MiniMax-M3.1-Flash vs Muse Wonder Full
Full profiles: MiniMax-M3.1-Flash (MiniMax) and Muse Wonder Full (Meta): every benchmark, price and rank.
Updated · Data from 5 sources
As of 21 Oct 2026, MiniMax-M3.1-Flash and Muse Wonder Full (max) are neck and neck on quality (61.9 vs 70.7, inside the ±10.4 margin of error) and close on price, so pick on the category that matters to you. Muse Wonder Full leads in every category we measure both in.
MiniMax-M3.1-Flash benchmarks MiniMax
Muse Wonder Full benchmarks max MetaOpen in the comparison toolWhich to pick for…
The pick's numbers come first. Category scores on the BenchLeader scale (50 is the average model, 15 points one standard deviation). High confidence means a lead of half a standard deviation or more; under one point is called either.
| Use case | Pick | Why | Confidence |
|---|---|---|---|
| Coding | Muse Wonder Full | 72 vs 63 category score; Arena WebDev 1726 vs 1588 | High |
| Reasoning | Muse Wonder Full | 95 vs 78 category score; CritPt 32.9% vs 22.3% | High |
| Knowledge | Muse Wonder Full | 71 vs 69 category score; AA-Omniscience 30.1 vs 15.6 | Medium |
| Long documents | Muse Wonder Full | 67 vs 65 category score; AA-LCR 83.7% vs 79.7% | Medium |
| High volume on a budget | Neither flagship | A smaller model is usually the better fit: Cheapest good LLMs, Fastest LLMs | – |
Key differences
- MiniMax-M3.1-Flash and Muse Wonder Full (max) are neck and neck on quality (61.9 vs 70.7, within the ±10.4 margin).
- MiniMax-M3.1-Flash is stronger in multimodal.
- Muse Wonder Full (max) is stronger in coding, composite, knowledge, long context, reasoning.
At a glance
| Spec | MiniMax-M3.1-Flash | Muse Wonder Full |
|---|---|---|
| Developer | MiniMax | Meta |
| Released | 19 Oct 2026 | 12 Oct 2026 |
| Context window (tokens) | 1,000,000 | 1,000,000 |
| Compared at | MiniMax-M3.1-Flash | Muse Wonder Full (max) |
| Open weights | No | No |
| Price in / out / cached input per 1M | $0.150 / $0.600 / $0.015 | – |
Category by category
Category scores on the BenchLeader scale: 50 is the average evaluated model, 15 points is one standard deviation. A gap under one point is called level.
| Category | MiniMax-M3.1-Flash | Muse Wonder Full (max) | Leader |
|---|---|---|---|
| Reasoning | 77.6 | 95.0 | Muse Wonder Full |
| Coding | 62.5 | 72.2 | Muse Wonder Full |
| Knowledge | 68.5 | 71.3 | Muse Wonder Full |
| Multimodal | 62.2 | – | not comparable |
| Long context | 64.9 | 67.0 | Muse Wonder Full |
| Composite | 66.5 | 92.1 | Muse Wonder Full |
Where sources disagree
Across the 19 benchmarks both have, MiniMax-M3.1-Flash leads 2, Muse Wonder Full leads 17. Every overall index that rates both puts Muse Wonder Full ahead.
| Overall index | MiniMax-M3.1-Flash | Muse Wonder Full (max) | Leader |
|---|---|---|---|
| BenchLeader Index | 61.9 | 70.7 | neck and neck |
| AA Intelligence Index v4.3.2 | 42.7 | 55.8 | Muse Wonder Full |
| Vals Index | 53.8 | 66.8 | Muse Wonder Full |
Each publisher runs its own tasks, harnesses and effort settings, so their overall verdicts can differ; BenchLeader reconciles them on one scale. † measured at another effort setting of the same model (the publisher did not test the one compared here).
