Kimi K3.1 Pro Together vs Muse Wonder Full
Full profiles: Kimi K3.1 Pro Together (Moonshot AI) and Muse Wonder Full (Meta): every benchmark, price and rank.
Updated · Data from 5 sources
As of 9 Nov 2026, Kimi K3.1 Pro Together and Muse Wonder Full are neck and neck on quality (60.5 vs 62.2 on the BenchLeader Index, inside the ±3.3 margin). Kimi K3.1 Pro Together leads in every category we measure both in.
Key facts (as of 9 Nov 2026)
- Kimi K3.1 Pro Together scores 60.5 on the BenchLeader Index and Muse Wonder Full scores 62.2 (BenchLeader, 9 Nov 2026).
Kimi K3.1 Pro Together benchmarks max Moonshot AI
Muse Wonder Full benchmarks max MetaAdd a third modelWhich 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 |
|---|---|---|---|
| Reasoning | Either | 67 vs 66 category score | Either |
| Knowledge | Kimi K3.1 Pro Together | 68 vs 63 category score | Medium |
| High volume on a budget | Neither flagship | A smaller model is usually the better fit: Cheapest good LLMs, Fastest LLMs | – |
Key differences
- Kimi K3.1 Pro Together (max) and Muse Wonder Full (max) are neck and neck on quality (60.5 vs 62.2, within the ±3.3 margin).
- Kimi K3.1 Pro Together (max) is stronger in knowledge, maths, reasoning.
- Muse Wonder Full (max) is stronger in agents & tools, coding, long context.
At a glance
| Spec | Kimi K3.1 Pro Together | Muse Wonder Full |
|---|---|---|
| Developer | Moonshot AI | Meta |
| Released | 23 Oct 2026 | 12 Oct 2026 |
| Context window (tokens) | – | 1,000,000 |
| Compared at | Kimi K3.1 Pro Together (max) | Muse Wonder Full (max) |
| Open weights | No | No |
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 | Kimi K3.1 Pro Together (max) | Muse Wonder Full (max) | Leader |
|---|---|---|---|
| Reasoning | 67.1 | 66.2 | level |
| Coding | – | 70.3 | not comparable |
| Agents & tools | – | 65.8 | not comparable |
| Maths | 65.8 | – | not comparable |
| Knowledge | 67.6 | 62.5 | Kimi K3.1 Pro Together |
| Long context | – | 66.6 | not comparable |
On one chart
Each domain on the index's own scale, where 50 is an average model. Click a domain to see the benchmarks behind it. Pick up to 5 models from the list.
Dashed: that model has no result on the axis it crosses; the line only joins its neighbours.
Not drawn, no result for these models: Instruction following, Multimodal, Human preference.
Where sources disagree
Across the 0 benchmarks both have, Kimi K3.1 Pro Together leads 0, Muse Wonder Full leads 0.
| Overall index | Kimi K3.1 Pro Together (max) | Muse Wonder Full (max) | Leader |
|---|---|---|---|
| BenchLeader Index | 60.5 | 62.2 | neck and neck |
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. Cost, tokens and time per benchmark task are measured: Artificial Analysis’ averages over its whole Intelligence Index run.
| Measure | Kimi K3.1 Pro Together (max) | Muse Wonder Full (max) |
|---|---|---|
| Output tokens per task (AA Index) | – | 88k |
| Of which reasoning | – | 55k |
Each model is compared at its best-ranked reasoning-effort setting. Kimi K3.1 Pro Together (max) scores 60.5. Muse Wonder Full (max) scores 62.2. 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
64 benchmarks, grouped by category; each name links to the board and its leaders. † measured at another effort setting of the same model, shown for reference and not counted as a win.
