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Muse model by Meta

Muse Wonder

Meta's Muse model for coding, long-running agents and computer use, which plans long tasks and delegates parts to sub-agents. API model muse-wonder-1.0 on the Meta Model API at US$4 per million input tokens and US$20 per million output tokens, with a 1M-token context, also in Muse Code, OpenRouter and Cursor. Muse Wonder Full, which Meta calls its most advanced model, runs only inside a Muse Code subscription.

Official page

Where it sits in Meta's lineup

  1. MuseMeta's Muse family of hosted and open-weight models for coding and agentic work.You are on Muse Wonder. Current:Muse Spark Open
  2. LlamaMeta's open-weight Llama model family.Llama 4 Maverick
Stack role
Foundation Model / Reasoning Engine
Offered in
1 product
Made by
Meta
Family
Muse, version 1.0
Released
Oct 12, 2026 Current
In its family
Release 2 of 3 in Muse. The newest is Muse Spark Open.

Strengths and weaknesses

Compare with other models Up to 3 beside Muse Wonder

  • Muse Wonder

Suggested comparisons

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

Muse WonderMetaThis page, always on the chart

Among the 40 current releases on this chart, Muse Wonder ranks 7th of 38 on Tool use, 7th of 37 on Code and 8th of 38 on Hard reasoning. Computer use is Meta's own figure on OSWorld 2.1, marked on the chart. It ranks lowest on Answers in full, 23rd of 25. Science, Multimodal and Instruction following: not yet published by Meta or any independent evaluator, checked Nov 2, 2026.

Each axis is one public benchmark at one setting, on its own fixed 0 to 100 scale, so adding a model never moves another. A dotted bridge crosses a missing result, which is never a zero. A hollow mark is a result from another source: the maker's own figure or another lab's run, where the benchmark's usual source has not tested the model yet. The readout names it.

On the chart

  • Muse WonderThis pageResults on 9 of 12 axes$4 / $20146 tokens/sFirst token in 24 s

Prices and speeds as of Oct 29, 2026.

Muse Wonder on each axis9 of 12 with a result

Beside the benchmarks

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

Cost

$3.27per task

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

Speed

212tokens a second

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

First token
31 s
Whole answer
43 s

Capacity

1.05Mtokens

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

Max output
944K
Reads
Text, Images, Speech, Video

Quality

52.4of 100

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

GDPval knowledge work
1,770 Elo
Terminal-Bench 4.0
52.0%
Epoch Capabilities Index
162

Hallucination

20.9%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
38.0%

Where you can get it

6of 19 routes

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

Open weights
No
Licence
Meta Model API Terms of Service
Every route and price

Figures from Artificial Analysis, OpenRouter, Epoch AI, GILD's route matrix and Meta, read Oct 26 to Nov 1, 2026. Each measure's definition and source open under . Not yet published for Muse Wonder: Cached input.

