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GLM model by Z.ai

GLM-5.3

Z.ai's flagship open-weight model for coding and agentic work, with a 1M-token context window, on the Z.ai API and also served by Mistral AI and OpenRouter. Weights under the GLM-5.3 License.

Official page

Where it sits in Z.ai's lineup

  1. GLMZ.ai's GLM family of open-weight models for coding, agents, and reasoning.You are on GLM-5.3. Current:GLM-5.3-Flash
Stack role
Foundation Model / Reasoning Engine
Offered in
3 products
Made by
Z.ai
Family
GLM, version 5.3
Released
Aug 18, 2026 Current
In its family
Release 2 of 3 in GLM. The newest is GLM-5.3-Flash.

Strengths and weaknesses

Compare with other models Up to 3 beside GLM-5.3

  • GLM-5.3

Suggested comparisons

The models a buyer weighs against GLM-5.3, picked on list price and on Artificial Analysis's Intelligence Index of overall quality. Add one to draw it beside GLM-5.3.

GLM-5.3Z.aiThis page, always on the chart

Among the 40 current releases on this chart, GLM-5.3 ranks 8th of 37 on Code and 10th of 31 on Agentic coding. It ranks lowest on Factuality, 23rd of 30 and Science, 18th of 24. Instruction following: not yet published by Z.ai or any independent evaluator, checked Nov 2, 2026. It cannot take Computer use and Multimodal. GLM-5.3 reads text only.

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.

On the chart

  • GLM-5.3This pageResults on 9 of 12 axes$1.40 / $4.4086 tokens/sFirst token in 2.7 s

Prices and speeds as of Oct 28, 2026.

GLM-5.3 on each axis9 of 12 with a result

Beside the benchmarks

Cost, speed, capacity, quality and accuracy for GLM-5.3, with where each figure sits among the 40 models GILD tracks. These measures stand beside the chart and never feed it.

Cost

$2.01per task

Cost per task. One Intelligence Index task at list price, every token counted. Run at max effort.

Cached input
$0.26 per 1M tokens

Speed

94tokens a second

Output speed. How fast it writes once the answer starts. Run at max effort.

First token
2.5 s
Whole answer
29 s

Capacity

1Mtokens

Context window. The most one request can hold, as the maker states it.

Max output
128K
Reads
Text

Quality

44.8of 100

Intelligence Index. One composite score across independent evaluations. Run at max effort.

GDPval knowledge work
1,658 Elo
Terminal-Bench 4.0
41.9%
Epoch Capabilities Index
156

Hallucination

38.9%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
32.3%

Where you can get it

10of 19 routes

Routes offering it. Of the clouds, gateways and coding products GILD tracks, those offering it today.

Open weights
Yes
Licence
GLM-5.3 License
Every route and price

Figures from Artificial Analysis, Z.ai, Epoch AI and GILD's route matrix, read Oct 26 to 29, 2026. Each measure's definition and source open under .

Every value with its benchmark, run and source

GLM-5.3's result on each axis, with the benchmark, the setting and run, who reported it, the source and the date
AxisBenchmark and settingGLM-5.3RunSourceDate
Agentic codingTerminal-Bench 4.0Pass@1 averaged over 3 runs, mini-swe-agent harness38.9%GLM 5.3Effort: not published. Harness: mini-swe-agent.Vals.aiOct 26, 2026
CodeSciCodeSubproblem accuracy, pass@1, highest effort run59%GLM-5.3 (Max)Effort: max. Harness: none.Artificial AnalysisOct 28, 2026
MathFrontierMath Tiers 1-3Accuracy, pass@1, highest effort run68.8%Effort: max. Harness: none.Epoch AIAug 25, 2026
ScienceGPQA DiamondAccuracy, pass@1, highest effort run90.9%Effort: max. Harness: none.Epoch AIAug 24, 2026
Hard reasoningHumanity's Last ExamAccuracy, text-only questions, no tools42.3%GLM-5.3 (Max)Effort: max. Harness: none.Artificial AnalysisOct 28, 2026
Tool useAutomationBench-AAScore, Artificial Analysis run62.2%GLM-5.3 (Max)Effort: max. Harness: Artificial Analysis AutomationBench harness.Artificial AnalysisOct 28, 2026
Computer useOSWorld 2.1Partial score, full 108-task set, v2.1 releaseGLM-5.3 reads text only.
Long contextAA-LCR v1.1Accuracy, Artificial Analysis run79.7%GLM-5.3 (Max)Effort: max. Harness: none.Artificial AnalysisOct 28, 2026
MultimodalMMMU-ProOverall accuracy, no toolsGLM-5.3 reads text only.
FactualityAA-Omniscience AccuracyAccuracy, Artificial Analysis run32.3%Hallucination rate 38.9% in the same run (lower is better)GLM-5.3 (Max)Effort: max. Harness: none.Artificial AnalysisOct 28, 2026
Answers in fullSpeechMap% Complete over 2,120 contested requests, reasoning-on entry. SpeechMap counted 25.1% of requests denied and 3.3% evaded.71.5%0.1% of requests failed at the provider and count against itEffort: reasoning on. Harness: none.SpeechMap.AIOct 28, 2026
Instruction followingMultiChallengeAccuracy, Scale AI runNot yet published by Z.ai or any independent evaluator, checked Nov 2, 2026

Price and speed

  • GLM-5.3 lists at $1.40 per million input tokens and $4.40 per million output tokens. Z.ai pricing, Oct 28, 2026.
  • GLM-5.3, at max effort, writes 85.7 output tokens per second on Z AI's API, and its first token arrives 2.7 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.

The result of every model GILD has benchmark results for, on each of the 12 axes. A vendor-reported value is marked. A model's run notes open under its row from its name, each with the axes it covers.
ModelAgentic codingCodeMathScienceHard reasoningTool useComputer useLong contextMultimodalFactualityAnswers in fullInstructions
GLM-5.338.9%59%68.8%90.9%42.3%62.2%Not yet published79.7%Not yet published32.3%71.5%Not yet published
GLM-5.3-Flash37.4%51.6%55.8%90.2%39.9%60.4%59.1%Reported by Z.aiOSWorld 2.080%86%Run by Vals.aiMMMU-Pro28.2%65.4%Not yet published
GLM-5.21%Run by Artificial AnalysisTerminal-Bench 4.051.2%59.2%Not yet published41.1%28.4%Not yet published78.3%Not yet published34.2%Run by Epoch AISimpleQA VerifiedNot yet published73.3%Run by Artificial AnalysisIFBench
Claude Haiku 5.536.4%55%75.1%89.6%44.4%35.4%72.4%Reported by AnthropicOSWorld 2.182.7%Not yet published34.7%78.8%67.7%
Claude Sonnet 5.564.1%61%88.8%95.6%55%71.8%80.1%Reported by Anthropic82.7%Not yet published51.5%81.6%Not yet published
Claude Opus 5.565.2%66.9%91.2%90.6%61.4%69.5%81.8%Reported by Anthropic84.7%87.7%65.5%82.8%Not yet published
Claude Fable 5.158.1%63.1%90.2%93.4%Run by Vals.ai59.1%59.4%80.7%Reported by Anthropic85.3%86.3%Run by Moonshot AI68.4%72.4%Not yet published
Claude Opus 553.5%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 510.6%54.3%65.6%80.3%41.3%36.5%57%Reported by Anthropic82%77.3%40.1%Not yet publishedNot yet published
Claude Fable 541.4%61%87%85.9%55.5%54.1%Not yet published82.3%Not yet published65.4%64.8%63.5%Run by Artificial AnalysisIFBench
Claude Opus 4.823.2%54.4%80%91%48.7%45.6%54.8%Run by OSWorld teamOSWorld 2.077.7%Not yet published48.8%67.4%62.2%Run by Artificial AnalysisIFBench
Claude Opus 4.7Not yet published54.5%70.2%86.4%42.3%Not yet published48.9%Run by OSWorld teamOSWorld 2.078.7%78.8%48.9%70.2%58.6%Run by Artificial AnalysisIFBench
Claude Sonnet 4.63%Run by Artificial AnalysisTerminal-Bench 4.050.1%71.1%Run by Epoch AIOTIS Mock AIME 2024-202578.8%33.6%20.1%41.5%Run by OSWorld teamOSWorld 2.080%73.3%40.9%35.8%56.6%Run by Artificial AnalysisIFBench
Claude Opus 4.6Not yet publishedNot yet published66%88.4%39.9%Not yet publishedNot yet published78%75.4%47%59.9%37.2%
Claude Opus 4.5Not yet publishedNot yet published34.4%86%30.1%Not yet publishedNot yet published77.3%74%46.6%57.5%59%
Claude Haiku 4.5Not yet published42.2%66.7%Run by Epoch AIOTIS Mock AIME 2024-202571.2%10.4%3.2%Not yet published74.3%58.6%18%24.7%50.5%
Claude Sonnet 4.5Not yet published45.7%23.9%82.3%17.8%14.1%Not yet published72.3%68.7%32.9%31.4%55.3%
GPT-6.1 Terra49.5%55.1%90.9%94.3%46.2%60.2%74.2%Reported by OpenAIOSWorld 2.182.7%84.7%47.6%Not yet published74.2%
GPT-6.1 Sol55.1%54.2%93.7%95.4%52.9%64.9%78%Reported by OpenAIOSWorld 2.183%86%61.8%69.5%82%
GPT-6 Luna13.6%54.6%78.9%90.5%38.5%53.2%48.9%Run by AnthropicOSWorld 2.183.3%79.7%39.6%63.4%Not yet published
GPT-6 Astra59.6%56.5%93.7%95.8%54.7%68.5%75.8%Run by Meta80.7%86.9%61.6%68.2%Not yet published
GPT-5.6 Sol37.9%57.1%89.1%93.5%49.5%60.1%62.7%Run by OSWorld teamOSWorld 2.084%83.4%69.7%Run by Epoch AISimpleQA VerifiedNot yet published72.7%Run by Artificial AnalysisIFBench
GPT-5.6 Terra22.7%55%86%93.3%42.9%59.6%Not yet published83%80.7%42.3%Not yet published71.2%Run by Artificial AnalysisIFBench
GPT-5.6 Luna11.6%53.6%82.1%91.6%39.5%50.2%Not yet published83.7%78.6%41%Run by Epoch AISimpleQA VerifiedNot yet publishedNot yet published
GPT-5.514.6%Run by Artificial AnalysisTerminal-Bench 4.055.8%85.3%93.5%Run by Artificial Analysis45.8%47.3%49.5%Run by OSWorld teamOSWorld 2.084.3%79.9%63%Run by Epoch AISimpleQA VerifiedNot yet published75.9%Run by Artificial AnalysisIFBench
GPT-5.4Not yet publishedNot yet published78.6%93.3%43.7%Not yet publishedNot yet published82%78.4%Not yet publishedNot yet published73.9%Run by Artificial AnalysisIFBench
gpt-oss-120b14.2%Run by Terminal-Bench (via Epoch AI)Terminal-Bench 2.034%88.9%Run by Epoch AIOTIS Mock AIME 2024-202575.8%19.6%0.2%Not yet published52%Not yet published16.8%Reported by OpenAISimpleQA36.3%45.3%
GPT-6 Sol44.4%57.6%89.8%94.3%47.9%61.6%64.4%Reported by OpenAIOSWorld 2.083.7%82.9%54.5%64%Not yet published
GPT-5.3-CodexNot yet publishedNot yet publishedNot yet published91.5%Run by Artificial Analysis42.5%Not yet publishedNot yet published83.3%78.5%Not yet publishedNot yet published75.4%Run by Artificial AnalysisIFBench
Gemini 4 Argon57.6%61.8%86%96.4%57.1%77.5%69.2%Reported by GoogleOSWorld 2.079.7%Not yet published48.3%87%78.7%
Gemini 3.8 Flash19.7%56.6%68.4%95.4%47.8%59.9%59%Reported by GoogleOSWorld 2.081.3%85.6%50.5%86.1%Not yet published
Gemma 4 31BNot yet published45.5%Not yet published85.7%Run by Artificial AnalysisGPQA Diamond23.6%4.9%Not yet published69.7%73.4%10.4%Run by Epoch AISimpleQA Verified82.3%75.6%Run by Artificial AnalysisIFBench
Gemini 3.1 Pro Preview2.5%58.7%59.6%94.4%47%35.4%Not yet published82%82.4%54.9%59.9%71.4%
Gemini 3.6 Flash7.1%Run by Artificial AnalysisTerminal-Bench 4.053.4%58.9%94.1%40.8%53%83%Reported by GoogleOSWorld-Verified80%83.2%66.2%Run by Epoch AISimpleQA Verified87.2%Not yet published
DeepSeek V4.1 Flash31.8%55.9%71.2%93.2%43.3%66.6%69.3%Run by Moonshot AIOSWorld 2.182.7%80.6%39.6%Not yet published74.9%
DeepSeek V4 Pro14.1%51%64.6%91.7%41%56.7%Not yet published80.3%Not yet published45.2%72%Not yet published
Kimi K3.1 Pro63.6%60.8%Not yet published94.2%Reported by Moonshot AI52.5%73.3%79.6%Reported by Moonshot AIOSWorld 2.186.3%83.9%48.9%Not yet publishedNot yet published
Kimi K317.2%59.5%72.2%93.1%46.9%58.3%Not yet published88.7%80.5%50.6%Run by Epoch AISimpleQA Verified65.9%Not yet published
Kimi K2.7 Code1%Run by Artificial AnalysisTerminal-Bench 4.047.8%54%87.9%35%24.5%Not yet published79.3%Not yet published36.5%Run by Epoch AISimpleQA VerifiedNot yet published63.1%Run by Artificial AnalysisIFBench
Mistral Large 424.7%Run by Artificial AnalysisTerminal-Bench 4.0Not yet publishedNot yet publishedNot yet publishedNot yet published57.8%Not yet publishedNot yet publishedNot yet published26%Not yet publishedNot yet published
Mistral Medium 3.50%Run by Artificial AnalysisTerminal-Bench 4.040.2%Not yet published74.8%Run by Artificial AnalysisGPQA Diamond13.8%6.3%Not yet published69.3%64.9%23%70.5%68.8%Run by Artificial AnalysisIFBench
Grok 4.728.8%57.4%53%92.7%43.1%65.6%Not yet published76.7%Not yet published42.7%64.1%Not yet published
Grok 4.617.2%56.5%66%93.2%42.9%66.7%Not yet published80.3%Not yet published48.9%Run by Epoch AISimpleQA Verified83.6%Not yet published
Grok 4.58.6%55%57.2%93.4%42.7%57.9%Not yet published79.3%80.4%48.3%Run by Epoch AISimpleQA Verified93.1%Not yet published
MiniMax M3.1 Flash25.3%53.4%Not yet publishedNot yet published48%72.5%61.7%Reported by MiniMaxOSWorld 2.079.7%79.1%45.1%Not yet publishedNot yet published
Mercury 33%Not yet publishedNot yet publishedNot yet publishedNot yet publishedNot yet publishedNot yet publishedNot yet publishedNot yet publishedNot yet publishedNot yet publishedNot yet published
Muse Spark Open6.6%58.4%69.8%88.6%43.9%49.7%80.4%Reported by MetaOSWorld-Verified78.3%80.9%42%Not yet published74.2%
Muse Wonder49.5%60.3%82.1%Not yet published50.1%68.1%72.6%Reported by Meta80.7%Not yet published38%42.7%Not yet published
Muse Spark 1.310.6%58.8%74%93.5%Run by Artificial AnalysisGPQA Diamond48.7%57.9%69.6%83%82%38%25.8%Not yet published
Llama 4 ScoutNot yet published21.3%7.8%Run by Epoch AIOTIS Mock AIME 2024-202551.8%3.8%0.2%Not yet published27.7%52.9%Not yet published70.1%39.5%Run by Artificial AnalysisIFBench
Llama 4 MaverickNot yet published31.7%20.6%Run by Epoch AIOTIS Mock AIME 2024-202567%4.9%0.2%Not yet published50%62.1%Not yet published58.3%43%Run by Artificial AnalysisIFBench
Qwen3.8 27B5.6%Run by Artificial AnalysisTerminal-Bench 4.046.6%Not yet published90.5%Run by Artificial AnalysisGPQA Diamond33.9%48.2%84.3%Reported by AlibabaOSWorld-Verified82%76.3%17.3%Not yet published79.5%Reported by AlibabaIFBench
Qwen3.8 Max38.9%52.1%65.6%92.3%43.1%56.2%Not yet published80.3%82.8%29.5%65.3%Not yet published
MiMo-V2.6-Pro31.3%60.9%Not yet publishedNot yet published49.4%58.6%82%Reported by XiaomiOSWorld-Verified86.3%Not yet published34.8%66.5%Not yet published
MiMo-V2.6-Flash24.2%51.3%Not yet publishedNot yet published35.1%64.1%80.8%Reported by XiaomiOSWorld-Verified74.3%73.1%27.2%66.9%Not yet published
Ling 3.1 Flash32.8%Run by Artificial AnalysisTerminal-Bench 4.056.8%Not yet publishedNot yet published43.5%67.5%Not yet published82.3%Not yet published26.5%Not yet publishedNot yet published
Step 5 Preview31.8%58.9%Not yet published93.5%Reported by StepFunGPQA Diamond46.5%51%Not yet published88.3%76.4%36.4%59.7%Not yet published

