Speed
81tokens a second
Output speed. How fast it writes once the answer starts.
- First token
- 0.9 s
Model family by Meta
Llama
Meta's open-weight Llama model family.
Where it sits in Meta's lineup
- Made by
- Meta
- Releases
- 2 tracked
Strengths and weaknesses
Compare with other models Up to 3 beside Llama 4 Scout
- Llama 4 Scout
Suggested comparisons
Llama 4 Scout is the newest Llama release. Add its earlier releases to see how the line moved.
Llama 4 Scout
Ranked against the 40 current releases on this chart, Llama 4 Scout's best rank is 13th of 26 on Answers in full. On Math, Epoch AI's runs on OTIS Mock AIME 2024-2025 put Llama 4 Scout 12.8 points under Llama 4 Maverick. Instruction following is Artificial Analysis's run on IFBench, marked on the chart. It ranks lowest on Multimodal, 25th of 25 and Science, 25th of 25. Agentic coding, Computer use and Factuality: not yet published by Meta or any independent evaluator, checked Nov 2, 2026.
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
- Llama 4 ScoutThis pageResults on 9 of 12 axes$0.16 / $0.64On Microsoft Foundry; the maker sells no API access133 tokens/sFirst token in 0.8 s
Prices and speeds as of Nov 2, 2026.
Llama 4 Scout on each axis9 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
- Llama 4 ScoutNot yet published by Meta or any independent evaluator, checked Nov 2, 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
- Llama 4 Scout21.3%
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. Where it has no run of a model, the maker's own figure or another lab's run stands in, marked with its benchmark.
- Llama 4 Scout7.8%Epoch AI's runBenchmark: OTIS Mock AIME 2024-2025, accuracy, high reasoning. From another source, so it is drawn and marked but not ranked with the others.Epoch AI's run of the instruction-tuned release. Llama 4 has no reasoning mode.
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
- Llama 4 Scout51.8%
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
- Llama 4 Scout3.8%Artificial Analysis publishes 3.8 for Llama 4 Scout, which has no reasoning mode, on this test.
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
- Llama 4 Scout0.2%Artificial Analysis publishes 0.2 for Llama 4 Scout on this test, far below its other results.
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
- Llama 4 ScoutNot yet published by Meta or any independent evaluator, checked Nov 2, 2026
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
- Llama 4 Scout27.7%
The share of MMMU-Pro's college-level questions over charts, diagrams and photos the model answers correctly.
MMMU-Pro, overall accuracy, no tools
- Llama 4 Scout52.9%
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
- Llama 4 ScoutNot yet published by Meta or any independent evaluator, checked Nov 2, 2026
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
- Llama 4 Scout70.1%
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. Where it has no run of a model, the maker's own figure or another lab's run stands in, marked with its benchmark.
- Llama 4 Scout39.5%Artificial Analysis's runBenchmark: IFBench, accuracy, Artificial Analysis IFBench run. From another source, so it is drawn and marked but not ranked with the others.Artificial Analysis ran Llama 4 Scout, which has no reasoning mode, in its own evaluation harness.
Cost, speed, capacity, quality and accuracy for Llama 4 Scout, with where each figure sits among the 41 models GILD tracks. These measures stand beside the chart and never feed it.
Capacity
10Mtokens
Context window. The most one request can hold, as the maker states it.
- Max output
- 8,000
- Reads
- Text, Images
Quality
-155Elo
GDPval knowledge work. Real office tasks, graded head to head.
Where you can get it
4of 19 routes
Routes offering it. Of the clouds, gateways and coding products GILD tracks, those offering it today.
- Open weights
- Yes
- Licence
- Llama 4 Community License
Figures from Artificial Analysis, Meta, AWS, GILD's route matrix and GitHub, read Oct 28 to 29, 2026. Each measure's definition and source open under . Not yet published for Llama 4 Scout: Cost per task, Cached input, Whole answer, Intelligence Index, Terminal-Bench 4.0, Epoch Capabilities Index, Hallucination rate and Knowledge accuracy.