Every value with its benchmark, run and source

Muse Wonder's result on each axis, with the benchmark, the setting and run, who reported it, the source and the date
AxisBenchmark and settingMuse WonderRunSourceDate
Agentic codingTerminal-Bench 4.0Pass@1 averaged over 3 runs, mini-swe-agent harness. Vals.ai ranked it 12th on its leaderboard of Oct 29, 2026, level with GPT-6.1 Terra at 49.49%.49.5%WonderEffort: not published. Harness: mini-swe-agent.Not drawn: Artificial Analysis 52% in another lab's harness, Oct 29, 2026. SourceVals.aiOct 29, 2026
CodeSciCodeSubproblem accuracy, pass@1, highest effort run60.3%Muse Wonder (Max)Effort: max. Harness: none.Artificial AnalysisOct 29, 2026
MathFrontierMath Tiers 1-3Accuracy, pass@1, highest effort run82.1%Effort: max. Harness: none.Epoch AIOct 12, 2026
ScienceGPQA DiamondAccuracy, pass@1, highest effort runNot yet published by Meta or any independent evaluator, checked Nov 2, 2026
Hard reasoningHumanity's Last ExamAccuracy, text-only questions, no tools50.1%Muse Wonder (Max)Effort: max. Harness: none.Artificial AnalysisOct 29, 2026
Tool useAutomationBench-AAScore, Artificial Analysis run68.1%Muse Wonder (Max)Effort: max. Harness: Artificial Analysis AutomationBench harness.Artificial AnalysisOct 29, 2026
Computer useOSWorld 2.1Partial score, full 108-task set, v2.1 release. Meta's own run at max effort in its own test framework on all 108 tasks: the average partial score. It fully completed 34.3% of tasks.72.6%Muse Wonder (max)Effort: max. Harness: Meta common evaluation framework.MetaReported by MetaOct 12, 2026
Long contextAA-LCR v1.1Accuracy, Artificial Analysis run80.7%Muse Wonder (Max)Effort: max. Harness: none.Artificial AnalysisOct 29, 2026
MultimodalMMMU-ProOverall accuracy, no toolsNot yet published by Meta or any independent evaluator, checked Nov 2, 2026
FactualityAA-Omniscience AccuracyAccuracy, Artificial Analysis run38%Hallucination rate 20.9% in the same run (lower is better)Muse Wonder (Max)Effort: max. Harness: none.Artificial AnalysisOct 29, 2026
Answers in fullSpeechMap% Complete over 2,120 contested requests, reasoning-on entry. SpeechMap tested it through OpenRouter with reasoning on. The provider's API blocked 54.8% of requests; the model denied 1.4% and evaded 1.1%.42.7%54.8% of requests failed at the provider and count against itEffort: reasoning on. Harness: none.SpeechMap.AIOct 29, 2026
Instruction followingMultiChallengeAccuracy, Scale AI runNot yet published by Meta or any independent evaluator, checked Nov 2, 2026

Price and speed

  • Muse Wonder lists at $4 per million input tokens and $20 per million output tokens. Meta pricing, Oct 29, 2026.
  • Muse Wonder, at max effort, writes 146.4 output tokens per second on Meta's API, and its first token arrives 24 s after the request. Artificial Analysis, Oct 29, 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
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 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 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
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
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-5.338.9%59%68.8%90.9%42.3%62.2%Not yet published79.7%Not yet published32.3%71.5%Not yet published
GLM-5.21%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
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. Muse Wonder49.5%
  10. GPT-6.1 Terra49.5%
  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. Muse Spark 1.310.6%
  33. Claude Sonnet 510.6%
  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. Kimi K2.7 Code1%Artificial Analysis's run, Terminal-Bench 4.0
  46. GLM-5.21%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. Muse Wonder82.1%
  15. GPT-5.6 Luna82.1%
  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. Muse Spark 1.393.5%Artificial Analysis's run, GPQA Diamond
  43. GPT-5.593.5%Artificial Analysis's run
  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. Muse Spark 1.348.7%
  14. Claude Opus 4.848.7%
  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. Claude Opus 4.742.3%
  35. GLM-5.342.3%
  36. Claude Sonnet 541.3%
  37. GLM-5.241.1%
  38. DeepSeek V4 Pro41%
  39. Gemini 3.6 Flash40.8%
  40. Claude Opus 4.639.9%
  41. GLM-5.3-Flash39.9%
  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. Muse Spark 1.357.9%
  25. Grok 4.557.9%
  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. Llama 4 Scout0.2%
  50. Llama 4 Maverick0.2%
  51. gpt-oss-120b0.2%