Agentic codingTerminal-Bench 4.0

  1. Claude Opus 5.565.2%
  2. Claude Sonnet 5.564.1%
  3. Kimi K3.1 Pro63.6%
  4. GPT-6 Astra59.6%
  5. Claude Fable 5.158.1%
  6. Gemini 4 Argon57.6%
  7. GPT-6.1 Sol55.1%
  8. Claude Opus 553.5%
  9. GPT-6.1 Terra49.5%
  10. Muse Wonder49.5%
  11. GPT-6 Sol44.4%
  12. Claude Fable 541.4%
  13. GLM-5.338.9%
  14. Qwen3.8 Max38.9%
  15. GPT-5.6 Sol37.9%
  16. GLM-5.3-Flash37.4%
  17. Claude Haiku 5.536.4%
  18. DeepSeek V4.1 Flash31.8%
  19. Step 5 Preview31.8%
  20. MiMo-V2.6-Pro31.3%
  21. Grok 4.728.8%
  22. MiniMax M3.1 Flash25.3%
  23. MiMo-V2.6-Flash24.2%
  24. Claude Opus 4.823.2%
  25. GPT-5.6 Terra22.7%
  26. Gemini 3.8 Flash19.7%
  27. Kimi K317.2%
  28. Grok 4.617.2%
  29. DeepSeek V4 Pro14.1%
  30. GPT-6 Luna13.6%
  31. GPT-5.6 Luna11.6%
  32. Claude Sonnet 510.6%
  33. Muse Spark 1.310.6%
  34. Grok 4.58.6%
  35. Muse Spark Open6.6%
  36. Mercury 33%
  37. Gemini 3.1 Pro Preview2.5%
  38. Ling 3.1 Flash32.8%Artificial Analysis's run, Terminal-Bench 4.0
  39. Mistral Large 424.7%Artificial Analysis's run, Terminal-Bench 4.0
  40. GPT-5.514.6%Artificial Analysis's run, Terminal-Bench 4.0
  41. gpt-oss-120b14.2%Terminal-Bench's run, Terminal-Bench 2.0
  42. Gemini 3.6 Flash7.1%Artificial Analysis's run, Terminal-Bench 4.0
  43. Qwen3.8 27B5.6%Artificial Analysis's run, Terminal-Bench 4.0
  44. Claude Sonnet 4.63%Artificial Analysis's run, Terminal-Bench 4.0
  45. GLM-5.21%Artificial Analysis's run, Terminal-Bench 4.0
  46. Kimi K2.7 Code1%Artificial Analysis's run, Terminal-Bench 4.0
  47. 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

  1. Claude Opus 5.566.9%
  2. Claude Fable 5.163.1%
  3. Gemini 4 Argon61.8%
  4. Claude Sonnet 5.561%
  5. Claude Fable 561%
  6. MiMo-V2.6-Pro60.9%
  7. Kimi K3.1 Pro60.8%
  8. Muse Wonder60.3%
  9. Kimi K359.5%
  10. GLM-5.359%
  11. Step 5 Preview58.9%
  12. Muse Spark 1.358.8%
  13. Gemini 3.1 Pro Preview58.7%
  14. Muse Spark Open58.4%
  15. GPT-6 Sol57.6%
  16. Grok 4.757.4%
  17. GPT-5.6 Sol57.1%
  18. Ling 3.1 Flash56.8%
  19. Gemini 3.8 Flash56.6%
  20. GPT-6 Astra56.5%
  21. Grok 4.656.5%
  22. Claude Opus 556.4%
  23. DeepSeek V4.1 Flash55.9%
  24. GPT-5.555.8%
  25. GPT-6.1 Terra55.1%
  26. Claude Haiku 5.555%
  27. GPT-5.6 Terra55%
  28. Grok 4.555%
  29. GPT-6 Luna54.6%
  30. Claude Opus 4.754.5%
  31. Claude Opus 4.854.4%
  32. Claude Sonnet 554.3%
  33. GPT-6.1 Sol54.2%
  34. GPT-5.6 Luna53.6%
  35. Gemini 3.6 Flash53.4%
  36. MiniMax M3.1 Flash53.4%
  37. Qwen3.8 Max52.1%
  38. GLM-5.3-Flash51.6%
  39. MiMo-V2.6-Flash51.3%
  40. GLM-5.251.2%
  41. DeepSeek V4 Pro51%
  42. Claude Sonnet 4.650.1%
  43. Kimi K2.7 Code47.8%
  44. Qwen3.8 27B46.6%
  45. Claude Sonnet 4.545.7%
  46. Gemma 4 31B45.5%
  47. Claude Haiku 4.542.2%
  48. Mistral Medium 3.540.2%
  49. gpt-oss-120b34%
  50. Llama 4 Maverick31.7%
  51. Llama 4 Scout21.3%

The other models in the grid have no result on SciCode yet.

MathFrontierMath Tiers 1-3

  1. GPT-6.1 Sol93.7%
  2. GPT-6 Astra93.7%
  3. Claude Opus 5.591.2%
  4. GPT-6.1 Terra90.9%
  5. Claude Fable 5.190.2%
  6. GPT-6 Sol89.8%
  7. GPT-5.6 Sol89.1%
  8. Claude Sonnet 5.588.8%
  9. Claude Fable 587%
  10. GPT-5.6 Terra86%
  11. Gemini 4 Argon86%
  12. Claude Opus 585.6%
  13. GPT-5.585.3%
  14. GPT-5.6 Luna82.1%
  15. Muse Wonder82.1%
  16. Claude Opus 4.880%
  17. GPT-6 Luna78.9%
  18. GPT-5.478.6%
  19. Claude Haiku 5.575.1%
  20. Muse Spark 1.374%
  21. Kimi K372.2%
  22. DeepSeek V4.1 Flash71.2%
  23. Claude Opus 4.770.2%
  24. Muse Spark Open69.8%
  25. GLM-5.368.8%
  26. Gemini 3.8 Flash68.4%
  27. Claude Opus 4.666%
  28. Grok 4.666%
  29. Claude Sonnet 565.6%
  30. Qwen3.8 Max65.6%
  31. DeepSeek V4 Pro64.6%
  32. Gemini 3.1 Pro Preview59.6%
  33. GLM-5.259.2%
  34. Gemini 3.6 Flash58.9%
  35. Grok 4.557.2%
  36. GLM-5.3-Flash55.8%
  37. Kimi K2.7 Code54%
  38. Grok 4.753%
  39. Claude Opus 4.534.4%
  40. Claude Sonnet 4.523.9%
  41. gpt-oss-120b88.9%Epoch AI's run, OTIS Mock AIME 2024-2025
  42. Claude Sonnet 4.671.1%Epoch AI's run, OTIS Mock AIME 2024-2025
  43. Claude Haiku 4.566.7%Epoch AI's run, OTIS Mock AIME 2024-2025
  44. Llama 4 Maverick20.6%Epoch AI's run, OTIS Mock AIME 2024-2025
  45. 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

  1. Gemini 4 Argon96.4%
  2. GPT-6 Astra95.8%
  3. Claude Sonnet 5.595.6%
  4. GPT-6.1 Sol95.4%
  5. Gemini 3.8 Flash95.4%
  6. Gemini 3.1 Pro Preview94.4%
  7. GPT-6.1 Terra94.3%
  8. GPT-6 Sol94.3%
  9. Gemini 3.6 Flash94.1%
  10. Claude Opus 593.9%
  11. GPT-5.6 Sol93.5%
  12. Grok 4.593.4%
  13. GPT-5.6 Terra93.3%
  14. GPT-5.493.3%
  15. DeepSeek V4.1 Flash93.2%
  16. Grok 4.693.2%
  17. Kimi K393.1%
  18. Grok 4.792.7%
  19. Qwen3.8 Max92.3%
  20. DeepSeek V4 Pro91.7%
  21. GPT-5.6 Luna91.6%
  22. Claude Opus 4.891%
  23. GLM-5.390.9%
  24. Claude Opus 5.590.6%
  25. GPT-6 Luna90.5%
  26. GLM-5.3-Flash90.2%
  27. Claude Haiku 5.589.6%
  28. Muse Spark Open88.6%
  29. Claude Opus 4.688.4%
  30. Kimi K2.7 Code87.9%
  31. Claude Opus 4.786.4%
  32. Claude Opus 4.586%
  33. Claude Fable 585.9%
  34. Claude Sonnet 4.582.3%
  35. Claude Sonnet 580.3%
  36. Claude Sonnet 4.678.8%
  37. gpt-oss-120b75.8%
  38. Claude Haiku 4.571.2%
  39. Llama 4 Maverick67%
  40. Llama 4 Scout51.8%
  41. Kimi K3.1 Pro94.2%Moonshot AI's own figure
  42. GPT-5.593.5%Artificial Analysis's run
  43. Muse Spark 1.393.5%Artificial Analysis's run, GPQA Diamond
  44. Step 5 Preview93.5%StepFun's own figure, GPQA Diamond
  45. Claude Fable 5.193.4%Vals.ai's run
  46. GPT-5.3-Codex91.5%Artificial Analysis's run
  47. Qwen3.8 27B90.5%Artificial Analysis's run, GPQA Diamond
  48. Gemma 4 31B85.7%Artificial Analysis's run, GPQA Diamond
  49. 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

  1. Claude Opus 5.561.4%
  2. Claude Fable 5.159.1%
  3. Gemini 4 Argon57.1%
  4. Claude Fable 555.5%
  5. Claude Sonnet 5.555%
  6. Claude Opus 554.9%
  7. GPT-6 Astra54.7%
  8. GPT-6.1 Sol52.9%
  9. Kimi K3.1 Pro52.5%
  10. Muse Wonder50.1%
  11. GPT-5.6 Sol49.5%
  12. MiMo-V2.6-Pro49.4%
  13. Claude Opus 4.848.7%
  14. Muse Spark 1.348.7%
  15. MiniMax M3.1 Flash48%
  16. GPT-6 Sol47.9%
  17. Gemini 3.8 Flash47.8%
  18. Gemini 3.1 Pro Preview47%
  19. Kimi K346.9%
  20. Step 5 Preview46.5%
  21. GPT-6.1 Terra46.2%
  22. GPT-5.545.8%
  23. Claude Haiku 5.544.4%
  24. Muse Spark Open43.9%
  25. GPT-5.443.7%
  26. Ling 3.1 Flash43.5%
  27. DeepSeek V4.1 Flash43.3%
  28. Grok 4.743.1%
  29. Qwen3.8 Max43.1%
  30. GPT-5.6 Terra42.9%
  31. Grok 4.642.9%
  32. Grok 4.542.7%
  33. GPT-5.3-Codex42.5%
  34. GLM-5.342.3%
  35. Claude Opus 4.742.3%
  36. Claude Sonnet 541.3%
  37. GLM-5.241.1%
  38. DeepSeek V4 Pro41%
  39. Gemini 3.6 Flash40.8%
  40. GLM-5.3-Flash39.9%
  41. Claude Opus 4.639.9%
  42. GPT-5.6 Luna39.5%
  43. GPT-6 Luna38.5%
  44. MiMo-V2.6-Flash35.1%
  45. Kimi K2.7 Code35%
  46. Qwen3.8 27B33.9%
  47. Claude Sonnet 4.633.6%
  48. Claude Opus 4.530.1%
  49. Gemma 4 31B23.6%
  50. gpt-oss-120b19.6%
  51. Claude Sonnet 4.517.8%
  52. Mistral Medium 3.513.8%
  53. Claude Haiku 4.510.4%
  54. Llama 4 Maverick4.9%
  55. Llama 4 Scout3.8%

The other models in the grid have no result on Humanity's Last Exam yet.

Tool useAutomationBench-AA

  1. Gemini 4 Argon77.5%
  2. Kimi K3.1 Pro73.3%
  3. MiniMax M3.1 Flash72.5%
  4. Claude Sonnet 5.571.8%
  5. Claude Opus 5.569.5%
  6. GPT-6 Astra68.5%
  7. Muse Wonder68.1%
  8. Ling 3.1 Flash67.5%
  9. Grok 4.666.7%
  10. DeepSeek V4.1 Flash66.6%
  11. Grok 4.765.6%
  12. GPT-6.1 Sol64.9%
  13. MiMo-V2.6-Flash64.1%
  14. GLM-5.362.2%
  15. GPT-6 Sol61.6%
  16. GLM-5.3-Flash60.4%
  17. GPT-6.1 Terra60.2%
  18. GPT-5.6 Sol60.1%
  19. Gemini 3.8 Flash59.9%
  20. GPT-5.6 Terra59.6%
  21. Claude Fable 5.159.4%
  22. MiMo-V2.6-Pro58.6%
  23. Kimi K358.3%
  24. Grok 4.557.9%
  25. Muse Spark 1.357.9%
  26. Mistral Large 457.8%
  27. DeepSeek V4 Pro56.7%
  28. Claude Opus 556.6%
  29. Qwen3.8 Max56.2%
  30. Claude Fable 554.1%
  31. GPT-6 Luna53.2%
  32. Gemini 3.6 Flash53%
  33. Step 5 Preview51%
  34. GPT-5.6 Luna50.2%
  35. Muse Spark Open49.7%
  36. Qwen3.8 27B48.2%
  37. GPT-5.547.3%
  38. Claude Opus 4.845.6%
  39. Claude Sonnet 536.5%
  40. Claude Haiku 5.535.4%
  41. Gemini 3.1 Pro Preview35.4%
  42. GLM-5.228.4%
  43. Kimi K2.7 Code24.5%
  44. Claude Sonnet 4.620.1%
  45. Claude Sonnet 4.514.1%
  46. Mistral Medium 3.56.3%
  47. Gemma 4 31B4.9%
  48. Claude Haiku 4.53.2%
  49. gpt-oss-120b0.2%
  50. Llama 4 Scout0.2%
  51. Llama 4 Maverick0.2%

The other models in the grid have no result on AutomationBench-AA yet.