Every value with its benchmark, run and source
| Axis | Benchmark and setting | Llama 4 Scout | Run | Source | Date |
|---|---|---|---|---|---|
| Agentic coding | Terminal-Bench 4.0Pass@1 averaged over 3 runs, mini-swe-agent harness | Not yet published by Meta or any independent evaluator, checked Nov 2, 2026 | |||
| Code | SciCodeSubproblem accuracy, pass@1, highest effort run | 21.3% | Llama 4 ScoutEffort: default. Harness: none. | Artificial Analysis | Nov 2, 2026 |
| Math | OTIS Mock AIME 2024-2025Accuracy, OTIS Mock AIME 2024-2025, high reasoning. Epoch AI's run of the instruction-tuned release. Llama 4 has no reasoning mode.Stands in for FrontierMath Tiers 1-3, accuracy, pass@1, highest effort run, which has no run of Llama 4 Scout yet. | 7.8% | Llama-4-Scout-17B-16E-InstructEffort: default. Harness: none. | Epoch AIRun by Epoch AI | Apr 8, 2025 |
| Science | GPQA DiamondAccuracy, pass@1, highest effort run | 51.8% | Llama-4-Scout-17B-16E-InstructEffort: default. Harness: none. | Epoch AI | Apr 8, 2025 |
| Hard reasoning | Humanity's Last ExamAccuracy, text-only questions, no tools. Artificial Analysis publishes 3.8 for Llama 4 Scout, which has no reasoning mode, on this test. | 3.8% | Llama 4 ScoutEffort: default. Harness: none. | Artificial Analysis | Nov 2, 2026 |
| Tool use | AutomationBench-AAScore, Artificial Analysis run. Artificial Analysis publishes 0.2 for Llama 4 Scout on this test, far below its other results. | 0.2% | Llama 4 ScoutEffort: default. Harness: Artificial Analysis AutomationBench harness. | Artificial Analysis | Nov 2, 2026 |
| Computer use | OSWorld 2.1Partial score, full 108-task set, v2.1 release | Not yet published by Meta or any independent evaluator, checked Nov 2, 2026 | |||
| Long context | AA-LCR v1.1Accuracy, Artificial Analysis run | 27.7% | Llama 4 ScoutEffort: default. Harness: none. | Artificial Analysis | Nov 2, 2026 |
| Multimodal | MMMU-ProOverall accuracy, no tools | 52.9% | Llama 4 ScoutEffort: default. Harness: none. | Artificial Analysis | Nov 2, 2026 |
| Factuality | AA-Omniscience AccuracyAccuracy, Artificial Analysis run | Not yet published by Meta or any independent evaluator, checked Nov 2, 2026 | |||
| Answers in full | SpeechMap% Complete over 2,120 contested requests, reasoning-on entry | 70.1% | Effort: default. Harness: none. | SpeechMap.AI | Oct 28, 2026 |
| Instruction following | IFBenchAccuracy, Artificial Analysis IFBench run. Artificial Analysis ran Llama 4 Scout, which has no reasoning mode, in its own evaluation harness.Stands in for MultiChallenge, accuracy, Scale AI run, which has no run of Llama 4 Scout yet. | 39.5% | Llama 4 ScoutEffort: default. Harness: none. | Artificial AnalysisRun by Artificial Analysis | Nov 2, 2026 |
Price and speed
- Meta sells no API access to Llama 4 Scout. Among Amazon Bedrock, Google Vertex AI and Microsoft Foundry, the lowest list price is on Microsoft Foundry: $0.16 per million input tokens and $0.64 per million output tokens (US East 2). Every host's price is in Routes. Microsoft Azure pricing, Oct 29, 2026.