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. Muse Spark 1.383%
  14. GPT-6.1 Sol83%
  15. GPT-5.6 Terra83%
  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. Muse Wonder80.7%
  28. GPT-6 Astra80.7%
  29. DeepSeek V4 Pro80.3%
  30. Grok 4.680.3%
  31. Qwen3.8 Max80.3%
  32. Claude Sonnet 4.680%
  33. Gemini 3.6 Flash80%
  34. GLM-5.3-Flash80%
  35. Gemini 4 Argon79.7%
  36. MiniMax M3.1 Flash79.7%
  37. GLM-5.379.7%
  38. Claude Opus 579.3%
  39. Kimi K2.7 Code79.3%
  40. Grok 4.579.3%
  41. Claude Opus 4.778.7%
  42. Muse Spark Open78.3%
  43. GLM-5.278.3%
  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. Muse Spark Open74.2%
  5. GPT-6.1 Terra74.2%
  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 Muse Wonder 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 Muse Wonder: the value, the run it comes from, the publisher and the day it was read
MeasureMuse WonderRunSourceRead
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.1.05MArtificial AnalysisOct 27, 2026
Max outputThe most tokens the model writes in one response.944Kno Meta figure in the stored maker sources; OpenRouter lists 943,718OpenRouterOct 29, 2026
ReadsThe kinds of input the model accepts.Text, Images, Speech, VideoArtificial AnalysisOct 27, 2026
LicenceThe terms the weights or the service are offered under.Meta Model API Terms of ServiceMetaNov 1, 2026
Open weightsWhether the maker publishes the weights for anyone to run.NoArtificial AnalysisOct 27, 2026
Routes offering itOf the 19 clouds, gateways and coding products GILD tracks, how many offer the release today, preview included.6 of 19GILD route matrixOct 29, 2026
Cost
Answer tokens per taskLower is better. Answer tokens per Intelligence Index task, reasoning excluded.25,677Muse Wonder (Max)Artificial AnalysisOct 27, 2026
Cost per task, cache readsLower is better. The cache-read share of AA's cost per Intelligence Index task.$1.51Muse Wonder (Max)Artificial AnalysisOct 27, 2026
Cost per task, cache writesLower is better. The cache-write share of AA's cost per Intelligence Index task.$0.59Muse Wonder (Max)Artificial AnalysisOct 27, 2026
Cost per task, inputLower is better. The input-token share of AA's cost per Intelligence Index task.$2.18Muse Wonder (Max)Artificial AnalysisOct 27, 2026
Cost per task, outputLower is better. The answer-token share of AA's cost per Intelligence Index task.$1.09Muse Wonder (Max)Artificial AnalysisOct 27, 2026
Cost per task, reasoningLower is better. The reasoning-token share of AA's cost per Intelligence Index task.$0.58Muse Wonder (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.$3.27Muse Wonder (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.$4,711Muse Wonder (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.54,477Muse Wonder (Max)Artificial AnalysisOct 27, 2026
Reasoning tokens per taskLower is better. Reasoning tokens per Intelligence Index task.28,800Muse Wonder (Max)Artificial AnalysisOct 27, 2026
Speed
End-to-end time, 100K promptLower is better. Median seconds for a whole response with a 100,000-token prompt.54 sMuse Wonder (Max)Artificial AnalysisOct 27, 2026
End-to-end response timeLower is better. Seconds AA measures for a whole response on its standard prompt.43 sMuse Wonder (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.53 sMuse Wonder (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.41 sMuse Wonder (Max)Artificial AnalysisOct 27, 2026
Output speed, 100K promptMedian output tokens per second when the prompt is about 100,000 tokens long.292 tokens/sMuse Wonder (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.212 tokens/sMuse Wonder (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.261 sMuse Wonder (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.46 sMuse Wonder (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.31 sMuse Wonder (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.20.9%Max effortArtificial AnalysisOct 29, 2026
Omniscience accuracyShare of AA-Omniscience knowledge questions answered correctly.38%Max effortArtificial AnalysisOct 29, 2026