Computer useOSWorld 2.1

  1. Claude Opus 577.7%
  2. Muse Spark 1.369.6%
  3. Qwen3.8 27B84.3%Alibaba's own figure, OSWorld-Verified
  4. Gemini 3.6 Flash83%Google's own figure, OSWorld-Verified
  5. MiMo-V2.6-Pro82%Xiaomi's own figure, OSWorld-Verified
  6. Claude Opus 5.581.8%Anthropic's own figure
  7. MiMo-V2.6-Flash80.8%Xiaomi's own figure, OSWorld-Verified
  8. Claude Fable 5.180.7%Anthropic's own figure
  9. Muse Spark Open80.4%Meta's own figure, OSWorld-Verified
  10. Claude Sonnet 5.580.1%Anthropic's own figure
  11. Kimi K3.1 Pro79.6%Moonshot AI's own figure, OSWorld 2.1
  12. GPT-6.1 Sol78%OpenAI's own figure, OSWorld 2.1
  13. GPT-6 Astra75.8%Meta's run
  14. GPT-6.1 Terra74.2%OpenAI's own figure, OSWorld 2.1
  15. Muse Wonder72.6%Meta's own figure
  16. Claude Haiku 5.572.4%Anthropic's own figure, OSWorld 2.1
  17. DeepSeek V4.1 Flash69.3%Moonshot AI's run, OSWorld 2.1
  18. Gemini 4 Argon69.2%Google's own figure, OSWorld 2.0
  19. GPT-6 Sol64.4%OpenAI's own figure, OSWorld 2.0
  20. GPT-5.6 Sol62.7%OSWorld team's run, OSWorld 2.0
  21. MiniMax M3.1 Flash61.7%MiniMax's own figure, OSWorld 2.0
  22. GLM-5.3-Flash59.1%Z.ai's own figure, OSWorld 2.0
  23. Gemini 3.8 Flash59%Google's own figure, OSWorld 2.0
  24. Claude Sonnet 557%Anthropic's own figure
  25. Claude Opus 4.854.8%OSWorld team's run, OSWorld 2.0
  26. GPT-5.549.5%OSWorld team's run, OSWorld 2.0
  27. Claude Opus 4.748.9%OSWorld team's run, OSWorld 2.0
  28. GPT-6 Luna48.9%Anthropic's run, OSWorld 2.1
  29. 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

  1. Kimi K388.7%
  2. Step 5 Preview88.3%
  3. Kimi K3.1 Pro86.3%
  4. MiMo-V2.6-Pro86.3%
  5. Claude Fable 5.185.3%
  6. Claude Opus 5.584.7%
  7. GPT-5.584.3%
  8. GPT-5.6 Sol84%
  9. GPT-5.6 Luna83.7%
  10. GPT-6 Sol83.7%
  11. GPT-6 Luna83.3%
  12. GPT-5.3-Codex83.3%
  13. GPT-6.1 Sol83%
  14. GPT-5.6 Terra83%
  15. Muse Spark 1.383%
  16. Claude Haiku 5.582.7%
  17. Claude Sonnet 5.582.7%
  18. GPT-6.1 Terra82.7%
  19. DeepSeek V4.1 Flash82.7%
  20. Claude Fable 582.3%
  21. Ling 3.1 Flash82.3%
  22. Claude Sonnet 582%
  23. GPT-5.482%
  24. Gemini 3.1 Pro Preview82%
  25. Qwen3.8 27B82%
  26. Gemini 3.8 Flash81.3%
  27. GPT-6 Astra80.7%
  28. Muse Wonder80.7%
  29. DeepSeek V4 Pro80.3%
  30. Grok 4.680.3%
  31. Qwen3.8 Max80.3%
  32. GLM-5.3-Flash80%
  33. Claude Sonnet 4.680%
  34. Gemini 3.6 Flash80%
  35. GLM-5.379.7%
  36. Gemini 4 Argon79.7%
  37. MiniMax M3.1 Flash79.7%
  38. Claude Opus 579.3%
  39. Kimi K2.7 Code79.3%
  40. Grok 4.579.3%
  41. Claude Opus 4.778.7%
  42. GLM-5.278.3%
  43. Muse Spark Open78.3%
  44. Claude Opus 4.678%
  45. Claude Opus 4.877.7%
  46. Claude Opus 4.577.3%
  47. Grok 4.776.7%
  48. Claude Haiku 4.574.3%
  49. MiMo-V2.6-Flash74.3%
  50. Claude Sonnet 4.572.3%
  51. Gemma 4 31B69.7%
  52. Mistral Medium 3.569.3%
  53. gpt-oss-120b52%
  54. Llama 4 Maverick50%
  55. Llama 4 Scout27.7%

The other models in the grid have no result on AA-LCR v1.1 yet.

MultimodalMMMU-Pro

  1. Claude Opus 5.587.7%
  2. GPT-6 Astra86.9%
  3. GPT-6.1 Sol86%
  4. Gemini 3.8 Flash85.6%
  5. Claude Opus 584.7%
  6. GPT-6.1 Terra84.7%
  7. Kimi K3.1 Pro83.9%
  8. GPT-5.6 Sol83.4%
  9. Gemini 3.6 Flash83.2%
  10. GPT-6 Sol82.9%
  11. Qwen3.8 Max82.8%
  12. Gemini 3.1 Pro Preview82.4%
  13. Muse Spark 1.382%
  14. Muse Spark Open80.9%
  15. GPT-5.6 Terra80.7%
  16. DeepSeek V4.1 Flash80.6%
  17. Kimi K380.5%
  18. Grok 4.580.4%
  19. GPT-5.579.9%
  20. GPT-6 Luna79.7%
  21. MiniMax M3.1 Flash79.1%
  22. Claude Opus 4.778.8%
  23. GPT-5.6 Luna78.6%
  24. GPT-5.3-Codex78.5%
  25. GPT-5.478.4%
  26. Claude Sonnet 577.3%
  27. Step 5 Preview76.4%
  28. Qwen3.8 27B76.3%
  29. Claude Opus 4.675.4%
  30. Claude Opus 4.574%
  31. Gemma 4 31B73.4%
  32. Claude Sonnet 4.673.3%
  33. MiMo-V2.6-Flash73.1%
  34. Claude Sonnet 4.568.7%
  35. Mistral Medium 3.564.9%
  36. Llama 4 Maverick62.1%
  37. Claude Haiku 4.558.6%
  38. Llama 4 Scout52.9%
  39. Claude Fable 5.186.3%Moonshot AI's run
  40. 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

  1. Claude Fable 5.168.4%
  2. Claude Opus 5.565.5%
  3. Claude Fable 565.4%
  4. GPT-6.1 Sol61.8%
  5. GPT-6 Astra61.6%
  6. Claude Opus 560.9%
  7. Gemini 3.1 Pro Preview54.9%
  8. GPT-6 Sol54.5%
  9. Claude Sonnet 5.551.5%
  10. Gemini 3.8 Flash50.5%
  11. Claude Opus 4.748.9%
  12. Kimi K3.1 Pro48.9%
  13. Claude Opus 4.848.8%
  14. Gemini 4 Argon48.3%
  15. GPT-6.1 Terra47.6%
  16. Claude Opus 4.647%
  17. Claude Opus 4.546.6%
  18. DeepSeek V4 Pro45.2%
  19. MiniMax M3.1 Flash45.1%
  20. Grok 4.742.7%
  21. GPT-5.6 Terra42.3%
  22. Muse Spark Open42%
  23. Claude Sonnet 4.640.9%
  24. Claude Sonnet 540.1%
  25. GPT-6 Luna39.6%
  26. DeepSeek V4.1 Flash39.6%
  27. Muse Wonder38%
  28. Muse Spark 1.338%
  29. Step 5 Preview36.4%
  30. MiMo-V2.6-Pro34.8%
  31. Claude Haiku 5.534.7%
  32. Claude Sonnet 4.532.9%
  33. GLM-5.332.3%
  34. Qwen3.8 Max29.5%
  35. GLM-5.3-Flash28.2%
  36. MiMo-V2.6-Flash27.2%
  37. Ling 3.1 Flash26.5%
  38. Mistral Large 426%
  39. Mistral Medium 3.523%
  40. Claude Haiku 4.518%
  41. Qwen3.8 27B17.3%
  42. GPT-5.6 Sol69.7%Epoch AI's run, SimpleQA Verified
  43. Gemini 3.6 Flash66.2%Epoch AI's run, SimpleQA Verified
  44. GPT-5.563%Epoch AI's run, SimpleQA Verified
  45. Kimi K350.6%Epoch AI's run, SimpleQA Verified
  46. Grok 4.648.9%Epoch AI's run, SimpleQA Verified
  47. Grok 4.548.3%Epoch AI's run, SimpleQA Verified
  48. GPT-5.6 Luna41%Epoch AI's run, SimpleQA Verified
  49. Kimi K2.7 Code36.5%Epoch AI's run, SimpleQA Verified
  50. GLM-5.234.2%Epoch AI's run, SimpleQA Verified
  51. gpt-oss-120b16.8%OpenAI's own figure, SimpleQA
  52. 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

  1. Grok 4.593.1%
  2. Gemini 3.6 Flash87.2%
  3. Gemini 4 Argon87%
  4. Gemini 3.8 Flash86.1%
  5. Grok 4.683.6%
  6. Claude Opus 5.582.8%
  7. Gemma 4 31B82.3%
  8. Claude Sonnet 5.581.6%
  9. Claude Haiku 5.578.8%
  10. Claude Opus 573.7%
  11. Claude Fable 5.172.4%
  12. DeepSeek V4 Pro72%
  13. GLM-5.371.5%
  14. Mistral Medium 3.570.5%
  15. Claude Opus 4.770.2%
  16. Llama 4 Scout70.1%
  17. GPT-6.1 Sol69.5%
  18. GPT-6 Astra68.2%
  19. Claude Opus 4.867.4%
  20. MiMo-V2.6-Flash66.9%
  21. MiMo-V2.6-Pro66.5%
  22. Kimi K365.9%
  23. GLM-5.3-Flash65.4%
  24. Qwen3.8 Max65.3%
  25. Claude Fable 564.8%
  26. Grok 4.764.1%
  27. GPT-6 Sol64%
  28. GPT-6 Luna63.4%
  29. Claude Opus 4.659.9%
  30. Gemini 3.1 Pro Preview59.9%
  31. Step 5 Preview59.7%
  32. Llama 4 Maverick58.3%
  33. Claude Opus 4.557.5%
  34. Muse Wonder42.7%
  35. gpt-oss-120b36.3%
  36. Claude Sonnet 4.635.8%
  37. Claude Sonnet 4.531.4%
  38. Muse Spark 1.325.8%
  39. Claude Haiku 4.524.7%

The other models in the grid have no result on SpeechMap yet.

Instruction followingMultiChallenge

  1. GPT-6.1 Sol82%
  2. Gemini 4 Argon78.7%
  3. DeepSeek V4.1 Flash74.9%
  4. GPT-6.1 Terra74.2%
  5. Muse Spark Open74.2%
  6. Gemini 3.1 Pro Preview71.4%
  7. Claude Haiku 5.567.7%
  8. Claude Opus 4.559%
  9. Claude Sonnet 4.555.3%
  10. Claude Haiku 4.550.5%
  11. gpt-oss-120b45.3%
  12. Claude Opus 4.637.2%
  13. Qwen3.8 27B79.5%Alibaba's own figure, IFBench
  14. GPT-5.575.9%Artificial Analysis's run, IFBench
  15. Gemma 4 31B75.6%Artificial Analysis's run, IFBench
  16. GPT-5.3-Codex75.4%Artificial Analysis's run, IFBench
  17. GPT-5.473.9%Artificial Analysis's run, IFBench
  18. GLM-5.273.3%Artificial Analysis's run, IFBench
  19. GPT-5.6 Sol72.7%Artificial Analysis's run, IFBench
  20. GPT-5.6 Terra71.2%Artificial Analysis's run, IFBench
  21. Mistral Medium 3.568.8%Artificial Analysis's run, IFBench
  22. Claude Fable 563.5%Artificial Analysis's run, IFBench
  23. Kimi K2.7 Code63.1%Artificial Analysis's run, IFBench
  24. Claude Opus 4.862.2%Artificial Analysis's run, IFBench
  25. Claude Opus 4.758.6%Artificial Analysis's run, IFBench
  26. Claude Sonnet 4.656.6%Artificial Analysis's run, IFBench
  27. Llama 4 Maverick43%Artificial Analysis's run, IFBench
  28. Llama 4 Scout39.5%Artificial Analysis's run, IFBench

The other models in the grid have no result on MultiChallenge yet.

Every measure on record

Cost, speed, reliability, knowledge-work and domain results for GLM-5.3 beyond the twelve chart axes, each with the run it comes from and its publisher. These stay separate measures; none is folded into the chart.