- Llama 4 Scout writes 132.8 output tokens per second at the median across the providers serving it, and its first token arrives 0.8 s after the request. Artificial Analysis, Nov 2, 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 |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 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 |
| ||||||||||||
| 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% |
| ||||||||||||
| 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 |
| ||||||||||||
| 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 |
| ||||||||||||
| 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 |
| ||||||||||||
| 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% |
| ||||||||||||
| 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 |
| ||||||||||||
| 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 |
| ||||||||||||
| 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 |
| ||||||||||||
| 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 |
| ||||||||||||
| 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 |
| ||||||||||||
| 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 |
| ||||||||||||
| 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 |
| ||||||||||||
| 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 |
| ||||||||||||
| 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 |
| ||||||||||||
| 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% |
| ||||||||||||
| 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% |
| ||||||||||||
| 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% |
| ||||||||||||
| 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% |
| ||||||||||||
| 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% |
| ||||||||||||
| 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% |
| ||||||||||||
| 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 |
| ||||||||||||
| 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 |
| ||||||||||||
| 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 |
| ||||||||||||
| 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 |
| ||||||||||||
| 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 |
| ||||||||||||
| 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% |
| ||||||||||||
| 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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| 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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| 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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| 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 |
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| 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 |
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| 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 |
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| 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 |
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| 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 |
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| 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 |
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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%
- Muse Wonder49.5%
- GPT-6.1 Terra49.5%
- 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%
- Muse Spark 1.310.6%
- Claude Sonnet 510.6%
- 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%
- Muse Wonder82.1%
- GPT-5.6 Luna82.1%
- 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
- Muse Spark 1.393.5%Artificial Analysis's run, GPQA Diamond
- GPT-5.593.5%Artificial Analysis's run
- 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%
- Muse Spark 1.348.7%
- Claude Opus 4.848.7%
- 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%
- Muse Spark 1.357.9%
- Grok 4.557.9%
- 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%
- Llama 4 Scout0.2%
- Llama 4 Maverick0.2%
- gpt-oss-120b0.2%
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%
- Muse Spark 1.383%
- GPT-6.1 Sol83%
- GPT-5.6 Terra83%
- Claude Haiku 5.582.7%
- Claude Sonnet 5.582.7%
- GPT-6.1 Terra82.7%
- DeepSeek V4.1 Flash82.7%
- 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%
- Muse Wonder80.7%
- GPT-6 Astra80.7%
- 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%
- Muse Spark Open78.3%
- GLM-5.278.3%
- 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%
- GPT-6 Luna39.6%
- DeepSeek V4.1 Flash39.6%
- 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%
- Muse Spark Open74.2%
- GPT-6.1 Terra74.2%
- 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 Llama release we track, newest first.
- Llama 4 MaverickAn earlier Meta release, a natively multimodal mixture-of-experts model with 17B active parameters across 128 experts and a 1M-token context window. Weights under the Llama 4 Community License; Meta lists no API price, so hosts serve it.
- Llama 4 ScoutAn earlier Meta release, a natively multimodal mixture-of-experts model with 17B active parameters and a 10M-token context window that fits on one H100 GPU. Weights under the Llama 4 Community License; Meta lists no API price, so hosts serve it.
What practitioners report
Llama 4 Scout has enough accounts to score 1 of 7 axes so far.
Each figure is the share of accounts naming Llama 4 Scout 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. | 53% | 8 favorable, 7 not, 15 authors |
| Tool use and structured outputWhether it calls tools correctly, returns valid structured output, and keeps agent loops on track. | Needs 5 accounts from 3 authors | 1 favorable, 2 not, 3 authors |
| Long contextHow it holds up over long documents, large codebases, long sessions, and many images or PDFs. | Only concerns on record | 0 favorable, 3 not, 3 authors |
| Developer experienceHow it is to build with: prompting, steering, effort settings, and support across SDKs and providers. | Only concerns on record | 0 favorable, 6 not, 6 authors |
| CostWhat the work costs: price per task, token use, and what caching and batch save. | Only praise on record | 1 favorable, 0 not, 1 author |
| SpeedResponse time, time to first token, and throughput. | Needs 5 accounts from 3 authors | 3 favorable, 1 not, 4 authors |
| ReliabilityWhether requests keep succeeding: overloaded errors, outages, rate limits, and changes that broke what worked. | Needs 5 accounts from 3 authors | 1 favorable, 3 not, 4 authors |
Every model on these seven axes
| Axis | Llama 4 Scout | Muse Spark Open | Muse Wonder | Muse Spark 1.3 | Llama 4 Maverick | 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 | DeepSeek V4.1 Flash | DeepSeek V4 Pro | 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 | Qwen3.8 27B | Qwen3.8 Max | MiMo-V2.6-Pro | MiMo-V2.6-Flash | Ling 3.1 Flash | Step 5 Preview |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Quality and reasoning | 53%8 favorable, 7 not, 15 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 | 44%8 favorable, 10 not, 17 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 | 61%25 favorable, 16 not, 40 authors | Only concerns on record0 favorable, 4 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 | 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 | Needs 5 accounts from 3 authors1 favorable, 2 not, 3 authors | No accounts yet | Only concerns on record0 favorable, 1 not, 1 author | Needs 5 accounts from 3 authors1 favorable, 1 not, 2 authors | Only concerns on record0 favorable, 4 not, 4 authors | 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 | 59%10 favorable, 7 not, 17 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 | 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 | Only concerns on record0 favorable, 3 not, 3 authors | 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 | 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 | 58%7 favorable, 5 not, 12 authors | No accounts yet | 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 | 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 | Only concerns on record0 favorable, 6 not, 6 authors | 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, 1 not, 1 author | 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 | 35%8 favorable, 15 not, 23 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 | 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 | Only praise on record1 favorable, 0 not, 1 author | 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 | 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 | 66%25 favorable, 13 not, 37 authors | Only praise on record2 favorable, 0 not, 2 authors | 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 | 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 | Needs 5 accounts from 3 authors3 favorable, 1 not, 4 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 | No accounts yet | 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 | 68%21 favorable, 10 not, 30 authors | Only concerns on record0 favorable, 1 not, 1 author | 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 | 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 | Needs 5 accounts from 3 authors1 favorable, 3 not, 4 authors | No accounts yet | Only concerns on record0 favorable, 2 not, 2 authors | Only concerns on record0 favorable, 1 not, 1 author | Only concerns on record0 favorable, 1 not, 1 author | 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 | 42%5 favorable, 7 not, 12 authors | Needs 5 accounts from 3 authors1 favorable, 1 not, 2 authors | 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 | 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 33 accounts behind Llama 4 Scout's figures
GILD searched GitHub, Reddit and the web for accounts that name Llama 4 Scout.