Price, speed and latency
List prices blended at three input tokens per output token. Per-task prices use the token counts on the methodology page; suite cost is what Artificial Analysis paid to run its whole Intelligence Index.
| Measure | MiniMax-M3.1-Flash | Muse Wonder Full (max) |
|---|---|---|
| Blended price per 1M tokens | $0.262 | – |
| Input / output per 1M | $0.150 / $0.600 | – / – |
| Cached input per 1M | $0.015 | – |
| Price per task: chat reply | $0.0002 | – |
| Price per task: summarize a 30-page report | $0.0022 | – |
| Price per task: code edit | $0.0018 | – |
| Price per task: agentic coding session | $0.011 | – |
| Price per task: structured extraction | $0.0004 | – |
| Cost to run a full benchmark suite | $0.220 | – |
| Output speed | 105 tok/s | – |
| Time to first answer | 20.5 s | – |
| Time to a complete answer | 25.3 s | – |
Each model is compared at its best-ranked reasoning-effort setting. MiniMax-M3.1-Flash scores 61.9 and takes 20 s to its first answer token. Muse Wonder Full (max) scores 70.7. Higher effort means more thinking before the answer: better scores, longer waits and more tokens billed. How reasoning effort changes scores and cost.
Every benchmark
47 benchmarks, grouped by category; each name links to the board and its leaders.
| Metric | Publisher | MiniMax-M3.1-Flash | Muse Wonder Full (max) |
|---|---|---|---|
| BenchLeader Index | BenchLeader | 61.9 | 70.7 |
| Coding score | BenchLeader | 62.5 | 72.2 |
| Composite score | BenchLeader | 66.5 | 92.1 |
| Knowledge score | BenchLeader | 68.5 | 71.3 |
| Long context score | BenchLeader | 64.9 | 67.0 |
| Multimodal score | BenchLeader | 62.2 | – |
| Reasoning score | BenchLeader | 77.6 | 95.0 |
| Blended price $/M | BenchLeader | $0.262 | – |
| Output speed | BenchLeader | 105 tok/s | – |
| Time to first answer | BenchLeader | 20.5 s | – |
| Context window | BenchLeader | 1,000,000 tokens | 1,000,000 tokens |
| Reasoning | |||
| LiveBench 2.0 Reasoning | LiveBench | 82.9% | – |
| Humanity's Last Exam (AA) | Artificial Analysis | 48.0% | 53.6% |
| CritPt | Artificial Analysis | 22.3% | 32.9% |
| MysteryMechanism | Vals AI | – | 35.1% |
| Coding | |||
| Arena WebDev | Arena (LMArena) | 1588 | 1726 |
| LiveBench 2.0 Coding | LiveBench | 83.9% | – |
| SciCode (AA) | Artificial Analysis | 53.4% | 62.6% |
| IOI | Vals AI | – | 79.8% |
| Code Migration | Vals AI | – | 61.0% |
| ProgramBench | Vals AI | – | 0.5% |
| Vibe Code Bench 1-100 | Vals AI | – | 34.0% |
| Vibe Code Bench v1.1 | Vals AI | 73.9% | 86.0% |
| Terminal-Bench 4.0 (AA) | Artificial Analysis | 25.8% | 57.1% |
| FrontierCode 1.1 (AA) | Artificial Analysis | 38.6% | 44.9% |
| Agents & tools | |||
| LiveBench Long Agentic | LiveBench | 34.7% | – |
| LiveBench Browser | LiveBench | 92.0% | – |
| GDPval-AA v2.1 | Artificial Analysis | 47.9% | 67.8% |
| CyberBench | Vals AI | – | 73.6% |
| Finance Agent v2 | Vals AI | – | 59.1% |
| Harvey's Legal Agent Benchmark | Vals AI | 7.5% | 23.3% |
| Legal Research Bench | Vals AI | 34.1% | 53.4% |
| SREBench | Vals AI | – | 11.8% |
| Tax Agent Bench | Vals AI | 32.1% | 43.0% |
| Terminal-Bench 4.0 (Vals) | Vals AI | 25.3% | 58.1% |
| Terminal-Bench Science | Vals AI | – | 37.1% |
Show all 47 benchmarks
| Metric | Publisher | MiniMax-M3.1-Flash | Muse Wonder Full (max) |
|---|---|---|---|
| Agents & tools | |||
| AutomationBench | Artificial Analysis | 72.5% | 71.3% |