Every measure on record for GLM-5.3: the value, the run it comes from, the publisher and the day it was read
MeasureGLM-5.3RunSourceRead
Specs and access
Context windowThe most tokens one request can hold, as the maker states it. Size alone says nothing about how well the model uses a long input; the Long context axis measures that.1MZ.aiOct 28, 2026
Max outputThe most tokens the model writes in one response.128KZ.aiOct 28, 2026
ReadsThe kinds of input the model accepts.TextArtificial AnalysisOct 27, 2026
LicenceThe terms the weights or the service are offered under.GLM-5.3 LicenseArtificial AnalysisOct 27, 2026
Open weightsWhether the maker publishes the weights for anyone to run.YesArtificial AnalysisOct 27, 2026
Routes offering itOf the 19 clouds, gateways and coding products GILD tracks, how many offer the release today, preview included.10 of 19GILD route matrixOct 29, 2026
Cost
Answer tokens per taskLower is better. Answer tokens per Intelligence Index task, reasoning excluded.22,398GLM-5.3 (Max)Artificial AnalysisOct 27, 2026
Cost per task, cache readsLower is better. The cache-read share of AA's cost per Intelligence Index task.$1.52GLM-5.3 (Max)Artificial AnalysisOct 27, 2026
Cost per task, cache writesLower is better. The cache-write share of AA's cost per Intelligence Index task.$0.16GLM-5.3 (Max)Artificial AnalysisOct 27, 2026
Cost per task, inputLower is better. The input-token share of AA's cost per Intelligence Index task.$1.69GLM-5.3 (Max)Artificial AnalysisOct 27, 2026
Cost per task, outputLower is better. The answer-token share of AA's cost per Intelligence Index task.$0.31GLM-5.3 (Max)Artificial AnalysisOct 27, 2026
Cost per task, reasoningLower is better. The reasoning-token share of AA's cost per Intelligence Index task.$0.21GLM-5.3 (Max)Artificial AnalysisOct 27, 2026
Cost per taskLower is better. What one Intelligence Index task cost AA at list price, input, cache, output and reasoning tokens together.$2.01GLM-5.3 (Max)Artificial AnalysisOct 27, 2026
Cost to run the indexLower is better. What the whole Intelligence Index run cost AA at list price. The runs cost from tens of dollars to about $13,000, so the axis is log from $10 to $100,000.$2,503GLM-5.3 (Max)Artificial AnalysisOct 27, 2026
Output tokens per taskLower is better. Tokens the model wrote per Intelligence Index task, reasoning included: how verbose it is.71,128GLM-5.3 (Max)Artificial AnalysisOct 27, 2026
Reasoning tokens per taskLower is better. Reasoning tokens per Intelligence Index task.48,730GLM-5.3 (Max)Artificial AnalysisOct 27, 2026
Cached inputLower is better. The maker's list price for input read from its prompt cache, per million tokens.$0.26Z.aiOct 28, 2026
Speed
End-to-end time, 100K promptLower is better. Median seconds for a whole response with a 100,000-token prompt.26 sGLM-5.3 (Max)Artificial AnalysisOct 27, 2026
End-to-end response timeLower is better. Seconds AA measures for a whole response on its standard prompt.29 sGLM-5.3 (Max)Artificial AnalysisOct 27, 2026
Time to first answer token, 100K promptLower is better. Median seconds to the first answer token with a 100,000-token prompt.22 sGLM-5.3 (Max)Artificial AnalysisOct 27, 2026
Time to first answer tokenLower is better. Seconds until the first answer token, after any reasoning, on AA's API runs.24 sGLM-5.3 (Max)Artificial AnalysisOct 27, 2026
Output speed, 100K promptMedian output tokens per second when the prompt is about 100,000 tokens long.122 tokens/sGLM-5.3 (Max)Artificial AnalysisOct 27, 2026
Output speedMedian output tokens per second on AA's API runs, with the 5th and 95th percentile when AA prints them.94 tokens/sGLM-5.3 (Max)Artificial AnalysisOct 27, 2026
Time per taskLower is better. Wall-clock seconds per Intelligence Index task. Runs take from about 15 s to about 33 min, so the axis is log from 1 s to 10,000 s.623 sGLM-5.3 (Max)Artificial AnalysisOct 27, 2026
Time to first token, 100K promptLower is better. Median seconds to the first chunk when the prompt is about 100,000 tokens long: long-input latency, separate from window size.5.3 sGLM-5.3 (Max)Artificial AnalysisOct 27, 2026
Time to first tokenLower is better. Median seconds to the first streamed chunk on AA's API runs, with the 5th and 95th percentile when AA prints them. Reasoning models spend this time thinking.2.5 sGLM-5.3 (Max)Artificial AnalysisOct 27, 2026
Reliability
Hallucination rateLower is better. AA-Omniscience hallucination rate shows how often the model answers wrongly when it does not know and should decline.38.9%Max effortArtificial AnalysisOct 28, 2026
Omniscience accuracyShare of AA-Omniscience knowledge questions answered correctly.32.3%Max effortArtificial AnalysisOct 28, 2026
Omniscience indexAA-Omniscience index: correct answers minus wrong answers, declines neutral, -100 to 100.14.3GLM-5.3 (Max)Artificial AnalysisOct 27, 2026
SimpleQA Verified (Epoch)Share of SimpleQA Verified factual questions answered correctly, best scorer, Epoch AI's run. A second factuality source beside AA-Omniscience.41%Max effortEpoch AIAug 28, 2026
Knowledge work
AA-BriefcaseAA-Briefcase overall Elo for long business deliverables, with AA's 95% interval.1,504GLM-5.3 (Max)Artificial AnalysisOct 27, 2026
AnalystAgent (AA run)AA's AnalystAgent score for analyst workflows.38.8%GLM-5.3 (Max)Artificial AnalysisOct 27, 2026
APEX-Agents (maintainers)APEX-Agents pass@1 from the maintainers, as Epoch AI republishes it.56.6%Mercor (via Epoch AI)Oct 26, 2026
GDP-PDF (AA run)Share of GDP-PDF document tasks where every check passes.11.2%GLM-5.3 (Max)Artificial AnalysisOct 27, 2026
GDPval-AAGDPval-AA Elo: AA's run of economically valuable knowledge-work tasks, graded pairwise, with AA's interval.1,658GLM-5.3 (Max)Artificial AnalysisOct 28, 2026
MLCR (AA run)AA's MLCR overall score for long, multi-document reading.17.2%GLM-5.3 (Max)Artificial AnalysisOct 27, 2026
Vending-Bench 2Vending-Bench 2 final balance of a simulated vending business run by the model, as Epoch AI republishes it.$8,164Andon Labs (via Epoch AI)Oct 26, 2026
Capability beyond the chart
AA-LCRAA long-context reasoning accuracy.79.7%GLM-5.3 (Max)Artificial AnalysisOct 27, 2026
ALE-BenchALE-Bench performance rating on long optimization contests, as Epoch AI republishes it.1,317High effortSakana AI (via Epoch AI)Oct 26, 2026
Chess puzzles (Epoch)Share of chess puzzles solved, Epoch AI's run.37%Max effortEpoch AIOct 13, 2026
CritPt (AA run)Share of CritPt research-level physics problems solved in AA's run.19.1%GLM-5.3 (Max)Artificial AnalysisOct 27, 2026
CursorBenchCursorBench score from Cursor, as Epoch AI republishes it.42.6%Max effortCursor (via Epoch AI)Oct 26, 2026
DeepSWEDeepSWE pass@1, as Epoch AI republishes it.69.0%Max effortDatacurve (via Epoch AI)Oct 26, 2026
DTBenchDTBench accuracy, as Epoch AI republishes it.87.7%Redwood Research (via Epoch AI)Oct 26, 2026
EnterpriseOps-Gym (AA run)AA's EnterpriseOps-Gym score for enterprise operations agents.36.4%GLM-5.3 (Max)Artificial AnalysisOct 27, 2026
Epoch Capabilities IndexEpoch Capabilities Index: Epoch AI's composite across its benchmark hub, with its confidence interval.156GLM-5.3Epoch AIOct 26, 2026
FrontierCode (AA run)AA's FrontierCode score: hard, unsaturated coding tasks.40.1%GLM-5.3 (Max)Artificial AnalysisOct 27, 2026
FrontierMath Tier 4 (Epoch)Share of FrontierMath Tier 4 research math problems solved, Epoch AI's run.29.3%Max effortEpoch AIAug 25, 2026
FrontierMath Tiers 1 to 3 (Epoch)Share of FrontierMath Tiers 1 to 3 problems solved, Epoch AI's run.68.8%Max effortEpoch AIAug 25, 2026
FrontierSWEFrontierSWE score, as Epoch AI republishes it.30.2%Max effortFrontierSWE (via Epoch AI)Oct 26, 2026
GPQA Diamond (AA run)GPQA Diamond accuracy in AA's run.91.7%GLM-5.3 (Max)Artificial AnalysisOct 27, 2026
GPQA Diamond (Epoch)GPQA Diamond accuracy, best scorer, Epoch AI's run.90.9%Max effortEpoch AIAug 24, 2026
Humanity's Last Exam (AA run)Share of Humanity's Last Exam questions answered correctly in AA's run.42.3%GLM-5.3 (Max)Artificial AnalysisOct 27, 2026
Intelligence IndexArtificial Analysis Intelligence Index: AA's composite of its own evaluation runs, 0 to 100 points.44.8GLM-5.3 (Max)Artificial AnalysisOct 27, 2026
IT-Bench SRE (AA run)AA's IT-Bench SRE score for incident and reliability agents.46.1%GLM-5.3 (Max)Artificial AnalysisOct 27, 2026
LMCALMCA score, 0 to 100, as Epoch AI republishes it. Its interval is printed only as a half-width, so it is not drawn.55.5Redwood Research (via Epoch AI)Oct 26, 2026
Mystery game puzzles (Epoch)Share of mystery game puzzles solved, Epoch AI's run.33%Max effortEpoch AIAug 30, 2026
OTIS Mock AIME (Epoch)Share of OTIS Mock AIME 2024 to 2025 problems solved, Epoch AI's run.91.1%Max effortEpoch AIAug 24, 2026
ProofBenchShare of ProofBench proofs graded correct, from Vals AI as Epoch AI republishes it.49%Max effortVals AI (via Epoch AI)Oct 26, 2026
SciCode (AA run)SciCode subproblem accuracy in AA's run.59.0%GLM-5.3 (Max)Artificial AnalysisOct 27, 2026
tau-Banking (AA run)AA's tau-Banking tool-use score.50.3%GLM-5.3 (Max)Artificial AnalysisOct 27, 2026
Terminal-Bench 4.0 (AA run)Share of Terminal-Bench 4.0 tasks solved in AA's own harness.41.9%GLM-5.3 (Max)Artificial AnalysisOct 27, 2026
Terminal-Bench Science (AA run)Share of Terminal-Bench Science tasks solved in AA's harness.9.5%GLM-5.3 (Max)Artificial AnalysisOct 27, 2026
WebDev ArenaWebDev Arena score from human pairwise votes on web builds, with its 95% interval, as Epoch AI republishes it.1,614Max effortLMArena (via Epoch AI)Oct 26, 2026
Domains
EconomicsArtificial Analysis capability score for economics questions, 0 to 100 points.51.2GLM-5.3 (Max)Artificial AnalysisOct 27, 2026
EngineeringArtificial Analysis capability score for engineering questions, 0 to 100 points.47.1GLM-5.3 (Max)Artificial AnalysisOct 27, 2026
Finance and accountingArtificial Analysis capability score for finance and accounting questions, 0 to 100 points.44.7GLM-5.3 (Max)Artificial AnalysisOct 27, 2026
Healthcare and medicalArtificial Analysis capability score for healthcare and medical questions, 0 to 100 points.42GLM-5.3 (Max)Artificial AnalysisOct 27, 2026
LegalArtificial Analysis capability score for legal questions, 0 to 100 points.42GLM-5.3 (Max)Artificial AnalysisOct 27, 2026
Strategy and operationsArtificial Analysis capability score for strategy and operations questions, 0 to 100 points.47.6GLM-5.3 (Max)Artificial AnalysisOct 27, 2026
Harvey Legal Lab (AA run)AA's run of Harvey's legal task lab.0.3%GLM-5.3 (Max)Artificial AnalysisOct 27, 2026

Routes, prices and uptime

Where GLM-5.3 is offered, what each route charges, and how each endpoint is holding up.

Where it is offered

10 of 19 routes GILD tracks offer GLM-5.3 today, preview included. Read Oct 29, 2026 from each route's own pages.

RouteStatusModel IDLimits and lifecycleSources
Amazon BedrockAvailableus.zai.glm-5.3global.zai.glm-5.3Cross-Region inference only, no In-Region endpoint; 1M context, 128K outputAmazon Web Services
Claude CodeAvailableglm-5.3Z.ai documents this route and Anthropic doesn't: point ANTHROPIC_BASE_URL at https://api.z.ai/api/anthropic; GLM Coding Plan sets glm-5.3[1m] for Opus and SonnetZ.aiAnthropic
CodexAvailableglm-5.3Z.ai documents this as a Codex custom model provider (Responses API), and OpenAI doesn'tZ.aiOpenAI
CursorAvailablenot statedpicker label GLM 5.3Hidden by default; US$1.40 input, US$0.26 cache read, US$4.40 outputCursor
DatabricksAvailabledatabricks-glm-5-3Model service name system.ai.glm-5-3; listed on the supported-models pageDatabricks
The maker's own APIAvailableglm-5.3Text input only; 1M context, 128K output; reasoning always on (low, high, max)Z.ai
GitHub ModelsRetirednot applicableservice retiredservice retired July 30, 2026GitHub
OpenCodeAvailableglm-5.3OpenCode Zen chat-completions endpoint and OpenCode GoOpenCode, ModelsOpenCode, Go
OpenRouterAvailablez-ai/glm-5.3z-ai/glm-5.3:batch1,048,576 context for the model; top provider 943,718 output; batch variant listedOpenRouter
Snowflake CortexPreviewglm-5.3Public preview through cross-region inference; 1,000,000 context, 128,000 outputSnowflake
Windsurf / DevinAvailableglm-5-3-highglm-5-3-lowglm-5-3-maxPro tier only (Low, High, Max)Cognition

Not offered on 6 routes: Antigravity, Claude on Google Cloud (Anthropic managed), Claude Platform on AWS, GitHub Copilot, Google Cloud Vertex / Agent Platform (Google managed) and Microsoft Foundry.

2 routes do not say: Gemini CLI and Grok Build.

What each of these 8 routes' pages say, with sources
RouteStatusModel IDLimits and lifecycleSources
AntigravityNot offeredAntigravity lists Gemini, Claude and GPT-OSS models onlyGoogle
Claude on Google Cloud (Anthropic managed)Not offeredTakes the Claude API's model IDs, which name Anthropic's Claude models onlyAnthropic, Claude Models on Google Cloud (Anthropic managed)Anthropic, Models overview
Claude Platform on AWSNot offeredClaude Platform on AWS lists Anthropic's Claude models onlyAnthropic
GitHub CopilotNot offeredAbsent from the Copilot supported-models table, which lists each supported modelGitHub
Google Cloud Vertex / Agent Platform (Google managed)Not offeredGoogle lists GLM 5.2, GLM 5 and GLM 4.7; GLM-5.3 isn't among themGoogle Cloud
Microsoft FoundryNot offeredFoundry names no Z.ai model; its other collections come from Cohere, DeepSeek, Meta, Mistral AI and xAIMicrosoft
Gemini CLINot statedGemini CLI's model page names Gemini models onlyGoogle
Grok BuildNot statedGrok Build pages name only grok-4.7xAI (SpaceXSI)

Prices by route

The lowest standard rate is OpenRouter, at $0.07 / $1.40 per million input and output tokens. US dollars per million tokens, as each route lists them, one row per route and rate plan, cheapest standard rate first after the maker's own; a blended rate states its mix. OpenRouter's endpoints follow under one heading, each with its monitor's uptime over 1 day and 30 minutes and the context and output it serves.

RouteStandard, in / outCache readOther ratesSource, or uptime (1 day / 30 min) and limits
Z.ai APIMaker$1.40 / $4.40$0.26Z.ai, Oct 28, 2026
OpenRouterLowest$0.07 / $1.40$0.069OpenRouter, Oct 29, 2026
Artificial Analysis price record$1.40 / $4.40$0.26Blended $2.15, 3 input : 1 output, no cacheBlended $0.9, 7 cache-hit : 2 input : 1 outputArtificial Analysis, Oct 27, 2026
Through OpenRouter, 49 provider endpoints. OpenRouter, Oct 29, 2026
Wafer (us)$0.07 / $1.40$0.069Up 100% / 100%1.05M context, 944K output
Baidu (fp8)80% discount included$0.28 / $0.88$0.052Up 100% / 100%1.05M context, 131K output
Wafer (fp4)$0.18 / $1.40$0.18Up 100% / 100%1.05M context, 944K output
Morph (fp8)$0.18 / $1.54$0.069Up 99.1% / 100%1.05M context, 944K output
Reka30% discount included$0.14 / $2.10$0.1Up 99.7% / 100%1.05M context, 262K output
Makora (fp4)$0.14 / $3$0.1Up 99.3% / 100%1.05M context, 128K output
Sail Research (fp8)$0.5 / $2$0.08Up 99.9%1.05M context, 944K output
Sail Research (us)$0.5 / $2$0.08Up 100% / 100%1.05M context, 944K output
DekaLLM$0.25 / $2.95$0.18Up 99.9% / 100%1.05M context, 944K output
InferenceNet (fp4)$0.08 / $3.60$0.076Up 100% / 100%1.05M context, 944K output
InferenceNet (us)$0.08 / $3.60$0.076Up 100% / 100%1.05M context, 944K output
Novita (fp8)55% discount included$0.63 / $1.98$0.12Up 99.7% / 100%1.05M context, 131K output
DeepInfra (fp4)37.5% discount included$0.56 / $2.50$0.13Up 98.2% / 100%1.05M context, 131K output
Io Net (fp8)$0.33 / $3.20$0.31Up 99.9% / 100%262K context, 131K output
GMICloud (fp8)50% discount included$0.7 / $2.20$0.13Up 100% / 100%1.05M context, 944K output
SiliconFlow (fp8)50% discount included$0.7 / $2.20$0.13Up 99.9% / 100%1.05M context, 262K output
Tenstorrent (fp8)$0.6 / $2.50$0.1Up 99.8% / 100%1.04M context, 131K output
Relace$0.07 / $4.38$0.07Up 100% / 100%1.05M context, 131K output
AkashML (fp8)$0.19 / $4.40$0.19Up 100% / 100%1.05M context, 131K output
Phala40% discount included$0.84 / $2.64$0.16Up 100% / 100%1.05M context, 944K output
Decart (fp4)$0.84 / $2.69$0.19Up 100% / 100%1.05M context, 944K output
DigitalOcean$0.91 / $2.86$0.17Up 99.5% / 100%1.05M context, 128K output
Inceptron (fp4)$1.20 / $2.20$0.14Up 99.9% / 100%1.05M context, 944K output
Fireworks (spot)$0.98 / $3.08$0.18Up 72.6% / 0%1.05M context, 944K output
PrimeIntellect$0.98 / $3.08$0.18Up 99.2% / 57.1%1.05M context, 131K output
Alibaba$1.19 / $3.74$0.24Up 100%1M context, 131K output
CoreWeave (fp8)$1.20 / $4$0.19Up 98.1% / 63.0%1.05M context, 944K output
Friendli10% discount included$1.26 / $3.96$0.23Up 100% / 100%1.05M context, 944K output
AtlasCloud (fp8)$1.40 / $4.40$0.26Up 100%1.05M context, 131K output
BaseTen (fp4, us)$1.40 / $4.40$0.14Up 100% / 100%1.05M context, 262K output
BaseTen (fp4)$1.40 / $4.40$0.14Up 100% / 100%1.05M context, 262K output
Cloudflare$1.40 / $4.40$0.26Up 100% / 100%1.05M context, 944K output
Crusoe (fp4)$1.40 / $4.40$0.26Up 100% / 100%1.05M context, 944K output
Fireworks$1.40 / $4.40$0.26Up 99.7% / 100%1.05M context, 944K output
Mistral (nvfp4)$1.40 / $4.40$0.14Up 100% / 100%1.05M context, 131K output
Mistral (zdr)$1.40 / $4.40$0.14Up 99.9% / 100%1.05M context, 131K output
Modal$1.40 / $4.40$0.26Up 100% / 100%1.05M context, 944K output
Nebius (fp4)$1.40 / $4.40$0.26Up 94.0%1.02M context, 922K output
Parasail (fp8)$1.40 / $4.40$0.26Up 99.5% / 71.4%1.05M context, 944K output
Together$1.40 / $4.40$0.26Up 100% / 100%1.05M context, 944K output
Venice20% discount included$1.40 / $4.40$0.26Up 99.6% / 100%1M context, 131K output
Z.AI (fp8)$1.40 / $4.40$0.26Up 100% / 100%1.05M context, 131K output
Mistral (nvfp4, eu)$1.54 / $4.84$0.15Up 100% / 100%1.05M context, 131K output
Amazon Bedrock (us-east-1)$1.68 / $5.28$0.31Cache write $2.10, 5-minute cacheUp 77.5% / 100%1.05M context, 131K output
ModelRun (fp4)$2.10 / $6.60$0.4Up 100% / 100%1.05M context, 524K output
Alibaba (prime, priority)Cache read $0.56, priority tierPriority $2.80 / $8.80, priority tierUp 100% / 100%1M context, 131K output
BaseTen (fast, priority)Cache read $0.21, priority tierPriority $2.10 / $6.60, priority tierUp 97.3% / 100%1.05M context, 262K output
BaseTen (us, fast, priority)Cache read $0.21, priority tierPriority $2.10 / $6.60, priority tierUp 97.7% / 100%1.05M context, 262K output
Fireworks (fast, priority)Cache read $0.39, priority tierPriority $2.10 / $6.60, priority tierUp 98.5% / 100%1.05M context, 944K output