Quality and reasoning 53%
- Favorable
The summary from Scout and Maverick both look good (comparable to Claude), and with this structure, Scout seems to follow the prompt slightly better.
The Llama 4 herd. georgeck, Hacker News commenter, self-described, Apr 5, 2025. Llama 4 Scout from OpenRouter summarizing a 339-comment Hacker News thread with a custom system prompt.
- Unfavorable
I can confidently say that Scout is not as good at writing as o1 pro, o3 mini, Claude, R1 or grok 3.
The Llama 4 herd. vessenes, Hacker News commenter, self-described, Apr 5, 2025. Llama 4 Scout on groqchat, which the author judged to be the model behind meta.ai, for essay writing.
- Favorable
I started running Llama 4 Scout on Groq using my Common Lisp client, and now trying Llama 4 Maverick on abacus.ai Really impressive!
The Llama 4 herd. mark_l_watson, Hacker News commenter, self-described, Apr 6, 2025. Llama 4 Scout on Groq from the author's Common Lisp client.
- Favorable
Scout (17B/109B) was punching in the ballpark of Gemma 3 27B, but not too far off Llama 3.3 70B and Mistral Large 2411 (123B)
Llama 4 Smells Bad. lhl, Hacker News commenter, self-described, Apr 24, 2025. Llama 4 Scout on the author's own MixEval, LiveBench, IFEval and EvalPlus runs with vLLM v0.8.3.
- Favorable
and definitely loses to LLaMA 4 Scout (~86%)
Introducing Gemma 3n. lostmsu, Hacker News commenter who built an online MMLU checker, self-described, Jun 26, 2025. Llama 4 Scout on the author's own MMLU subset website.
- Unfavorable
Maverick and Scout were not great, even with post-training in my experience
Open models by OpenAI. BoorishBears, Hacker News commenter, self-described, Aug 5, 2025. Llama 4 Scout and Maverick, including post-trained versions, in the author's own work.
- Unfavorable
Llama 4 Scout completely broke down.
GPT-5.1: A smarter, more conversational ChatGPT. hamburgererror, Hacker News commenter, self-described, Nov 13, 2025. Llama 4 Scout on duck.ai on a question other models also answered.
- Favorable
Guess which ones got 100% accuracy? GPT-5-mini, Grok-4.1-fast and... Llama4 Scout.
Dell's version of the DGX Spark fixes pain points. kouteiheika, Hacker News commenter, self-described, Jan 2, 2026. Llama 4 Scout through OpenRouter in an ablation of 20+ models on a batch query job.
- Favorable
Small (8B-17B): Qwen 3 8B, Llama 4 Scout (Good for RAG/Extraction).
Tell HN: I cut Claude API costs from $70/month to pennies. 44za12, Hacker News commenter who maintains a model selection cheat sheet, self-described, Jan 26, 2026. Llama 4 Scout in the author's model selection cheat sheet by task type.
- Favorable
framed the question as a riddle and all models except for Llama 4 Scout failed anyway.
I want to wash my car. The car wash is 50 meters away. Should I walk or drive?. ivanjermakov, Hacker News commenter, self-described, Feb 16, 2026. Llama 4 Scout on the car-wash question framed as a riddle.
- Unfavorable
The structural channel for the free Llama models (Llama 4 Scout, Llama 3.3 70B on Workers AI) is genuinely noisy
Show HN: I built a LLM human rights evaluator for HN (content vs. site behavior). 9wzYQbTYsAIc, Hacker News commenter who built an LLM rights evaluator, self-described, Mar 4, 2026. Llama 4 Scout on Workers AI scoring Hacker News front-page stories.