Omniscience indexAA-Omniscience index: correct answers minus wrong answers, declines neutral, -100 to 100.25.5Muse Wonder (Max)Artificial AnalysisOct 27, 2026
Knowledge work
AA-BriefcaseAA-Briefcase overall Elo for long business deliverables, with AA's 95% interval.1,659Muse Wonder (Max)Artificial AnalysisOct 27, 2026
GDP-PDF (AA run)Share of GDP-PDF document tasks where every check passes.30.6%Muse Wonder (Max)Artificial AnalysisOct 27, 2026
GDPval-AAGDPval-AA Elo: AA's run of economically valuable knowledge-work tasks, graded pairwise, with AA's interval.1,770Muse Wonder (Max)Artificial AnalysisOct 27, 2026
MLCR (AA run)AA's MLCR overall score for long, multi-document reading.22.2%Muse Wonder (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.$9,432Andon Labs (via Epoch AI)Oct 26, 2026
Capability beyond the chart
AA-LCRAA long-context reasoning accuracy.80.7%Muse Wonder (Max)Artificial AnalysisOct 27, 2026
CritPt (AA run)Share of CritPt research-level physics problems solved in AA's run.28.3%Muse Wonder (Max)Artificial AnalysisOct 27, 2026
CursorBenchCursorBench score from Cursor, as Epoch AI republishes it.50.4%Max effortCursor (via Epoch AI)Oct 26, 2026
DTBenchDTBench accuracy, as Epoch AI republishes it.95.2%Redwood Research (via Epoch AI)Oct 26, 2026
Epoch Capabilities IndexEpoch Capabilities Index: Epoch AI's composite across its benchmark hub, with its confidence interval.162Muse WonderEpoch AIOct 26, 2026
FrontierCode (AA run)AA's FrontierCode score: hard, unsaturated coding tasks.46.5%Muse Wonder (Max)Artificial AnalysisOct 27, 2026
FrontierMath Tier 4 (Epoch)Share of FrontierMath Tier 4 research math problems solved, Epoch AI's run.70.7%Max effortEpoch AIOct 12, 2026
FrontierMath Tiers 1 to 3 (Epoch)Share of FrontierMath Tiers 1 to 3 problems solved, Epoch AI's run.82.1%Max effortEpoch AIOct 12, 2026
Humanity's Last Exam (AA run)Share of Humanity's Last Exam questions answered correctly in AA's run.50.1%Muse Wonder (Max)Artificial AnalysisOct 27, 2026
Intelligence IndexArtificial Analysis Intelligence Index: AA's composite of its own evaluation runs, 0 to 100 points.52.4Muse Wonder (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.56.8Redwood Research (via Epoch AI)Oct 26, 2026
Mystery game puzzles (Epoch)Share of mystery game puzzles solved, Epoch AI's run.51%Max effortEpoch AIOct 14, 2026
OTIS Mock AIME (Epoch)Share of OTIS Mock AIME 2024 to 2025 problems solved, Epoch AI's run.99.4%Max effortEpoch AIOct 12, 2026
ProofBenchShare of ProofBench proofs graded correct, from Vals AI as Epoch AI republishes it.84%Vals AI (via Epoch AI)Oct 26, 2026
SciCode (AA run)SciCode subproblem accuracy in AA's run.60.3%Muse Wonder (Max)Artificial AnalysisOct 27, 2026
Terminal-Bench 4.0 (AA run)Share of Terminal-Bench 4.0 tasks solved in AA's own harness.52.0%Muse Wonder (Max)Artificial AnalysisOct 27, 2026
Terminal-Bench Science (AA run)Share of Terminal-Bench Science tasks solved in AA's harness.25.7%Muse Wonder (Max)Artificial AnalysisOct 27, 2026
WeirdML v3, best runWeirdML v3 maximum performance across runs, as Epoch AI republishes it.25.2%Extra-high effortHåvard Tveit Ihle (via Epoch AI)Oct 26, 2026
Domains
EconomicsArtificial Analysis capability score for economics questions, 0 to 100 points.57.7Muse Wonder (Max)Artificial AnalysisOct 27, 2026
EngineeringArtificial Analysis capability score for engineering questions, 0 to 100 points.53.8Muse Wonder (Max)Artificial AnalysisOct 27, 2026
Finance and accountingArtificial Analysis capability score for finance and accounting questions, 0 to 100 points.51.3Muse Wonder (Max)Artificial AnalysisOct 27, 2026
Healthcare and medicalArtificial Analysis capability score for healthcare and medical questions, 0 to 100 points.48.1Muse Wonder (Max)Artificial AnalysisOct 27, 2026
LegalArtificial Analysis capability score for legal questions, 0 to 100 points.52Muse Wonder (Max)Artificial AnalysisOct 27, 2026
Strategy and operationsArtificial Analysis capability score for strategy and operations questions, 0 to 100 points.54.8Muse Wonder (Max)Artificial AnalysisOct 27, 2026
Harvey Legal Lab (AA run)AA's run of Harvey's legal task lab.10%Muse Wonder (Max)Artificial AnalysisOct 27, 2026