Lineup

Z.ai's 3 releases in 1 family, oldest to newest along each tier, with list price and speed. GLM-5.3 is lit.

CurrentLegacyThis model

Price is the list price per 1M tokens, input / output. Speed is median output tokens per second. Bars share one scale across the lineup. Read between Oct 28, 2026 and Oct 31, 2026.

  1. GLM

    Z.ai's GLM family of open-weight models for coding, agents, and reasoning.

    3 releases

    1. 5.2Current. In 2 products we coverPrice$1.40 / $4.40Speed80.3 tok/s
    2. This page5.3Current. In 3 products we coverPrice$1.40 / $4.40Speed85.7 tok/s
    3. 5.3-FlashCurrent. In 2 products we coverPrice$0.15 / $0.50Speed70.5 tok/s

Where it fits

The layers of Agentic Software Development that GLM-5.3 can power. A product supplies the rest.

Product & Engineering, Software Development

Agentic Software Development

Primary role
Foundation Model / Reasoning Engine

GLM-5.3 can power coding, reasoning, and validation work inside an agentic software-development product. The Model does not itself provide the surrounding interface, execution environment, or system of record.

  1. Work planning & task decomposition

    The Model can assist with work planning & task decomposition when a Product supplies the necessary context and tools.

    Supporting

  2. Codebase context & intelligence

    The Model can assist with codebase context & intelligence when a Product supplies the necessary context and tools.

    Supporting

  3. Coding & implementation

    The Model can assist with coding & implementation when a Product supplies the necessary context and tools.

    Supporting

  4. Debugging & investigation

    The Model can assist with debugging & investigation when a Product supplies the necessary context and tools.

    Supporting

  5. Testing & verification

    The Model can assist with testing & verification when a Product supplies the necessary context and tools.

    Supporting

  6. Code review & quality

    The Model can assist with code review & quality when a Product supplies the necessary context and tools.

    Supporting

Products

We cover 3 products that offer GLM-5.3 today, all subscriptions.

Through a subscription

  1. OpenCode+27 PositiveOpen-source, MIT-licensed coding agent that edits code and runs commands from a terminal UI, desktop app, web client, or editor extension.Go, Go PlusPlans that include it
  2. Cline+39 PositiveOpen-source coding agent for your editor and terminal, on the models you choose.ClinePassPlans that include it
  3. Perplexity−25 NegativeAI answer engine with cited web research, model choice, and an agent for longer tasks.Pro, MaxPlans that include it

Limits each vendor states

ClineClinePass
2 to 5 times the usage the standard API rate buys on popular open coding models, measured against a 5-hour rolling window, a weekly limit and a monthly limit; Cline publishes no figures for those limits.
PerplexityPro, Max
In Perplexity's Search model picker on Pro and Max; usage limits apply, with no per-model figures published.

Plan access as each vendor's page states it: Anomaly (Oct 28, 2026), Cline (Oct 28, 2026), Perplexity (Oct 26, 2026).

Comparisons

GILD comparisons that name GLM-5.3, then those of the clouds and APIs that serve it.

What practitioners report

Strongest on Quality and reasoning, weakest on Speed.

Each figure is the share of accounts naming GLM-5.3 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.