- Unfavorable
They were both DOA.. couldn't even beat much smaller local models.
Muse Spark: Scaling towards personal superintelligence. prodigycorp, Hacker News commenter, self-described, Apr 8, 2026. Llama 4 Scout and Maverick tried by the author against smaller local models.
- Unfavorable
as soon as you try them yourself they fall to pieces
Muse Spark: Scaling towards personal superintelligence. nl, Hacker News commenter who runs an agentic SQL benchmark, self-described, Apr 9, 2026. Llama 4 Scout (llama-4-scout-17b-16e) on the author's own agentic SQL benchmark.
- Favorable
Llama Scout outperformed Gemini Flash 2.5 on a benchmark I built at the time.
Mistral OCR 4.1. ComputerPerson, Hacker News commenter, self-described, Aug 13, 2026. Llama 4 Scout on a document benchmark the author built.
- Unfavorable
Scout produces non-functional or severely deficient code across multiple tasks.
Llama 4 Scout: Total Disaster – or Misunderstood Workhorse?. PromptInjection, author of the Prompt Injection newsletter, self-described, Dec 8, 2025. Llama 4 Scout tested against GLM 4.5 Air and Qwen3 Next 80B on writing, coding and translation.
Tool use and structured output Needs 5 accounts from 3 authors
- Favorable
I'm able to get great structured output from both the latest Gemini Flash models and the latest Llama Scout models.
Ask HN: Is synthetic data generation practical outside academia?. publicdaniel, Hacker News commenter building a document parsing engine, self-described, Jun 7, 2025. Llama 4 Scout hosted on Groq for structured output from PDF documents.
- Unfavorable
Llama-4-scout-17b-16e scores 14/25
Muse Spark: Scaling towards personal superintelligence. nl, Hacker News commenter who runs an agentic SQL benchmark, self-described, Apr 9, 2026. Llama 4 Scout (llama-4-scout-17b-16e) on the author's own agentic SQL benchmark.
- Unfavorable
This causes an infinite loop in any client that relies on the standard OpenAI tool calling protocol
Llama 4 Scout MLX: Tool calls emitted as text instead of OpenAI tool_calls format. ferraro, GitHub user, self-described, Apr 13, 2026. Llama 4 Scout MLX 4-bit in LM Studio on a Mac Studio M3 Ultra with OpenCode.
Long context Only concerns on record
- Unfavorable
I got an error when passing a prompt with about 20k tokens to the Llama 4 Scout model on groq
Llama 4 Now Live on Groq. sinab, Hacker News commenter, self-described, Apr 6, 2025. Llama 4 Scout on the Groq API with a prompt of about 20k tokens.
- Unfavorable
unfortunately it is also disappointing at pretty much any context length
Breaking Quadratic Barriers: A Non-Attention LLM for Ultra-Long Context Horizons. littlestymaar, Hacker News commenter, self-described, Jun 16, 2025. Llama 4 Scout as an open-weight long-context model.
- Unfavorable
runtime errors occur if the total effective sequence length (text tokens + image feature representations + past_key_values_length) exceeds the model's config.text_config.attention_chunk_size
Bug: Llama4 Multimodal (Llama4ForConditionalGeneration) Fails with Optimized Attention (sdpa, eager) and KV Cache for Effective Sequence Lengths > attention_chunk_size (8192). Peter-233234, Hugging Face user, self-described, May 24, 2025. Llama 4 Scout Instruct (17B-16E) in transformers 4.53.2 with multi-image prompts and the KV cache on.
- Unfavorable
Llama 4 Scout 🆕 10M 1K 81.7 (69.4) 72.3 61.8 50.8 35.5 26.9 21.6
NoLiMa: Long-Context Evaluation Beyond Literal Matching. Adobe Research, publisher of the NoLiMa long-context benchmark (ICML 2025), self-described, Apr 10, 2025. Llama 4 Scout on the NoLiMa long-context benchmark from 1K to 32K tokens.
Developer experience Only concerns on record
- Unfavorable
that had a 2048 limit on output size for some reason
The Llama 4 herd. simonw, Hacker News commenter, self-described, Apr 5, 2025. Llama 4 Scout through OpenRouter and on Groq with the llm-groq plugin, summarizing a Hacker News thread.
- Unfavorable
When I tried llama4 scout and tried to set the max output tokens above 8192 it told me the max was 8192.