Routes, prices and uptime

Where Muse Wonder is offered, what each route charges, and how each endpoint is holding up.

Where it is offered

6 of 19 routes GILD tracks offer Muse Wonder today, preview included. Read Oct 29, 2026 from each route's own pages.

RouteStatusModel IDLimits and lifecycleSources
Claude CodeAvailablemuse-wonder-1.0Meta documents this route and Anthropic doesn't: point ANTHROPIC_BASE_URL at Meta Model API's Messages endpoint; its config runs the main loop and the Opus tier on muse-wonder-1.0Meta
CodexAvailablemuse-wonder-1.0Meta documents this as a Codex custom model provider (Responses API), and OpenAI doesn'tMetaOpenAI
CursorAvailablenot statedpicker label Muse WonderUS$4 input, US$0.20 cache read, US$20 output; up to 1M tokens in Max Mode at the same rates; no US data residencyCursor
The maker's own APIPreviewmuse-wonder-1.0Preview on Meta Model API, Standard mode only; 1,048,576 context; US$4 input, US$0.20 cached input, US$20 output per million tokens; not offered in South KoreaMeta, ModelsMeta, Pricing and rate limits
GitHub ModelsRetirednot applicableservice retiredservice retired July 30, 2026GitHub
OpenCodeAvailablemuse-wonder-1.0OpenCode Zen over the Responses API, US$4 input, US$20 output, US$0.20 cached read; not in OpenCode GoOpenCode, ModelsOpenCode, Go
OpenRouterAvailablemeta/muse-wonder1,048,576 context for the model; top provider 943,718 outputOpenRouter

Not offered on 9 routes: Amazon Bedrock, Antigravity, Claude on Google Cloud (Anthropic managed), Claude Platform on AWS, Databricks, GitHub Copilot, Google Cloud Vertex / Agent Platform (Google managed), Microsoft Foundry and Snowflake Cortex.

3 routes do not say: Gemini CLI, Grok Build and Windsurf / Devin.

What each of these 12 routes' pages say, with sources
RouteStatusModel IDLimits and lifecycleSources
Amazon BedrockNot offeredBedrock's Meta models are Llama 3 and Llama 4 only, no Muse modelAmazon Web Services
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
DatabricksNot offeredDatabricks' Meta models are Llama 4 Maverick, Llama 3.3 70B and Llama 3.1 8B, no Muse modelDatabricks
GitHub CopilotNot offeredAbsent from the Copilot supported-models table, which lists each supported modelGitHub
Google Cloud Vertex / Agent Platform (Google managed)Not offeredGoogle's Meta section lists Muse Spark 1.3 onlyGoogle Cloud
Microsoft FoundryNot offeredFoundry sells Meta's Llama models and lists Muse-Glimmer-30B for fine-tuning; Muse Wonder isn't among themMicrosoft
Snowflake CortexNot offeredCortex's Meta models are Llama 4 Maverick and Llama 3.x, no Muse modelSnowflake
Gemini CLINot statedGemini CLI's model page names Gemini models onlyGoogle
Grok BuildNot statedGrok Build names only grok-4.7; its docs say it supports any custom model added to its config filexAI (SpaceXSI), Grok Build: SpaceXSI's Coding AgentxAI (SpaceXSI), Bring Grok to
Windsurf / DevinNot statedabsent from Devin model dataCognition

Prices by route

The lowest standard rate is Meta API, at $4 / $20 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
Meta APIMakerLowest$4 / $20Meta, Oct 29, 2026
Artificial Analysis price record$4 / $20$0.2Blended $8, 3 input : 1 output, no cacheBlended $2.94, 7 cache-hit : 2 input : 1 outputArtificial Analysis, Oct 27, 2026
OpenRouter$4 / $20$0.2OpenRouter, Oct 29, 2026
Through OpenRouter, 1 provider endpoints. OpenRouter, Oct 30, 2026
Meta$4 / $20$0.2Up 98.5% / 100%1.05M context, 944K output

Lineup

Meta's 5 releases in 2 families, oldest to newest along each tier, with list price and speed. Muse Wonder 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 Nov 2, 2026.

  1. Muse

    Meta's Muse family of hosted and open-weight models for coding and agentic work.

    3 releases

    1. Spark 1.3Current. In 3 products we coverPrice$1.25 / $4.25Speed167.8 tok/s
    2. This pageWonderCurrent. In 1 product we coverPrice$4 / $20Speed146.4 tok/s
    3. Spark OpenCurrent. In no product we cover yetPriceNot on recordSpeed139.6 tok/s

  2. Llama

    Meta's open-weight Llama model family.