| GDP.pdf (AA) | Artificial Analysis | 20.8% | 32.6% |
| Harvey LAB-AA v1.1 | Harvey | – | 13.1% |
| AA-Briefcase v1.1 | Artificial Analysis | 1474 | 1729 |
| Terminal-Bench-Science 0.1 (AA) | Artificial Analysis | 3.3% | – |
| Knowledge | |||
| LiveBench 2.0 Data Analysis | LiveBench | 71.4% | – |
| LiveBench Research | LiveBench | 72.7% | – |
| AA-Omniscience | Artificial Analysis | 15.6 | 30.1 |
| LegalBench | Vals AI | – | 87.4% |
| BioMysteryBench | Vals AI | – | 73.3% |
| Excel Modeling Benchmark | Vals AI | – | 71.9% |
| MedCode | Vals AI | – | 49.9% |
| MedScribe | Vals AI | – | 89.3% |
| Public Benefits Bench | Vals AI | – | 73.8% |
| AA-Omniscience: accuracy | Artificial Analysis | 56.2% | 43.2% |
| AA-Omniscience: non-hallucination | Artificial Analysis | 7.2% | 77.0% |
| Multimodal | |||
| LiveBench Design | LiveBench | 74.0% | – |
| MMMU-Pro | Artificial Analysis | 79.1% | – |
| Long context | |||
| AA-LCR | Artificial Analysis | 79.7% | 83.7% |
| Composite | |||
| LiveBench 2.0 | LiveBench | 73.1% | – |
| AA Intelligence Index v4.3.2 | Artificial Analysis | 42.7 | 55.8 |
| Vals Index | Vals AI | 53.8 | 66.8 |
Data as of 2026-10-21. Best configuration of each model; every score links to its source on the model pages.
What changed
- MiniMax-M3.1-Flash: 1 new result (Terminal-Bench-Science 0.1 (AA)).
- Muse Wonder Full (max): 1 new result (FrontierCode 1.1 (AA)).
- MiniMax-M3.1-Flash: BenchLeader Index 62.5 → 61.9.
- Muse Wonder Full (max): BenchLeader Index 68.6 → 70.7.
- MiniMax-M3.1-Flash: 16 new results (FrontierCode 1.1 (AA), Arena WebDev, LiveBench 2.0…).
- Muse Wonder Full (max): 1 new result (Arena WebDev); 2 score revisions.
- MiniMax-M3.1-Flash: first results.
- Muse Wonder Full (max): 21 new results (IOI, LegalBench, Vals Index…).
- Muse Wonder Full (max): 1 new result (Harvey LAB-AA v1.1).
- Muse Wonder Full (max): first results.
Related comparisons
- MiniMax-M3.1-Flash vs Claude Opus 5.5
- MiniMax-M3.1-Flash vs Gemini 4 Argon
- MiniMax-M3.1-Flash vs GPT-6 Astra
- Muse Wonder Full vs Claude Opus 5.5
- Muse Wonder Full vs Gemini 4 Argon
- Muse Wonder Full vs GPT-6 Astra
- Muse Wonder Full vs Claude Fable 5.1
- MiniMax-M3.1-Flash vs Claude Fable 5.1
Rankings: Best LLM overall · Best LLM for coding · Best LLM for agents · Best cheap LLMs
MiniMax-M3.1-Flash vs Muse Wonder Full: questions
- Is MiniMax-M3.1-Flash better than Muse Wonder Full?
- MiniMax-M3.1-Flash and Muse Wonder Full (max) are neck and neck on quality (61.9 vs 70.7, within the ±10.4 margin). The BenchLeader Index combines every independent quality benchmark; the two are within the margin of error as of 2026-10-21, so check the category scores for your use.
- Is MiniMax-M3.1-Flash better than Muse Wonder Full for coding?
- Muse Wonder Full scores higher in coding (72 vs 63 on the category index, where 50 is average). On Arena WebDev, the top shared coding benchmark, it is 1588 for MiniMax-M3.1-Flash against 1726 for Muse Wonder Full.
- Which is better for long documents?
- Muse Wonder Full scores higher on long-context benchmarks (67 vs 65). Both accept 1,000,000 tokens of context.
- Do independent benchmarks agree on MiniMax-M3.1-Flash vs Muse Wonder Full?
- Across the 19 benchmarks both have, MiniMax-M3.1-Flash leads 2, Muse Wonder Full leads 17. Every overall index that rates both puts Muse Wonder Full ahead.
- When was MiniMax-M3.1-Flash released?
- MiniMax-M3.1-Flash was released on 19 Oct 2026.