhl, Hacker News commenter, self-described, Oct 19, 2026. DeepSeek V4.1 Flash and DeepSeek V4.1 Flash 1017 on fast local infrastructure.
- Unfavorable
Getting a lot of errors from OpenRouter's endpoint
Comment on: DeepSeek-v4.1-Flash-1017. summarity, Hacker News commenter, self-described, Oct 17, 2026. DeepSeek V4.1 Flash, the 1017 checkpoint, through OpenRouter in GitHub Copilot CLI.
- Favorable
I never experience quota issues
Comment on: GPT-6 Sol and Luna. flippingheck, Hacker News commenter, self-described, Sep 23, 2026. DeepSeek V4.1 Flash (DeepSeek 4.1 Flash).
- Unfavorable
Why Deepseek 4.1 flash always 429 these days
XYZ on Deepseek 4.1 flash 429 errors. XYZ (@zhangasync), full stack WebGIS developer, X user, self-described, Oct 25, 2026. DeepSeek V4.1 Flash (Deepseek 4.1 flash) on an OpenCode Go subscription.
- Favorable
i've been able to run it for basically a full working day during off-peak windows
Yum on more DeepSeek V4.1 Flash 1017 findings. Yum (@yuhasbeentaken), growth engineer who benchmarks AI agents, X user, self-described, Oct 19, 2026. DeepSeek V4.1 Flash, the 1017 checkpoint, in OpenCode free and Go.
- Unfavorable
Deepseek servers went unavailable for 5 hours.
Comment on: DeepSeek-v4.1-Flash-1017. npn, Hacker News commenter, self-described, Oct 17, 2026. DeepSeek V4.1 Flash on the DeepSeek API around the 1017 rollout.
- Unfavorable
deepseek v4.1 flash rate limits me on prod but never seems to happen on local
Comment on: So you want to use OpenRouter?. mesmertech, Hacker News commenter, self-described, Sep 11, 2026. DeepSeek V4.1 Flash through OpenRouter in production.
- Unfavorable
Whenever I select DeepSeek v4.1 Flash it always returns only
DeepSeek v4.1 Flash always returns 400. ioma8, GitHub user filing an OpenCode issue, self-described, Oct 9, 2026. DeepSeek V4.1 Flash through OpenCode Go in opencode cli v2.0.26.
- Favorable
With my OpenCode Go sub of $10/month, DeepSeek is basically unlimited.
Why Isn't The Industry Freaking Out About DeepSeek 4.1 Flash?. Jono, author of the Jono's Corner blog, self-described, Oct 7, 2026. DeepSeek V4.1 Flash (DeepSeek 4.1 Flash) on an OpenCode Go plan across a dozen projects.
- Unfavorable
I keep getting this error every few hours
OpenCode Go: Error: Provider blocked the response-DeepSeek V4.1 Flash. yabdali, GitHub user filing an OpenCode issue, self-described, Oct 26, 2026. DeepSeek V4.1 Flash on the OpenCode Go plan in OpenCode v2.1.4.
- Unfavorable
The reasoning budget is exhausted, content is empty, and the user sees no output at all.
Reasoning loop amplification with DSpark enabled + intrinsic repetition loop in DeepSeek-V4.1-Flash. wwwcxc520, Hugging Face user running the model in production, self-described, Oct 12, 2026. DeepSeek V4.1 Flash in production on 4x RTX PRO 6000 and on the official DeepSeek API.
- Favorable
it's cheap, fast, and reliable
Comment on: Sonnet 5.5. jchw, Hacker News commenter, self-described, Sep 28, 2026. DeepSeek V4.1 Flash.