    2 releases

    1. 4 MaverickLegacy. In no product we cover yetPrice$0.24 / $0.97, on Amazon BedrockSpeed53.5 tok/s
    2. 4 ScoutLegacy. In no product we cover yetPrice$0.16 / $0.64, on Microsoft FoundrySpeed132.8 tok/s

Where it fits

The layers of Agentic Software Development that Muse Wonder can power. A product supplies the rest.

Product & Engineering, Software Development

Agentic Software Development

Primary role
Foundation Model / Reasoning Engine

Muse Wonder 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 1 product that offers Muse Wonder today, all subscriptions.

Through a subscription

  1. Cursor+11 MixedAI coding agent and code editor for writing, reviewing, and shipping software, with agents in the editor, the terminal, and the cloud.Premium, Super, Ultra, Teams, EnterprisePlans that include it

Limits each vendor states

CursorPremium, Super, Ultra, Teams, Enterprise
Not part of the included pool: on Premium and above, billed at the model's API list price from the first request, paid from prepaid credit (input $4, no cache write price, cache read $0.2, output $20 per million tokens); US data residency: No. Plus and Free do not include third-party models.

Plan access as each vendor's page states it: Anysphere (Oct 28, 2026).

What practitioners report

Muse Wonder has enough accounts to score 1 of 7 axes so far.

Each figure is the share of accounts naming Muse Wonder 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 Muse Wonder 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.20%1 favorable, 4 not, 5 authors
Tool use and structured outputWhether it calls tools correctly, returns valid structured output, and keeps agent loops on track.Only concerns on record0 favorable, 1 not, 1 author
Long contextHow it holds up over long documents, large codebases, long sessions, and many images or PDFs.Only concerns on record0 favorable, 1 not, 1 author
Developer experienceHow it is to build with: prompting, steering, effort settings, and support across SDKs and providers.Only concerns on record0 favorable, 1 not, 1 author
CostWhat the work costs: price per task, token use, and what caching and batch save.Only concerns on record0 favorable, 9 not, 9 authors
SpeedResponse time, time to first token, and throughput.Only concerns on record0 favorable, 1 not, 1 author
ReliabilityWhether requests keep succeeding: overloaded errors, outages, rate limits, and changes that broke what worked.Only concerns on record0 favorable, 2 not, 2 authors
Every model on these seven axes
Share of accounts favorable on each axis for Muse Wonder and every other model GILD has accounts for
AxisMuse WonderMuse Spark OpenMuse Spark 1.3Llama 4 ScoutLlama 4 MaverickClaude 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 3GLM-5.3-FlashGLM-5.3GLM-5.2Qwen3.8 27BQwen3.8 MaxMiMo-V2.6-ProMiMo-V2.6-FlashLing 3.1 FlashStep 5 Preview
Quality and reasoning20%1 favorable, 4 not, 5 authorsNeeds 5 accounts from 3 authors2 favorable, 1 not, 3 authorsOnly praise on record2 favorable, 0 not, 2 authors53%8 favorable, 7 not, 15 authors44%8 favorable, 10 not, 17 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 authors67%14 favorable, 7 not, 21 authors76%47 favorable, 15 not, 61 authors71%5 favorable, 2 not, 7 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 outputOnly concerns on record0 favorable, 1 not, 1 authorNo accounts yetNeeds 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 authors67%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 authors33%2 favorable, 4 not, 6 authors57%4 favorable, 3 not, 7 authorsNo accounts yet46%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 contextOnly concerns on record0 favorable, 1 not, 1 authorNo accounts yetOnly 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 authors29%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 yet40%2 favorable, 3 not, 5 authorsNo accounts yet75%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 experienceOnly 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 author25%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, 3 not, 3 authors33%5 favorable, 10 not, 15 authorsNo accounts yet17%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
CostOnly concerns on record0 favorable, 9 not, 9 authorsOnly concerns on record0 favorable, 1 not, 1 authorNeeds 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 author69%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 authors76%16 favorable, 5 not, 21 authors35%8 favorable, 15 not, 23 authors71%5 favorable, 2 not, 7 authorsNeeds 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
SpeedOnly 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 yet74%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 authors33%3 favorable, 6 not, 9 authors20%3 favorable, 12 not, 15 authorsNeeds 5 accounts from 3 authors1 favorable, 1 not, 2 authors33%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, 2 not, 2 authorsNo accounts yetOnly 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 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 authorsOnly concerns on record0 favorable, 7 not, 7 authorsOnly concerns on record0 favorable, 4 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 17 accounts behind Muse Wonder's figures

GILD searched Hacker News, GitHub, Reddit, X and the web for accounts that name Muse Wonder.