Share of practitioner accounts favorable to GLM-5.3 on each of seven axes, with the accounts behind each figure
AxisFavorableAccounts
Quality and reasoningWhether its answers and code are right on the author's own task: reasoning, accuracy, instruction following, and consistency.76%47 favorable, 15 not, 61 authors
Tool use and structured outputWhether it calls tools correctly, returns valid structured output, and keeps agent loops on track.57%4 favorable, 3 not, 7 authors
Long contextHow it holds up over long documents, large codebases, long sessions, and many images or PDFs.40%2 favorable, 3 not, 5 authors
Developer experienceHow it is to build with: prompting, steering, effort settings, and support across SDKs and providers.33%5 favorable, 10 not, 15 authors
CostWhat the work costs: price per task, token use, and what caching and batch save.35%8 favorable, 15 not, 23 authors
SpeedResponse time, time to first token, and throughput.20%3 favorable, 12 not, 15 authors
ReliabilityWhether requests keep succeeding: overloaded errors, outages, rate limits, and changes that broke what worked.Only concerns on record0 favorable, 4 not, 4 authors
Every model on these seven axes
Share of accounts favorable on each axis for GLM-5.3 and every other model GILD has accounts for
AxisGLM-5.3GLM-5.3-FlashGLM-5.2Claude Haiku 5.5Claude Sonnet 5.5Claude Opus 5.5Claude Fable 5.1Claude Opus 5Claude Sonnet 5Claude Fable 5Claude Opus 4.8Claude Opus 4.7Claude Sonnet 4.6Claude Opus 4.6Claude Opus 4.5Claude Haiku 4.5Claude Sonnet 4.5GPT-6.1 TerraGPT-6.1 SolGPT-6 LunaGPT-6 AstraGPT-5.6 SolGPT-5.6 TerraGPT-5.6 LunaGPT-5.5GPT-5.4gpt-oss-120bGPT-6 SolGPT-5.3-CodexGemini 4 ArgonGemini 3.8 FlashGemma 4 31BGemini 3.1 Pro PreviewGemini 3.6 FlashDeepSeek V4.1 FlashDeepSeek V4 ProKimi K3.1 ProKimi K3Kimi K2.7 CodeMistral Large 4Mistral Medium 3.5Grok 4.7Grok 4.6Grok 4.5MiniMax M3.1 FlashMercury 3Muse Spark OpenMuse WonderMuse Spark 1.3Llama 4 ScoutLlama 4 MaverickQwen3.8 27BQwen3.8 MaxMiMo-V2.6-ProMiMo-V2.6-FlashLing 3.1 FlashStep 5 Preview
Quality and reasoning76%47 favorable, 15 not, 61 authors67%14 favorable, 7 not, 21 authors71%5 favorable, 2 not, 7 authors73%19 favorable, 7 not, 26 authors64%14 favorable, 8 not, 22 authors68%17 favorable, 8 not, 25 authors54%15 favorable, 13 not, 28 authors50%6 favorable, 6 not, 12 authors56%9 favorable, 7 not, 16 authors68%13 favorable, 6 not, 18 authors68%17 favorable, 8 not, 25 authors57%12 favorable, 9 not, 21 authors67%12 favorable, 6 not, 18 authors70%19 favorable, 8 not, 27 authors62%13 favorable, 8 not, 20 authors58%14 favorable, 10 not, 24 authors69%11 favorable, 5 not, 16 authors33%3 favorable, 6 not, 8 authors55%12 favorable, 10 not, 22 authors55%16 favorable, 13 not, 29 authors44%12 favorable, 15 not, 26 authors33%3 favorable, 6 not, 9 authors38%3 favorable, 5 not, 8 authorsNeeds 5 accounts from 3 authors3 favorable, 1 not, 4 authors33%4 favorable, 8 not, 12 authors33%2 favorable, 4 not, 6 authors58%22 favorable, 16 not, 38 authors31%10 favorable, 22 not, 32 authorsNeeds 5 accounts from 3 authors1 favorable, 3 not, 4 authors63%22 favorable, 13 not, 35 authors56%27 favorable, 21 not, 45 authors80%24 favorable, 6 not, 28 authors56%20 favorable, 16 not, 36 authorsNeeds 5 accounts from 3 authors1 favorable, 3 not, 4 authors61%25 favorable, 16 not, 40 authorsOnly concerns on record0 favorable, 4 not, 4 authors59%20 favorable, 14 not, 32 authorsOnly praise on record3 favorable, 0 not, 3 authors50%3 favorable, 3 not, 6 authors58%11 favorable, 8 not, 18 authors36%5 favorable, 9 not, 14 authors43%16 favorable, 21 not, 36 authors86%6 favorable, 1 not, 7 authors60%3 favorable, 2 not, 5 authors62%13 favorable, 8 not, 21 authors86%18 favorable, 3 not, 21 authorsNeeds 5 accounts from 3 authors2 favorable, 1 not, 3 authors20%1 favorable, 4 not, 5 authorsOnly praise on record2 favorable, 0 not, 2 authors53%8 favorable, 7 not, 15 authors44%8 favorable, 10 not, 17 authors71%24 favorable, 10 not, 34 authors57%4 favorable, 3 not, 7 authors22%2 favorable, 7 not, 9 authors40%4 favorable, 6 not, 10 authorsOnly concerns on record0 favorable, 1 not, 1 authorNeeds 5 accounts from 3 authors2 favorable, 1 not, 3 authors
Tool use and structured output57%4 favorable, 3 not, 7 authors33%2 favorable, 4 not, 6 authorsNo accounts yet67%6 favorable, 3 not, 9 authors40%4 favorable, 6 not, 10 authors46%6 favorable, 7 not, 13 authors30%3 favorable, 7 not, 10 authorsNeeds 5 accounts from 3 authors3 favorable, 1 not, 4 authors70%7 favorable, 3 not, 10 authors57%4 favorable, 3 not, 7 authors50%4 favorable, 4 not, 8 authors50%4 favorable, 4 not, 8 authors29%2 favorable, 5 not, 7 authors33%4 favorable, 8 not, 12 authors70%7 favorable, 3 not, 10 authors43%3 favorable, 4 not, 6 authors50%3 favorable, 3 not, 6 authors40%2 favorable, 3 not, 5 authors40%4 favorable, 6 not, 10 authors33%3 favorable, 6 not, 9 authors62%8 favorable, 5 not, 13 authorsNo accounts yetOnly concerns on record0 favorable, 2 not, 2 authorsOnly praise on record1 favorable, 0 not, 1 authorOnly praise on record1 favorable, 0 not, 1 authorNo accounts yet27%4 favorable, 11 not, 15 authors56%5 favorable, 4 not, 9 authorsNo accounts yet25%2 favorable, 6 not, 8 authors47%7 favorable, 8 not, 15 authors67%4 favorable, 2 not, 6 authors54%7 favorable, 6 not, 12 authorsOnly concerns on record0 favorable, 1 not, 1 author59%10 favorable, 7 not, 17 authorsOnly concerns on record0 favorable, 1 not, 1 authorNeeds 5 accounts from 3 authors3 favorable, 1 not, 4 authorsOnly concerns on record0 favorable, 1 not, 1 authorNo accounts yet38%5 favorable, 8 not, 13 authorsOnly concerns on record0 favorable, 5 not, 5 authors38%6 favorable, 10 not, 16 authorsOnly praise on record2 favorable, 0 not, 2 authorsOnly concerns on record0 favorable, 1 not, 1 author67%4 favorable, 2 not, 6 authors80%8 favorable, 2 not, 10 authorsNo accounts yetOnly concerns on record0 favorable, 1 not, 1 authorNeeds 5 accounts from 3 authors1 favorable, 1 not, 2 authorsNeeds 5 accounts from 3 authors1 favorable, 2 not, 3 authorsOnly concerns on record0 favorable, 4 not, 4 authors46%6 favorable, 7 not, 13 authorsOnly praise on record1 favorable, 0 not, 1 authorOnly concerns on record0 favorable, 5 not, 5 authorsOnly concerns on record0 favorable, 1 not, 1 authorOnly concerns on record0 favorable, 1 not, 1 authorOnly concerns on record0 favorable, 1 not, 1 author
Long context40%2 favorable, 3 not, 5 authorsNo accounts yetNo accounts yet29%2 favorable, 5 not, 7 authors60%3 favorable, 2 not, 5 authors80%8 favorable, 2 not, 10 authors63%5 favorable, 3 not, 8 authors67%4 favorable, 2 not, 6 authors50%3 favorable, 3 not, 6 authors33%2 favorable, 4 not, 6 authors60%6 favorable, 4 not, 10 authors50%4 favorable, 4 not, 7 authors71%5 favorable, 2 not, 7 authors64%7 favorable, 4 not, 11 authors40%4 favorable, 6 not, 10 authors40%2 favorable, 3 not, 5 authors50%4 favorable, 4 not, 8 authorsOnly concerns on record0 favorable, 1 not, 1 author38%3 favorable, 5 not, 8 authors20%1 favorable, 4 not, 5 authors27%3 favorable, 8 not, 11 authorsNo accounts yetNo accounts yetOnly concerns on record0 favorable, 1 not, 1 authorOnly concerns on record0 favorable, 1 not, 1 authorNeeds 5 accounts from 3 authors2 favorable, 1 not, 3 authors25%2 favorable, 6 not, 8 authorsOnly concerns on record0 favorable, 3 not, 3 authorsNo accounts yet25%2 favorable, 6 not, 8 authors38%5 favorable, 8 not, 13 authors20%1 favorable, 4 not, 5 authors44%7 favorable, 9 not, 16 authorsOnly praise on record1 favorable, 0 not, 1 author58%7 favorable, 5 not, 12 authorsNo accounts yetNeeds 5 accounts from 3 authors3 favorable, 1 not, 4 authorsOnly praise on record1 favorable, 0 not, 1 authorOnly concerns on record0 favorable, 1 not, 1 authorNeeds 5 accounts from 3 authors1 favorable, 3 not, 4 authorsNo accounts yet42%5 favorable, 7 not, 12 authorsNo accounts yetNo accounts yet40%2 favorable, 3 not, 5 authors60%3 favorable, 2 not, 5 authorsNo accounts yetOnly concerns on record0 favorable, 1 not, 1 authorOnly concerns on record0 favorable, 1 not, 1 authorOnly concerns on record0 favorable, 3 not, 3 authorsNeeds 5 accounts from 3 authors2 favorable, 1 not, 3 authors75%6 favorable, 2 not, 8 authorsOnly praise on record1 favorable, 0 not, 1 authorNeeds 5 accounts from 3 authors1 favorable, 1 not, 2 authorsNeeds 5 accounts from 3 authors1 favorable, 1 not, 2 authorsNo accounts yetNo accounts yet
Developer experience33%5 favorable, 10 not, 15 authorsOnly concerns on record0 favorable, 3 not, 3 authorsNo accounts yet25%2 favorable, 6 not, 8 authors38%5 favorable, 8 not, 13 authors38%6 favorable, 10 not, 16 authors50%7 favorable, 7 not, 14 authors25%3 favorable, 9 not, 12 authors29%2 favorable, 5 not, 7 authors25%3 favorable, 9 not, 12 authors53%10 favorable, 9 not, 19 authors29%4 favorable, 10 not, 14 authors57%4 favorable, 3 not, 7 authors45%5 favorable, 6 not, 11 authors67%8 favorable, 4 not, 12 authorsNeeds 5 accounts from 3 authors2 favorable, 2 not, 4 authors50%3 favorable, 3 not, 6 authorsOnly concerns on record0 favorable, 2 not, 2 authors27%3 favorable, 8 not, 11 authors25%2 favorable, 6 not, 8 authors41%7 favorable, 10 not, 17 authorsNo accounts yetOnly concerns on record0 favorable, 1 not, 1 authorNo accounts yetNo accounts yetNo accounts yet14%1 favorable, 6 not, 7 authors25%3 favorable, 9 not, 12 authorsNo accounts yet33%3 favorable, 6 not, 9 authors39%7 favorable, 11 not, 17 authorsOnly concerns on record0 favorable, 7 not, 7 authors40%8 favorable, 12 not, 20 authorsNo accounts yet35%8 favorable, 15 not, 23 authorsNo accounts yet9%1 favorable, 10 not, 11 authorsNo accounts yetOnly concerns on record0 favorable, 1 not, 1 author13%2 favorable, 14 not, 16 authorsOnly concerns on record0 favorable, 9 not, 9 authors25%5 favorable, 15 not, 20 authorsNo accounts yetNo accounts yetOnly concerns on record0 favorable, 7 not, 7 authors11%1 favorable, 8 not, 9 authorsOnly concerns on record0 favorable, 1 not, 1 authorOnly concerns on record0 favorable, 1 not, 1 authorNo accounts yetOnly concerns on record0 favorable, 6 not, 6 authorsOnly concerns on record0 favorable, 1 not, 1 author17%1 favorable, 5 not, 6 authorsOnly concerns on record0 favorable, 1 not, 1 authorOnly concerns on record0 favorable, 1 not, 1 authorOnly concerns on record0 favorable, 1 not, 1 authorNo accounts yetNo accounts yet
Cost35%8 favorable, 15 not, 23 authors76%16 favorable, 5 not, 21 authors71%5 favorable, 2 not, 7 authors69%20 favorable, 9 not, 29 authors45%10 favorable, 12 not, 22 authors56%15 favorable, 12 not, 27 authors20%4 favorable, 16 not, 20 authors43%3 favorable, 4 not, 7 authors39%7 favorable, 11 not, 17 authors8%1 favorable, 11 not, 12 authors40%6 favorable, 9 not, 14 authors50%7 favorable, 7 not, 13 authors50%6 favorable, 6 not, 12 authors33%7 favorable, 14 not, 20 authors53%8 favorable, 7 not, 15 authors29%4 favorable, 10 not, 12 authors38%3 favorable, 5 not, 8 authors80%8 favorable, 2 not, 9 authors74%14 favorable, 5 not, 19 authors79%22 favorable, 6 not, 26 authors29%7 favorable, 17 not, 23 authors57%4 favorable, 3 not, 7 authorsOnly concerns on record0 favorable, 1 not, 1 author50%3 favorable, 3 not, 6 authorsNeeds 5 accounts from 3 authors1 favorable, 3 not, 4 authors63%5 favorable, 3 not, 8 authors60%3 favorable, 2 not, 5 authors55%12 favorable, 10 not, 21 authorsNeeds 5 accounts from 3 authors2 favorable, 1 not, 3 authors35%7 favorable, 13 not, 20 authors58%14 favorable, 10 not, 23 authorsOnly praise on record7 favorable, 0 not, 7 authors50%8 favorable, 8 not, 16 authorsOnly concerns on record0 favorable, 1 not, 1 author66%25 favorable, 13 not, 37 authorsOnly praise on record2 favorable, 0 not, 2 authors40%10 favorable, 15 not, 25 authors71%5 favorable, 2 not, 7 authorsNeeds 5 accounts from 3 authors1 favorable, 3 not, 4 authors27%3 favorable, 8 not, 11 authorsOnly concerns on record0 favorable, 8 not, 8 authors19%5 favorable, 21 not, 26 authors20%1 favorable, 4 not, 5 authorsOnly praise on record4 favorable, 0 not, 4 authors80%12 favorable, 3 not, 15 authors50%6 favorable, 6 not, 12 authorsOnly concerns on record0 favorable, 1 not, 1 authorOnly concerns on record0 favorable, 9 not, 9 authorsNeeds 5 accounts from 3 authors2 favorable, 1 not, 3 authorsOnly praise on record1 favorable, 0 not, 1 authorOnly praise on record1 favorable, 0 not, 1 authorNeeds 5 accounts from 3 authors2 favorable, 2 not, 4 authorsOnly concerns on record0 favorable, 2 not, 2 authorsNeeds 5 accounts from 3 authors1 favorable, 1 not, 2 authorsOnly praise on record3 favorable, 0 not, 3 authorsOnly praise on record1 favorable, 0 not, 1 authorOnly praise on record1 favorable, 0 not, 1 author
Speed20%3 favorable, 12 not, 15 authors33%3 favorable, 6 not, 9 authorsNeeds 5 accounts from 3 authors1 favorable, 1 not, 2 authors74%14 favorable, 5 not, 19 authors88%14 favorable, 2 not, 16 authors46%6 favorable, 7 not, 13 authors44%4 favorable, 5 not, 9 authors60%3 favorable, 2 not, 5 authors44%4 favorable, 5 not, 9 authors57%4 favorable, 3 not, 7 authors31%4 favorable, 9 not, 13 authors63%5 favorable, 3 not, 8 authors17%1 favorable, 5 not, 6 authors36%4 favorable, 7 not, 11 authors73%8 favorable, 3 not, 11 authors78%7 favorable, 2 not, 9 authors75%6 favorable, 2 not, 8 authors83%5 favorable, 1 not, 5 authors37%7 favorable, 12 not, 19 authors45%5 favorable, 6 not, 11 authors41%7 favorable, 10 not, 17 authorsOnly praise on record1 favorable, 0 not, 1 authorNeeds 5 accounts from 3 authors1 favorable, 1 not, 2 authors80%4 favorable, 1 not, 5 authorsNeeds 5 accounts from 3 authors1 favorable, 1 not, 2 authorsNo accounts yet85%23 favorable, 4 not, 27 authors57%4 favorable, 3 not, 7 authorsOnly praise on record1 favorable, 0 not, 1 author45%5 favorable, 6 not, 11 authors61%19 favorable, 12 not, 31 authors53%10 favorable, 9 not, 17 authors35%6 favorable, 11 not, 16 authorsNeeds 5 accounts from 3 authors2 favorable, 1 not, 3 authors68%21 favorable, 10 not, 30 authorsOnly concerns on record0 favorable, 1 not, 1 author21%4 favorable, 15 not, 19 authorsOnly concerns on record0 favorable, 2 not, 2 authorsNo accounts yet21%3 favorable, 11 not, 14 authorsOnly concerns on record0 favorable, 2 not, 2 authors29%5 favorable, 12 not, 17 authorsNeeds 5 accounts from 3 authors1 favorable, 2 not, 3 authorsOnly praise on record2 favorable, 0 not, 2 authors44%4 favorable, 5 not, 9 authors65%13 favorable, 7 not, 20 authorsOnly concerns on record0 favorable, 1 not, 1 authorOnly concerns on record0 favorable, 1 not, 1 authorNeeds 5 accounts from 3 authors1 favorable, 1 not, 2 authorsNeeds 5 accounts from 3 authors3 favorable, 1 not, 4 authorsNo accounts yet33%7 favorable, 14 not, 21 authorsNeeds 5 accounts from 3 authors1 favorable, 3 not, 4 authorsOnly concerns on record0 favorable, 4 not, 4 authorsOnly concerns on record0 favorable, 1 not, 1 authorOnly concerns on record0 favorable, 2 not, 2 authorsOnly concerns on record0 favorable, 1 not, 1 author
ReliabilityOnly concerns on record0 favorable, 4 not, 4 authorsOnly concerns on record0 favorable, 7 not, 7 authorsOnly concerns on record0 favorable, 1 not, 1 author20%1 favorable, 4 not, 5 authors18%2 favorable, 9 not, 11 authors13%1 favorable, 7 not, 8 authors9%1 favorable, 10 not, 11 authors13%1 favorable, 7 not, 8 authors63%5 favorable, 3 not, 7 authors22%2 favorable, 7 not, 9 authors17%2 favorable, 10 not, 12 authors18%2 favorable, 9 not, 11 authors17%1 favorable, 5 not, 6 authors20%3 favorable, 12 not, 15 authors38%6 favorable, 10 not, 16 authors29%2 favorable, 5 not, 7 authors40%4 favorable, 6 not, 10 authorsOnly concerns on record0 favorable, 1 not, 1 author13%1 favorable, 7 not, 8 authorsOnly concerns on record0 favorable, 5 not, 5 authors14%2 favorable, 12 not, 14 authorsOnly concerns on record0 favorable, 4 not, 4 authorsOnly concerns on record0 favorable, 1 not, 1 authorNo accounts yetOnly concerns on record0 favorable, 2 not, 2 authorsOnly concerns on record0 favorable, 4 not, 4 authorsOnly concerns on record0 favorable, 4 not, 4 authors17%1 favorable, 5 not, 6 authorsOnly concerns on record0 favorable, 3 not, 3 authors5%1 favorable, 18 not, 19 authors15%3 favorable, 17 not, 20 authorsOnly concerns on record0 favorable, 5 not, 5 authors14%3 favorable, 19 not, 22 authorsOnly concerns on record0 favorable, 1 not, 1 author42%5 favorable, 7 not, 12 authorsNeeds 5 accounts from 3 authors1 favorable, 1 not, 2 authors8%1 favorable, 12 not, 13 authorsOnly concerns on record0 favorable, 1 not, 1 authorNeeds 5 accounts from 3 authors1 favorable, 1 not, 2 authors38%3 favorable, 5 not, 8 authorsOnly concerns on record0 favorable, 4 not, 4 authors22%2 favorable, 7 not, 9 authorsOnly concerns on record0 favorable, 1 not, 1 authorNo accounts yet60%3 favorable, 2 not, 5 authors33%2 favorable, 4 not, 5 authorsNo accounts yetOnly concerns on record0 favorable, 2 not, 2 authorsOnly concerns on record0 favorable, 1 not, 1 authorNeeds 5 accounts from 3 authors1 favorable, 3 not, 4 authorsOnly concerns on record0 favorable, 1 not, 1 authorOnly concerns on record0 favorable, 9 not, 9 authorsOnly concerns on record0 favorable, 1 not, 1 authorOnly concerns on record0 favorable, 2 not, 2 authorsNo accounts yetNo accounts yetOnly concerns on record0 favorable, 1 not, 1 author
The 106 accounts behind GLM-5.3's figures

GILD searched Hacker News and GitHub for accounts that name GLM-5.3.

Quality and reasoning 76%

  • Favorable
    Even and especially for frontend UI, GLM 5.3 is a whole world better than Astra.

    Artificial Analysis Intelligence Index v5. dannyw, Hacker News commenter, self-described, Oct 28, 2026. GLM 5.3 against GPT-6 Astra on frontend UI work.

  • Favorable
    GLM 5.3 is so much better than Astra at backend tasks, Astra does the most weird nonsensical bugs.

    Artificial Analysis Intelligence Index v5. mariopt, Hacker News commenter, self-described, Oct 28, 2026. GLM 5.3 against GPT-6 Astra on backend tasks.

  • Unfavorable
    Benchmarks might have you believe open models are only barely behind the big US labs in intelligence, but it feels much worse in practice.

    Anthropic S-1. ac29, Hacker News commenter, self-described, Oct 26, 2026. GLM 5.3 and GLM 5.3-flash for a week on the author's main project, beside DeepSeek Flash 4.1 and Kimi 3.

  • Favorable
    GLM 5.3 with DSFV4.1 as advisor via omp feels Opus 4.6 level, i.e. totally able to ship stuff.

    IBM CEO says open weight models are now good and cheap on-prem. Frannky, Hacker News commenter, self-described, Oct 26, 2026. GLM 5.3 through OpenRouter in omp with DeepSeek Flash V4.1 as advisor.

  • Favorable
    GLM 5.3 is good enough if anthropic and openai go under (which they wont).

    No signs of AI payoff outside the tech sector. zzzeek, Hacker News commenter, self-described, Oct 24, 2026. GLM 5.3 as a fallback developer tool.

  • Favorable
    GLM 5.3 because it is very good a more complex stuff

    IBM CEO says open weight models are now good and cheap on-prem. jacquesm, Hacker News commenter, self-described, Oct 26, 2026. GLM 5.3 run locally as a workhorse model beside Qwen 3.8.

  • Unfavorable
    as someone who has tried glm 5.3, it's way behind frontier

    X post by @David97717063. David, X user, self-described, Oct 27, 2026. GLM 5.3 tried against a frontier-model subscription.

  • Favorable
    GLM 5.3 so good I still haven't used Deepseek 1017 yet

    X post by @NonBinaryJew. Human AI, social scientist and local AI enthusiast, self-described, Oct 27, 2026. GLM 5.3 as the author's current model.

  • Unfavorable
    The result is pretty ugly and unintuitive, OP's design is much nicer.

    Show HN: Vocal Slice – Cut audio by selecting text, fully on-device. andai, Hacker News commenter, self-described, Aug 18, 2026. GLM 5.3 on a one-shot app build with AssemblyAI for transcription.

  • Favorable
    It's a really good model.

    GLM-5.3 Artificial Analysis Benchmarks. glub, Hacker News commenter, self-described, Aug 18, 2026. GLM 5.3, tested on its release day.

  • Unfavorable
    for my production work they simply couldn't cope at all

    GPT 5.6 Sol 20% price reduction. nsoonhui, Hacker News commenter, self-described, Aug 22, 2026. GLM 5.3 through OpenRouter on production work.

  • Favorable
    had to start using GLM-5.3 to fix Opus 5 errors even on primitive backend changes

    Anthropic appears to be A/B testing reduced effort levels in Claude Code. cynerx, Hacker News commenter, self-described, Aug 22, 2026. GLM-5.3 on backend changes after Opus 5.

  • Favorable
    I have been using GLM-5.3 in my home setup and it is very good in comparison.

    Anthropic appears to be A/B testing reduced effort levels in Claude Code. surgical_fire, Hacker News commenter, self-described, Aug 22, 2026. GLM-5.3 in a home setup, compared with Claude at work.

  • Favorable
    Fable/Sol/GLM 5.3/Kimi are its league (in that order)

    A week of using Codex more than Claude. c0rruptbytes, Hacker News commenter, self-described, Aug 22, 2026. GLM 5.3 on the author's own SlopCodeBench runs.

  • Favorable
    it's definitely an impressive model, coming in around #6

    GLM-5.3 (open-weight) beat Anthropic/OpenAI models – for 1/5 the cost. gertlabs, Hacker News commenter posting Gertlabs evaluation results, self-described, Aug 23, 2026. GLM 5.3 on Gertlabs multi-agent coding evaluations.

  • Favorable
    it's not quite there, but it's good enough for productive work

    Ox-Alpha Is GLM?. petesergeant, Hacker News commenter, self-described, Aug 25, 2026. GLM-5.3 as the fallback when Fable and Sol credits run out.