Llama 4 Now Live on Groq. jasonjmcghee, Hacker News commenter, self-described, Apr 5, 2025. Llama 4 Scout in the Groq console.
- Unfavorable
There were actually multiple bugs which impacted long context benchmarks and general inference
Llama 4 Smells Bad. danielhanchen, Hacker News commenter who helped fix Llama 4 inference bugs, self-described, Apr 24, 2025. Llama 4 Scout across transformers, llama.cpp and vLLM after release, plus the author's own GGUF uploads.
- Unfavorable
Above model is not loading correctly, however, meta-llama/Llama-4-Scout-17B-16E, works fine.
VLLM not loading meta-llama/Llama-4-Scout-17B-16E-Instruct. alokkrsahu, Hugging Face user, self-described, Apr 9, 2025. Llama 4 Scout Instruct (17B-16E) served with vLLM.
- Unfavorable
Could not run Llama 4 Scout with TGI in 2xH200
Could not run Llama 4 Scout with TGI in 2xH200. Bihan, GitHub user, self-described, Apr 9, 2025. Llama 4 Scout on Hugging Face TGI 3.2.3 across two H200 GPUs.
- Unfavorable
Running inference of QLoRA fine-tuned Llama-4 Scout does not work
Running inference of QLoRA fine-tuned Llama-4 Scout does not work. cyril-k, GitHub user, self-described, Apr 22, 2025. Llama 4 Scout fine-tuned with QLoRA in Axolotl on one H100, then served with vLLM.
Cost Only praise on record
- Favorable
but the pricing was way better for Groq
Mercury: Ultra-fast language models based on diffusion. asaddhamani, Hacker News commenter working on a performance-sensitive application, self-described, Jul 7, 2025. Llama 4 Scout on Groq against Inception Mercury in a performance-sensitive application.
Speed Needs 5 accounts from 3 authors
- Unfavorable
scout, although faster to generate, takes a while longer to fill in the long context, basically getting the same usability speeds as with the qwq or gemma 27b.
Roo or Cline? We're building a superset. ach9l, Hacker News commenter, self-described, Apr 12, 2025. Llama 4 Scout running locally on a 512 GB Mac Studio.
- Favorable
With llama hosted on groq it's about 3 seconds.
Ask HN: Is synthetic data generation practical outside academia?. publicdaniel, Hacker News commenter building a document parsing engine, self-described, Jun 7, 2025. Llama 4 Scout hosted on Groq for structured output from PDF documents.
- Favorable
I tried Mercury and Groq (Llama 3.1 8b, Llama 4 Scout) and the performance was neck-and-neck
Mercury: Ultra-fast language models based on diffusion. asaddhamani, Hacker News commenter working on a performance-sensitive application, self-described, Jul 7, 2025. Llama 4 Scout on Groq against Inception Mercury in a performance-sensitive application.
- Favorable
(eg, Llama 4 Scout 109B-A17B Q4 at almost 20 tok/s)
Coding with LLMs in the summer of 2025 – an update. lhl, Hacker News commenter, self-described, Jul 20, 2025. Llama 4 Scout at Q4 (109B-A17B) on an AMD Strix Halo machine.
Reliability Needs 5 accounts from 3 authors
- Unfavorable
And with Scout I got complete junk output for some reason
The Llama 4 herd. simonw, Hacker News commenter, self-described, Apr 5, 2025. Llama 4 Scout through OpenRouter and on Groq with the llm-groq plugin, summarizing a Hacker News thread.
- Favorable
I used their API just fine for Llama 4 Scout for weeks now.
Cerebras achieves 2,500T/s on Llama 4 Maverick (400B). M4v3R, Hacker News commenter, self-described, May 31, 2025. Llama 4 Scout through the Cerebras API.
- Unfavorable
Groq's official deprecations page confirms llama-4-scout-17b-16e-instruct was removed from the free/developer tier 2026-06-17
[provider-review] groq: llama-4-scout-17b-16e-instruct dropped from Groq's free/developer tier. chrizefan, GitHub user maintaining DigiThings provider reviews, self-described, Jul 19, 2026. Llama 4 Scout (llama-4-scout-17b-16e-instruct) on Groq's free/developer tier.
- Unfavorable
which Groq no longer serves
Groq fallback fails: model llama-4-scout no longer exists. lowfoon, GitHub user, self-described, Oct 6, 2026. Llama 4 Scout on Groq as the image-analysis fallback in Blue Iris AI Hub.