Quality and reasoning 20%

  • Unfavorable
    Muse Spark 1.3 (max): 32.2 Muse Wonder 1.0 (max): 31.7

    So, I tested Muse Wonder 1.0 on real work. Paweł Huryn, self-described AI PM who writes the Product Compass newsletter, Oct 13, 2026. Muse Wonder, the 1.0 release, at max effort on 105 bugs across 2 repos, over multiple runs.

  • Favorable
    Muse Wonder (Max) gained +19 pts and 9 places to #2

    Muse Wonder (Max) enters Code Arena: WebDev and Text Arena. Arena, the public human-preference leaderboard, self-described, Oct 13, 2026. Muse Wonder (Max) in Arena's Text Arena and Code Arena: WebDev voting.

  • Unfavorable
    Wonder finished with 80 passes, 11 failures and seven errors out of 98 tasks

    Benchmark notes: Wonder behind Spark 1.3. Correct_Tomato1871, author of the open-source MindTrial reasoning benchmark, on Reddit, self-described, Oct 27, 2026. Meta Muse Wonder through OpenRouter in MindTrial at max reasoning effort, with Python execution capped at ten calls a task, on 98 tasks.

  • Unfavorable
    Other models, like Muse Wonder and Argon, are a total waste of time.

    Kimi K3.1 Pro and K3.1 Pro Highspeed. a3nz3g, Hacker News commenter, self-described, Oct 24, 2026. Muse Wonder for software development, set against Opus and Sol.

  • Favorable
    These three are different enough that their insights are very complementary.

    LLMs are making formal software verification feasible at a much larger scale. simondotau, Hacker News commenter, self-described, Oct 23, 2026. Muse Wonder in a three-model group with Opus 5.5 and Grok 4.7 that refines a detailed plan before any code is written.

  • Unfavorable
    Muse Wonder isn't much better than Muse Spark 1.3[1]

    Muse Wonder. dom96, Hacker News commenter who built the Killswitch programming-language benchmark, self-described, Oct 12, 2026. Muse Wonder on his Killswitch programming-language benchmark with a $5 budget.

  • Unfavorable
    It's much worse than Opus 5.5. IMO it's closer to Sonnet or Haiku for this test.

    Muse Wonder. jjcm, Hacker News commenter who runs image-to-HTML tests, self-described, Oct 12, 2026. Muse Wonder (high) on an image-to-HTML conversion against Opus 5.5 (high).

Tool use and structured output Only concerns on record

  • Favorable
    Python execution itself is mostly successful: 490 of 524 calls succeed

    Benchmark notes: Wonder behind Spark 1.3. Correct_Tomato1871, author of the open-source MindTrial reasoning benchmark, on Reddit, self-described, Oct 27, 2026. Meta Muse Wonder through OpenRouter in MindTrial at max reasoning effort, with Python execution capped at ten calls a task, on 98 tasks.

  • Unfavorable
    this looks like the model emitting a foreign tool-call syntax as text

    muse-code/muse-wonder-1.0 prints tool-call markup as plain text instead of making a tool call. DuncanBetts, oh-my-pi coding agent user, self-described, Oct 14, 2026. Muse Wonder (muse-code/muse-wonder-1.0) through the muse-code provider in oh-my-pi at xhigh thinking.

Long context Only concerns on record

  • Unfavorable
    I suspect its vision model isn't mature yet

    Muse Wonder. jjcm, Hacker News commenter who runs image-to-HTML tests, self-described, Oct 12, 2026. Muse Wonder (high) on an image-to-HTML conversion against Opus 5.5 (high).