  • Favorable
    I had good experience with GLM 5.3

    Z.ai confirms Ox Alpha is a new GLM-series model and will release its weights. stanac, Hacker News commenter, self-described, Aug 26, 2026. GLM 5.3 through OpenRouter in August 2026.

  • Favorable
    It definitely can be a daily driver if you don't want to use Anthropic or OpenAI.

    GLM-5.3-Flash. Sphax, Hacker News commenter, self-described, Aug 26, 2026. GLM 5.3 on the Z.ai Max coding plan in the Pi harness.

  • Favorable
    I'm actually finding GLM-5.3 max to be better than Sol and Fable.

    GLM-5.3-Flash. nullbio, Hacker News commenter, self-described, Aug 27, 2026. GLM-5.3 at max effort in OpenCode through OpenRouter.

  • Favorable
    I've noticed no real difference between the Claude model and GLM

    GLM-5.3-Flash. crossroadsguy, Hacker News commenter, self-described, Aug 27, 2026. GLM 5.3 for coding, compared with Claude.

  • Favorable
    I used it with pi and had a fairly good time

    GLM-5.3 is now open-weight. revolvingthrow, Hacker News commenter, self-described, Aug 28, 2026. GLM 5.3 in the Pi harness.

  • Favorable
    It's been able to tackle all the random hard problems I've thrown at it and it has the intuition that DS4Flash seems to lack.

    GLM-5.3 is now open-weight. mmastrac, Hacker News commenter, self-described, Aug 28, 2026. GLM-5.3 run locally on two DGX Sparks.

  • Favorable
    The winners so far are (ranked by the quality of the final result, not by token cost) GPT 5.6 sol (extra high thinking); GLM 5.3

    Ask HN: What is one simple thing LLMs are insanely bad at?. drpython, Hacker News commenter, self-described, Aug 29, 2026. GLM 5.3 on the author's own Rust code-simplification test.

  • Favorable
    GLM 5.3 feels like Opus 4.8 (which I consider better than Opus 5).

    GLM-5.3-Flash. bel8, Hacker News commenter, self-described, Aug 29, 2026. GLM 5.3 on the OpenCode Go plan.

  • Favorable
    it is a legit, proper, work horse. As in, this can do real work.

    GLM-5.3 is now open-weight. ThouYS, Hacker News commenter, self-described, Aug 29, 2026. GLM 5.3 run on-prem.

  • Favorable
    I am running GLM 5.3 across 2x DGX Sparks and was doing comparisons and it absolutely can beat Gemini.

    Apple caught off guard by AI demand for Mac Mini and Mac Studio. sharms, Hacker News commenter, self-described, Aug 31, 2026. GLM 5.3 run across two DGX Sparks, compared with Gemini and Fable 5.

  • Favorable
    its definitely slower but it gets the job done

    Is it just me, or has Claude Opus gotten worse recently?. dalekirkwood, Hacker News commenter, self-described, Sep 1, 2026. The author's team chose GLM 5.3 over Claude.

  • Favorable
    I tried GLM5.3 and it was pretty decent.

    GPT-6 Astra. akie, Hacker News commenter, self-described, Sep 4, 2026. GLM 5.3, compared with Opus and Sonnet.

  • Favorable
    I specifically use it with glm 5.3 as it is the most language specific LLM that understands nuances.

    Ask HN: Who is using MCP in production?. navigate8310, Hacker News commenter, self-described, Sep 4, 2026. GLM 5.3 with the author's own textbook MCP server for Chinese study.

  • Unfavorable
    I can tell the difference between the SOTA and GLM 5.3, and paying a few hundred for the better models is definitely worth it.

    Mistral raises €3B. user43928, Hacker News commenter, self-described, Sep 8, 2026. GLM 5.3 compared with state-of-the-art paid models.

  • Favorable
    even using the original model (GLM here) against that list to go fix it seems fine

    How well do agents use test/verification techniques?. Havoc, Hacker News commenter, self-described, Sep 8, 2026. GLM-5.3 writing code, with Muse 1.3 listing bugs for it to fix.

  • Favorable
    It is slow, but a very strong worker.

    DeepSeek launching v4.1 flash cheaper and more capable than v4 pro. bitexploder, Hacker News commenter, self-described, Sep 9, 2026. GLM 5.3 at max effort as a heavy concurrent agent worker.

  • Favorable
    It did and the new part is better than the human-designed part I grabbed off the internet.

    Benchmark: CadQuery vs. OpenSCAD for agentic CAD work. evilduck, Hacker News commenter, self-described, Sep 12, 2026. GLM 5.3 with the Hermes agent redesigning a 3D-printable part from STL files.

  • Unfavorable
    My experience is that open weights models find between 1/4 to 1/2 of what Fable/Opus stack can find, and often miss the most critical issues.

    GPT-5.6 Luna vs. GPT-6 Astra: Is a $1.20 Model Good Enough for Code Review?. criley2, Hacker News commenter, self-described, Sep 14, 2026. GLM 5.3 with review skills and subagents in opencode and omp, against the Fable/Opus stack.

  • Unfavorable
    GLM-5.3 and Kimi K3 are just below where I can use them to completely replace frontier models.

    Step 5 Preview: Advancing the Pareto Frontier. InsideOutSanta, Hacker News commenter, self-described, Sep 20, 2026. GLM-5.3 as a possible replacement for frontier models.

  • Favorable
    DSv4.1 Flash and GLM 5.3 kept in check by a supervising frontier like Astra or Fable already in my experience clowns massively on ever using Opus or Sonnet.

    MiMo v2.6. rpcope1, Hacker News commenter, self-described, Sep 22, 2026. GLM 5.3 and DeepSeek V4.1 Flash supervised by Astra or Fable.

  • Favorable
    GLM-5.3(-flash), which both gave me consistently great results

    MiMo v2.6. celrod, Hacker News commenter, self-described, Sep 22, 2026. GLM-5.3 and GLM-5.3 Flash in a bare-bones vibe-coded harness.

  • Favorable
    GLM 5.3 I've been getting Opus 5-level performance

    MiMo-v2.6-Pro: Intelligence, Performance and Price Analysis. jmaker, Hacker News commenter, self-described, Sep 22, 2026. GLM 5.3 with Qwen 3.8 and DeepSeek 4.1 Flash after cancelling Claude subscriptions.

  • Favorable
    It is quite clever and hacks around it pretty effectively however.

    Claude Opus 5.5. jjcm, Hacker News commenter, self-described, Sep 22, 2026. GLM 5.3 on the author's build test, which it does without vision input.

  • Unfavorable
    GLM 5.3 knows that its implementation violates user requirements yet sticks with it after imagining what a hypothetical grader will check

    Speculative Reward Hacking in Coding Agents. _jonas, Hacker News commenter, self-described, Sep 25, 2026. GLM 5.3 agent reasoning traces on DeepSWE-1.1 tasks.

  • Favorable
    I think it's as good as the latest closed-weight models at a fraction of the cost

    Ask HN: Which model do you use for work?. meredithbloom, Hacker News commenter, self-described, Sep 26, 2026. GLM 5.3 Coding at work under a capped AI quota.

  • Favorable
    I have tried Qwen 3.8, Kimi 3 and GLM 5.3 which are equally impressive

    GPT 6.1 Sol: Near-Astra intelligence for a fifth of the price. wg0, Hacker News commenter, self-described, Sep 29, 2026. GLM 5.3 tried beside Qwen 3.8, Kimi 3 and DeepSeek v4.1 Flash.

  • Favorable
    it was able to completely rewrite it in just 1/2 very small prompts which is crazy

    Next.js 16.4. Imustaskforhelp, Hacker News commenter, self-described, Oct 10, 2026. GLM 5.3 porting a Go htmx and templ codebase to Gleam.

  • Favorable
    I think GLM 5.3 (non-flash) is a vastly better model.

    One month coding with GLM 5.3 Flash. RussianCow, Hacker News commenter, self-described, Oct 2, 2026. GLM 5.3 (non-flash) for planning, with GLM 5.3 Flash executing.

  • Unfavorable
    I've had less than satisfactory results with GLM5.3.

    Mistral Large 4. Roark66, Hacker News commenter, self-described, Oct 6, 2026. GLM 5.3 compared with Qwen3.8-Flash-Next for coding.

  • Favorable
    in a 20-game match Pi's engine won 18 and drew the other 2

    I had Codex and Pi build the same app in Orca, then compared them side by side. piscaries, Hacker News commenter, self-described, Oct 6, 2026. GLM-5.3 in Pi under Orca against Codex with GPT-5.6, both building a chess coach app.

  • Favorable
    Recently I switched to the Mistral hosted GLM-5.3, this worked very well and powered through a tonne of work.

    Mistral Large 4. phillc73, Hacker News commenter, self-described, Oct 6, 2026. GLM-5.3 hosted by Mistral on Mistral subscriptions.

  • Unfavorable
    And GLM 5.3 is very clearly not a frontier model

    Why isn't the industry freaking out about DeepSeek 4.1 Flash?. mlinsey, Hacker News commenter, self-described, Oct 8, 2026. GLM 5.3 on a $100/mo Z.ai subscription against Opus 5.5 on a $100/mo Claude subscription.

  • Favorable
    I was previously using GLM-5.3 as the orchestrator, after switching to DS anecdotally there was an unnacceptable quality loss

    Why isn't the industry freaking out about DeepSeek 4.1 Flash?. p1necone, Hacker News commenter, self-described, Oct 8, 2026. GLM-5.3 as orchestrator over cheaper implementer models.

  • Favorable
    there really isn't that much of a difference between GLM5.3 and Opus/OpenAI

    Why isn't the industry freaking out about DeepSeek 4.1 Flash?. dada216, Hacker News commenter, self-described, Oct 9, 2026. GLM-5.3 against Opus and OpenAI models on CRUD-style ERP software.

  • Favorable
    Its very good, I'll only go back to Claude if GLM isn't available

    Why isn't the industry freaking out about DeepSeek 4.1 Flash?. disgruntledphd2, Hacker News commenter, self-described, Oct 9, 2026. GLM 5.3 as a replacement for Claude.

  • Favorable
    Feels dumber than GLM 5.3 (only open model I use extensively).

    Muse Spark Open. eknkc, Hacker News commenter, self-described, Oct 15, 2026. GLM 5.3 as the author's main open model, used as the yardstick for a new release.

  • Unfavorable
    For most projects, a single prompt will get me what I want with good quality with Deepseek vs GLM 5.3.

    Muse Spark Open. neya, Hacker News commenter, self-described, Oct 16, 2026. GLM 5.3 against DeepSeek V4 Flash in OpenCode on JS and Elixir projects.

  • Unfavorable
    Am I the only one experiencing accidental chinese tokens, wrong grammar, and other sloppy mistakes in almost every output when using GLM 5.3?

    Muse Spark Open. meeq, Hacker News commenter, self-described, Oct 16, 2026. GLM 5.3 through the z.ai and OpenCode Go subscriptions.

  • Unfavorable
    the free claide.ai works quite well and better than GLM 5.3 (not even flash)

    DeepSeek-v4.1-Flash-1017. crossroadsguy, Hacker News commenter, self-described, Oct 17, 2026. GLM 5.3 (not Flash) compared with free claude.ai and DeepSeek.

  • Unfavorable
    Neither flash or regular glm 5.3 are close in my experience.

    Muse Spark 1.3. KptMarchewa, Hacker News commenter, self-described, Sep 3, 2026. GLM 5.3 and GLM 5.3 Flash compared with Sol.

  • Favorable
    I'm switching between Opus, GPT Codex and GLM 5.3 for coding and I can barely tell the difference.

    Mistral raises €3B. eloisant, Hacker News commenter, self-described, Sep 8, 2026. GLM 5.3 for coding, alternating with Opus and GPT Codex.

  • Unfavorable
    causes in-house GLM 5.3 transposition issue

    [dead]. portmortem, Hacker News commenter, self-described, Sep 10, 2026. an in-house GLM 5.3 deployment generating VyOS firewall configuration from a spec.

  • Favorable
    GLM5.3 on max has in my experience far less hallucinations than any other open weights model

    How GLM built its own inference infrastructure. ma2kx, Hacker News commenter, self-described, Sep 17, 2026. GLM-5.3 at max effort against other open-weight models.

  • Favorable
    From my experience GLM 5.3 is at most 6 months away from the frontier models, and good enough for most tasks already

    Sonnet 5.5. tripleee, Hacker News commenter, self-described, Sep 28, 2026. GLM 5.3 compared with frontier models.

  • Favorable
    GLM 5.3 is incredible because for the first time with an open-source model, it feels.. enough.

    Mistral Large 4. pacha3000, Hacker News commenter, self-described, Oct 6, 2026. GLM 5.3 as an everyday open model.

  • Favorable
    GLM 5.3 is very impressive and definitely better

    Why isn't the industry freaking out about DeepSeek 4.1 Flash?. ctolsen, Hacker News commenter, self-described, Oct 8, 2026. GLM 5.3 compared with MiMo-2.6-pro.

  • Favorable
    they recently added GLM 5.3 to their platform (and it works rather well)

    Mistral Large 4. petercooper, Hacker News commenter, self-described, Oct 21, 2026. GLM 5.3 hosted on Mistral's platform.

Tool use and structured output 57%

  • Favorable
    less likely to get stuck so I can let it run for much longer without intervention

    IBM CEO says open weight models are now good and cheap on-prem. jacquesm, Hacker News commenter, self-described, Oct 26, 2026. GLM 5.3 run locally as a workhorse model beside Qwen 3.8.

  • Favorable
    I've had tasks running for almost 70 hours straight without stopping

    X post by @SPAC89. Iam_, X user, self-described, Sep 4, 2026. GLM 5.3 Max as orchestrator with GLM 5.3 Flash workers on the GLM Coding plan in ZCode, about 15B tokens in a week.

  • Unfavorable
    both GLM 5.3 and Deepseek v4 went into infinite loop and wasted my tokens until my OpenRouter wallet reached 0

    GPT 5.6 Sol 20% price reduction. nsoonhui, Hacker News commenter, self-described, Aug 22, 2026. GLM 5.3 through OpenRouter on production work.

  • Favorable
    4 inputs from me, two related to how I'd run it on draft day. Worked great!

    State of Open Models: Summer 2026 Observations. jst1fthsdys, Hacker News commenter, self-described, Sep 1, 2026. GLM-5.3 in OMP on a multi-step data and site-building task.

  • Favorable
    I feel im having the most productive experience with agentic collaborations so far, by a lot.

    Fable 5 – Median thinking declined in August. poslathian, Hacker News commenter, self-described, Sep 21, 2026. GLM-5.3 as a daily driver in Pi with custom extensions, for modeling and analysis work.

  • Unfavorable
    it forgot how to do tool calls yesterday

    Why isn't the industry freaking out about DeepSeek 4.1 Flash?. disgruntledphd2, Hacker News commenter, self-described, Oct 9, 2026. GLM 5.3 as a replacement for Claude.

  • Unfavorable
    The model rather quickly starts appending unnecessary tool calls and loops.

    GLM-5.3 degenerates and loops with Mistral as provider. novakovicdavid, GitHub issue author, self-described, Oct 18, 2026. Mistral-hosted zai-glm-5.3 in the Pi coding agent 1.3.0.

Long context 40%

Developer experience 33%

  • Unfavorable
    Model will not load if I enable tensor split.

    Eval bug: GLM 5.3 (non flash) doesn't load with Tensor Split and CUDA backend. d-shehu, GitHub issue author, self-described, Oct 27, 2026. GLM-5.3 UD-IQ4_XS GGUF in llama.cpp on an AWS g7 instance with four RTX 4500 Pro GPUs.

  • Unfavorable
    it degenerates to repeating a single `@` token

    GLM-5.3 (glm_moe_dsa) emits repeated '@' tokens instead of a response on CPU (ngl=0). darkhipo, GitHub issue author, self-described, Sep 17, 2026. GLM-5.3 unsloth UD-Q4_K_XL GGUF in llama.cpp on CPU on an M4 Max with 128 GB.