Developer experience Only concerns on record

  • Unfavorable
    the benchmark scores for "Muse Wonder" on the main marketing page are actually for "Muse Wonder Full,"

    Muse Wonder. droidjj, Hacker News commenter, self-described, Oct 12, 2026. Muse Wonder on Meta's pricing page and Meta's launch page.

Cost Only concerns on record

  • Unfavorable
    and 50% more expensive. Multiple runs.

    So, I tested Muse Wonder 1.0 on real work. Paweł Huryn, self-described AI PM who writes the Product Compass newsletter, Oct 13, 2026. Muse Wonder, the 1.0 release, at max effort on 105 bugs across 2 repos, over multiple runs.

  • Unfavorable
    but way too expensive [0]

    Muse Wonder. XCSme, Hacker News commenter, self-described, Oct 13, 2026. Muse Wonder, citing an AI Benchy comparison page for meta-muse-wonder-max.

  • Unfavorable
    A lot of the tasks were failed because they exceeded the $5 budget though

    Muse Wonder. dom96, Hacker News commenter who built the Killswitch programming-language benchmark, self-described, Oct 12, 2026. Muse Wonder on his Killswitch programming-language benchmark with a $5 budget.

  • Unfavorable
    Two somewhat small prompts with Muse Wonder Max-contributor used 4% of my weekly quota and I quickly switched back.

    Muse Wonder. hugh4life, Hacker News commenter on the $15 Muse Code plan, self-described, Oct 12, 2026. Muse Wonder Max-contributor on the $15 Muse Code plan.

  • Unfavorable
    For me wonder burns so many more expensive tokens it's not worth using vs spark-contributor

    Benchmark notes: Wonder behind Spark 1.3. siberianmi, Reddit member in r/MetaMuseSpark, self-described, Oct 28, 2026. Muse Wonder, in reply to the MindTrial post on Meta Muse Wonder, against spark-contributor.

  • Unfavorable
    For both wonders - it is really simple to spend 5% of weekly limit (15% of 5h) in 10 minutes.

    Meta introduced Muse Wonder - new frontier model. mdn0, Reddit member in r/opencode, self-described, Oct 13, 2026. Muse Wonder and Muse Wonder Full ("both wonders") against a weekly and 5-hour usage limit.

  • Unfavorable
    i have the $5 subscription and one prompt with muse wonder and it exhausted my allowed compute.

    Meta introduced Muse Wonder - new frontier model. DandadanAsia, Reddit member in r/opencode on a $5 subscription, self-described, Oct 13, 2026. Muse Wonder on the author's $5 subscription, with the contributor discount on.

  • Unfavorable
    Muse Wonder came out, so I ran it live. It got its starter by turn 20 and reached Viridian City by turn 59, close to the fastest models. It made it into Viridian Forest on turn 208 and spent the last 792 turns there. It cost $96.06. Opus 5.5 is billed the same per token and beat Brock in 271 turns for $8.44.

    Muse Wonder cost $96 on Pokemon Red and never got past the first forest. VibeCodyH, a Reddit user who runs PokeBench, self-described, Oct 13, 2026. Muse Wonder on a six-hour live Pokemon Red run, against Claude Opus 5.5 at the same per-token price.

  • Unfavorable
    my 15$ subcription, In 4 prompts, 5hr limit reached and 27% weekly exhausted

    Meta introduced Muse Wonder, new frontier model. ApprehensiveEye7387, a Reddit user, self-described, Oct 13, 2026. Muse Wonder on a US$15 Muse subscription at the contributor tier.

Speed Only concerns on record

  • Unfavorable
    In my tests, it's similar to Spark 1.3, a bit slower

    So, I tested Muse Wonder 1.0 on real work. Paweł Huryn, self-described AI PM who writes the Product Compass newsletter, Oct 13, 2026. Muse Wonder, the 1.0 release, at max effort on 105 bugs across 2 repos, over multiple runs.

  • Favorable
    takes 16.9% less model-request time than Spark

    Benchmark notes: Wonder behind Spark 1.3. Correct_Tomato1871, author of the open-source MindTrial reasoning benchmark, on Reddit, self-described, Oct 27, 2026. Meta Muse Wonder through OpenRouter in MindTrial at max reasoning effort, with Python execution capped at ten calls a task, on 98 tasks.

Reliability Only concerns on record