  • Favorable
    I've forgotten how good it feels to see reasoning tokens.

    GLM-5.3 Artificial Analysis Benchmarks. glub, Hacker News commenter, self-described, Aug 18, 2026. GLM 5.3, tested on its release day.

  • Unfavorable
    Z.AI is the only provider for GLM 5.3 on OpenRouter.

    Z.ai confirms Ox Alpha is a new GLM-series model and will release its weights. stanac, Hacker News commenter, self-described, Aug 26, 2026. GLM 5.3 through OpenRouter in August 2026.

  • Favorable
    It tends to be more proactive with suggestions after a task is done also.

    GLM-5.3-Flash. bel8, Hacker News commenter, self-described, Aug 29, 2026. GLM 5.3 on the OpenCode Go plan.

  • Unfavorable
    I used open router and sometimes had good, then appalling performance.

    DeepSeek v4.1 Flash Is Now Our Best Hacking Model. cregy, Hacker News commenter, self-described, Sep 16, 2026. GLM 5.3 through OpenRouter across FP8 and FP4 providers.

  • Favorable
    On OpenRouter, I count 29 different providers for this model

    Microsoft exec called AI scraping 'the largest theft of labor in human history'. bhelkey, Hacker News commenter, self-described, Sep 18, 2026. GLM 5.3 provider choice on OpenRouter.

  • Unfavorable
    The rest of the session was all claude-speak up until I've rage-quit

    Claude Opus 5.5. hypfer, Hacker News commenter, self-described, Sep 23, 2026. GLM-5.3 asked to find the root cause behind an Opus 5 patch.

  • Unfavorable
    glm 5.x is just very chatty though

    Pop!_OS bans AI-generated code from much of its codebase. zzzeek, Hacker News commenter, self-described, Oct 4, 2026. GLM 5.3 on together.ai to review intricate Claude changes.

  • Favorable
    GLM 5.3 acknowledges it and talks about it, even acknowledging the censorship of it.

    The AI Race Just Got Awkward. techjamie, Hacker News commenter, self-described, Sep 30, 2026. GLM 5.3 on a historical question, against DeepSeek 4.1 Flash and Kimi K3.

  • Favorable
    being able to see more of the thinking tokens is extremely valuable as it means I can steer the model quicker and more effectively

    Mistral Large 4. disgruntledphd2, Hacker News commenter, self-described, Oct 7, 2026. GLM 5.3 and Kimi K3 against Claude models.

  • Unfavorable
    GLM 5.3 is locked behind some dumb request system

    Anthropic S-1. c0rruptbytes, Hacker News commenter, self-described, Oct 26, 2026. GLM 5.3 on Amazon Bedrock in a multi-provider harness.

  • Unfavorable
    When setting dcp>1 and triton_mla attention backend, glm-5.3 crashes with

    [Bug] GLM-5.3 DPC crashes. xhejtman, GitHub issue author, self-described, Sep 6, 2026. GLM-5.3 served by SGLang with decode context parallelism and the triton_mla backend.

  • Unfavorable
    That GLM 5,3 Series Censorship Filters. Is Totally Tighter Come For Writing

    GLM 5.3 Censorship Filters Disappointed. songonzales71-svg, GitHub issue author, self-described, Sep 30, 2026. GLM-5.3 on chat.z.ai for creative writing and roleplay.

  • Unfavorable
    Starting sglang for RadixArk/GLM-5.3-NVFP4 with TP=8, DCP=8 on B300 GPUs fails with

    [Bug] DCP fails for GLM-5.3-NVFP4 on B300. sfbemerk, GitHub issue author, self-described, Sep 30, 2026. RadixArk GLM-5.3-NVFP4 in SGLang with TP=8 and DCP=8 on B300 GPUs.

Cost 35%

  • Unfavorable
    cost more than my sub because it uses more tokens to solve the same problem

    X post by @David97717063. David, X user, self-described, Oct 27, 2026. GLM 5.3 tried against a frontier-model subscription.

  • Favorable
    It cuts my costs by around 70% while maintaining the same quality

    X post by @SPAC89. Iam_, X user, self-described, Sep 4, 2026. GLM 5.3 Max as orchestrator with GLM 5.3 Flash workers on the GLM Coding plan in ZCode, about 15B tokens in a week.

  • Unfavorable
    I tried to use GLM 5.3 once and it burned like half my weeks usage in minutes because it wasn't caching properly.

    X post by @ian_90211. Ian, writer in Beverly Hills, self-described, Oct 26, 2026. GLM 5.3 on a Command Code subscription.

  • Unfavorable
    The price , in the end, didn't come cheap, mainly because too much time wasted on thinking.

    GPT 5.6 Sol 20% price reduction. nsoonhui, Hacker News commenter, self-described, Aug 22, 2026. GLM 5.3 through OpenRouter on production work.

  • Unfavorable
    For the price, it's actually not Pareto optimal

    GLM-5.3 (open-weight) beat Anthropic/OpenAI models – for 1/5 the cost. gertlabs, Hacker News commenter posting Gertlabs evaluation results, self-described, Aug 23, 2026. GLM 5.3 on Gertlabs multi-agent coding evaluations.

  • Unfavorable
    I always kept running out of usage with the original glm-5.3

    GLM-5.3-Flash. rush86999, Hacker News commenter, self-described, Aug 26, 2026. GLM-5.3 on the Z.ai coding plan.

  • Favorable
    Still dollars per day (at most) with heavy concurrent agent running.

    DeepSeek launching v4.1 flash cheaper and more capable than v4 pro. bitexploder, Hacker News commenter, self-described, Sep 9, 2026. GLM 5.3 at max effort as a heavy concurrent agent worker.

  • Unfavorable
    slower, more expensive, and less good for what I use them for

    Ask HN: What default model do you use and why?. gpugreg, Hacker News commenter, self-described, Sep 12, 2026. GLM-5.3 on Python, CUDA and JS work, compared with DeepSeek models.

  • Unfavorable
    Thing is that GLM 5.3 is many multiples the cost to run, and slower.

    DeepSeek v4.1 Flash Is Now Our Best Hacking Model. cmrdporcupine, Hacker News commenter, self-described, Sep 16, 2026. GLM 5.3 compared with DeepSeek V4.1 Flash for iterative work.

  • Unfavorable
    but the token allowances were kinda limited

    Claude Cowork and chat are now one Claude. KronisLV, Hacker News commenter, self-described, Sep 16, 2026. GLM 5.3 on a subscription, compared with Kimi K3.

  • Favorable
    I paid $360 annual for Max plan and currently averaging about 1BN tokens a day with their frontier GLM-5.3 model.

    How GLM built its own inference infrastructure. Daviey, Hacker News commenter, self-described, Sep 17, 2026. GLM-5.3 on an annual Z.ai Max coding plan.

  • Favorable
    The max plan will provide ~1,100 USD of GLM-5.3 or ~260 USD of GLM-5.3-flash per month for 168 USD.

    How GLM built its own inference infrastructure. _aavaa_, Hacker News commenter, self-described, Sep 17, 2026. GLM-5.3 on the Z.ai Max plan through omp at about a 97% cache hit rate.

  • Unfavorable
    Running GLM-5.3 high on their monthly plan will hit quotas absurdly fast compared to Opus 5 High on Claude code.

    How GLM built its own inference infrastructure. reacharavindh, Hacker News commenter, self-described, Sep 17, 2026. GLM-5.3 at high effort on the €18 Z.ai monthly plan, compared with Opus 5 High in Claude Code.

  • Unfavorable
    Were it not for GLM 5.3 blowing up a quarter of my monthly budget in 5h

    GPT-6 Sol and Luna. sieve, Hacker News commenter, self-described, Sep 23, 2026. GLM 5.3 on a monthly API budget beside DeepSeek, Meta and Xiaomi models.

  • Favorable
    if I use it I don't run out of quota by the end of the first week of each month

    Ask HN: Which model do you use for work?. meredithbloom, Hacker News commenter, self-described, Sep 26, 2026. GLM 5.3 Coding at work under a capped AI quota.

  • Unfavorable
    It's slightly better than Flash but rarely enough to justify the much steeper price.

    One month coding with GLM 5.3 Flash. ThibWeb, Hacker News commenter, self-described, Oct 2, 2026. GLM 5.3 on usage-based billing, compared with GLM 5.3 Flash.

  • Unfavorable
    I also completely maxed out two subscriptions within the space of six days this month.

    Mistral Large 4. phillc73, Hacker News commenter, self-described, Oct 6, 2026. GLM-5.3 hosted by Mistral on Mistral subscriptions.

  • Favorable
    the cache reads are free so I can let it think a lot without breaking the bank

    Claude Haiku 5.5. pimeys, Hacker News commenter, self-described, Oct 8, 2026. GLM 5.3 on Coralbricks, where cache reads are free.

  • Unfavorable
    compared to Opus 5.5 on a $100/mo Claude subscription, there wasn't a big gap

    Why isn't the industry freaking out about DeepSeek 4.1 Flash?. mlinsey, Hacker News commenter, self-described, Oct 8, 2026. GLM 5.3 on a $100/mo Z.ai subscription against Opus 5.5 on a $100/mo Claude subscription.

  • Favorable
    It is basically free, half a cent per turn maybe

    Whistle: Speech to Text in 16.9 MB. cco, Hacker News commenter, self-described, Oct 9, 2026. GLM 5.3 generating replies in a Home Assistant voice pipeline.

  • Unfavorable
    GLM 5.3 was more expensive than Haiku and Sonnet 5.5 on a workload I was testing recently despite being much cheaper on the price sheet.

    Token-maxxing is dead, OpenRouter's token usage plateaus. alphabettsy, Hacker News commenter, self-described, Oct 20, 2026. GLM 5.3 on the author's own test workload against Haiku and Sonnet 5.5.

  • Unfavorable
    they are more expensive than just using Opus/Sol on subs

    SlopCodeBench 10/2026 – Opus 5.5, Astra wins overall, xhigh considered harmful. ac29, Hacker News commenter, self-described, Oct 21, 2026. GLM 5.3 through inference providers, against Opus and Sol on subscriptions.

  • Favorable
    the GLM models are significantly less verbose

    MiMo v2.6. FredFS456, Hacker News commenter, self-described, Sep 22, 2026. GLM 5.3 and GLM 5.3 Flash compared with DeepSeek 4.1 Flash.

  • Unfavorable
    but it also at least 4x the price

    Why isn't the industry freaking out about DeepSeek 4.1 Flash?. ctolsen, Hacker News commenter, self-described, Oct 8, 2026. GLM 5.3 compared with MiMo-2.6-pro.

Speed 20%

  • Favorable
    After a few days of using a fast GLM-5.3 endpoint for coding... codex feels unbearably slow

    X post by @vikhyatk. vik, X user (bio: teaching computers how to see @moondreamai), self-described, Oct 7, 2026. GLM-5.3 on a fast endpoint for coding.

  • Unfavorable
    So that's why GLM-5.3 is so horribly slow on OpenCode last days.

    X post by @PovilasKorop. Povilas Korop, AI Coding & Laravel Educator, self-described, Oct 27, 2026. GLM-5.3 on OpenCode.

  • Unfavorable
    GLM 5.3 was slow. DS can do 600+ tps.

    X post by @OliverDlouhy. Oliver Dlouhy, Co-founder & CEO of Kiwi.com, self-described, Oct 27, 2026. GLM 5.3 compared with DeepSeek on throughput.

  • Unfavorable
    I tried the same real world task on all three and GLM-5.3 was the slowest by a factor of 3.

    Ox Alpha. mgrandl, Hacker News commenter, self-described, Aug 21, 2026. GLM-5.3 against Opus and Sol on the same real-world task.

  • Unfavorable
    Even for simpler tasks, Chinese models took long time to complete

    GPT 5.6 Sol 20% price reduction. nsoonhui, Hacker News commenter, self-described, Aug 22, 2026. GLM 5.3 through OpenRouter on production work.

  • Unfavorable
    Claude is definitely faster as well

    GLM-5.3-Flash. crossroadsguy, Hacker News commenter, self-described, Aug 27, 2026. GLM 5.3 for coding, compared with Claude.

  • Unfavorable
    We use GLM 5.3 - its definitely slower

    Is it just me, or has Claude Opus gotten worse recently?. dalekirkwood, Hacker News commenter, self-described, Sep 1, 2026. The author's team chose GLM 5.3 over Claude.

  • Unfavorable
    If you are okay with waiting use GLM 5.3 max.

    DeepSeek launching v4.1 flash cheaper and more capable than v4 pro. bitexploder, Hacker News commenter, self-described, Sep 9, 2026. GLM 5.3 at max effort as a heavy concurrent agent worker.

  • Unfavorable
    GLM-5.3, GLM-5.3-Flash and Kimi K3 are also fine, but slower

    Ask HN: What default model do you use and why?. gpugreg, Hacker News commenter, self-described, Sep 12, 2026. GLM-5.3 on Python, CUDA and JS work, compared with DeepSeek models.

  • Unfavorable
    many multiples the cost to run, and slower

    DeepSeek v4.1 Flash Is Now Our Best Hacking Model. cmrdporcupine, Hacker News commenter, self-described, Sep 16, 2026. GLM 5.3 compared with DeepSeek V4.1 Flash for iterative work.

  • Favorable
    GLM 5.3 was faster and still pretty good

    Claude Cowork and chat are now one Claude. KronisLV, Hacker News commenter, self-described, Sep 16, 2026. GLM 5.3 on a subscription, compared with Kimi K3.

  • Unfavorable
    Codex finished faster

    I had Codex and Pi build the same app in Orca, then compared them side by side. piscaries, Hacker News commenter, self-described, Oct 6, 2026. GLM-5.3 in Pi under Orca against Codex with GPT-5.6, both building a chess coach app.

  • Unfavorable
    even if GLM 5.3 is a bit slower

    Why isn't the industry freaking out about DeepSeek 4.1 Flash?. jacquesm, Hacker News commenter, self-described, Oct 8, 2026. GLM 5.3 after switching from DeepSeek V4.1.

  • Favorable
    it was so fast it generated entire documents like instantly

    Why isn't the industry freaking out about DeepSeek 4.1 Flash?. pjerem, Hacker News commenter, self-described, Oct 8, 2026. GLM-5.3 on Ollama Cloud.

  • Unfavorable
    it's more ~Terra, while being significantly slower

    Real-SWE: Benchmarking AI models on private, real-world, enterprise codebases. CuriouslyC, Hacker News commenter, self-described, Sep 13, 2026. GLM 5.3 as a daily driver since release, beside GPT 5.6 Sol.

Reliability Only concerns on record

  • Unfavorable
    Nah, it's unusable today. Yesterday even GLM-5.3 worked smoothly without any timeouts.

    X post by @mithilyaganti. Mithil Yaganti, tests LLMs and builds benchmarks for long-running agentic tasks, self-described, Oct 26, 2026. GLM-5.3 in ZCode, replying to the ZCode account.

  • Unfavorable
    including GLM is they will dumb down the models based on load

    Muse Spark Open. neya, Hacker News commenter, self-described, Oct 16, 2026. GLM 5.3 against DeepSeek V4 Flash in OpenCode on JS and Elixir projects.

  • Unfavorable
    On some days it's usable, but on most days it feels more like having to trust a pretty smart intern that may or may not get a small stroke every couple of minutes.

    Muse Spark Open. meeq, Hacker News commenter, self-described, Oct 16, 2026. GLM 5.3 through the z.ai and OpenCode Go subscriptions.

  • Unfavorable
    Claude Code sessions through the bridge: about 7 of 22 streamed requests failed in one session (2026-10-08).

    GLM 5.3: intermittent internalServerException / ServiceUnavailableException (Bedrock-side, repro pending). prog893, GitHub issue author and bedrock-bridge maintainer, self-described, Oct 27, 2026. global.zai.glm-5.3 on Amazon Bedrock through bedrock-bridge in Claude Code sessions.