| Metric | Publisher | Kimi K3.1 Pro Together (max) | Muse Wonder Full (max) |
|---|---|---|---|
| BenchLeader Index | BenchLeader | 60.5 | 62.2 |
| Knowledge score | BenchLeader | 67.6 | 62.5 |
| Maths score | BenchLeader | 65.8 | – |
| Reasoning score | BenchLeader | 67.1 | 66.2 |
| Agents & tools score | BenchLeader | – | 65.8 |
| Coding score | BenchLeader | – | 70.3 |
| Long context score | BenchLeader | – | 66.6 |
| Context window | BenchLeader | – | 1,000,000 tokens |
| Reasoning | |||
| GPQA Diamond | Epoch AI Benchmarking Hub | 94.2% | – |
| Humanity's Last Exam (AA) | Artificial Analysis | – | 53.6% |
| HLE-Diamond (AA) | Artificial Analysis | – | 48.5% |
| CritPt | Artificial Analysis | – | 32.9% |
| CritPt v2 hard subset (AA) | Artificial Analysis | – | 56.5% |
| MysteryMechanism | Vals AI | – | 35.1% |
| Chess Puzzles | Epoch AI Benchmarking Hub | 45.0% | – |
| Mystery Game Puzzles | Epoch AI Benchmarking Hub | 42.0% | – |
| Coding | |||
| Arena WebDev | Arena (LMArena) | – | 1724 |
| SciCode (AA) | Artificial Analysis | – | 62.6% |
| IOI | Vals AI | – | 79.8% |
| Code Migration | Vals AI | – | 61.0% |
| Code Migration v1.1 | Vals AI | – | 62.8% |
| ProgramBench | Vals AI | – | 0.5% |
| SWE-bench Multimodal | Vals AI | – | 47.3% |
| Vibe Code Bench 1-100 | Vals AI | – | 34.0% |
| Vibe Code Bench v1.1 | Vals AI | – | 86.0% |
| Terminal-Bench 4.0 (AA) | Artificial Analysis | – | 57.1% |
| FrontierCode 1.1 (AA) | Artificial Analysis | – | 44.9% |
| FrontierCode 2.0 (AA) | Artificial Analysis | – | 37.8% |
| Agents & tools | |||
| Arena Agent | Arena (LMArena) | – | 9.1 |
| GDPval-AA v2.1, normalised score | Artificial Analysis | – | 67.8% |
| GDPval-AA v2.1 | Artificial Analysis | – | 1857 |
| CyberBench | Vals AI | – | 73.6% |
| Finance Agent v2 | Vals AI | – | 59.1% |
Show all 64 benchmarks
| Metric | Publisher | Kimi K3.1 Pro Together (max) | Muse Wonder Full (max) |
|---|---|---|---|
| Agents & tools | |||
| Finance Agent v2.1 | Vals AI | – | 67.6% |
| Harvey's Legal Agent Benchmark v1.1 | Vals AI | – | 23.3% |
| Harvey's Legal Agent Benchmark v1 | Vals AI | – | 21.7% |
| Legal Research Bench | Vals AI | – | 53.4% |
| Robo-bench | Vals AI | – | 10.4% |
| SREBench | Vals AI | – | 11.8% |
| Tax Agent Bench | Vals AI | – | 43.0% |
| Terminal-Bench 4.0 (Vals) | Vals AI | – | 58.1% |
| Terminal-Bench Science | Vals AI | – | 37.1% |
| AutomationBench | Artificial Analysis | – | 71.3% |
| GDP.pdf (AA) | Artificial Analysis | – | 32.6% |
| Harvey LAB-AA v1.1 | Harvey | – | 13.1% |
| AA-Briefcase v1.1 | Artificial Analysis | – | 1729 |
| GDPx | GDPx by SemiAnalysis | – | 9.0% |
| Terminal-Bench-Science 0.1 (AA) | Artificial Analysis | – | 37.1% |
| Maths | |||
| FrontierMath Tiers 1–3 | Epoch AI Benchmarking Hub | 78.3% | – |
| FrontierMath Tier 4 | Epoch AI Benchmarking Hub | 65.8% | – |
| OTIS Mock AIME | Epoch AI Benchmarking Hub | 100.0% | – |
| Knowledge | |||
| SimpleQA Verified | Epoch AI Benchmarking Hub | 62.2% | – |
| AA-Omniscience v1.1 | Artificial Analysis | – | 30.6 |
| LegalBench | Vals AI | – | 87.4% |
| BioMysteryBench | Vals AI | – | 73.3% |
| Excel Modeling Benchmark | Vals AI | – | 71.9% |
| Excel Modeling Benchmark v1.1 | Vals AI | – | 75.0% |
| MedCode | Vals AI | – | 49.9% |
| MedScribe | Vals AI | – | 89.3% |
| Public Benefits Bench v1.1 | Vals AI | – | 73.8% |
| AA-Omniscience v1.1: accuracy | Artificial Analysis | – | 41.0% |
| AA-Omniscience v1.1: non-hallucination | Artificial Analysis | – | 82.4% |
| Long context | |||
| AA-LCR v1.1 | Artificial Analysis | – | 83.7% |
| MLCR | Artificial Analysis | – | 22.2% |
| Composite | |||
| AA Intelligence Index v5.0 | Artificial Analysis | – | 50.1 |
| AA Intelligence Index v4.3.2 | Artificial Analysis | – | 55.8 |
| AA Progress Index v1 | Artificial Analysis | – | 343.2 |
| Vals Index | Vals AI | – | 66.8 |
| Vals Finance Index | Vals AI | – | 64.5% |
| Vals RSI Index | Vals AI | – | 24.4% |
| Vals Science Index | Vals AI | – | 48.5% |
| Vals Router Index | Vals AI | – | 66.8%† |
Data as of 2026-11-09. Best configuration of each model; every score links to its source on the model pages.
What changed
- Kimi K3.1 Pro Together (max): first results.
- Muse Wonder Full (max): 1 score revision.
- Muse Wonder Full (max): 1 score revision.
- Muse Wonder Full (max): 1 new result (Arena Agent).
- Muse Wonder Full (max): 6 new results (AA Intelligence Index v5.0, AA Progress Index v1, HLE-Diamond (AA)…); 2 score revisions.
- Muse Wonder Full (max): 1 new result (Terminal-Bench-Science 0.1 (AA)).
- Muse Wonder Full (max): 9 new results (Code Migration v1.1, Excel Modeling Benchmark v1.1, Finance Agent v2.1…).
- Muse Wonder Full (max): 1 new result (FrontierCode 1.1 (AA)).
- Muse Wonder Full (max): 1 new result (Arena WebDev); 2 score revisions.
- Muse Wonder Full (max): 21 new results (IOI, LegalBench, Vals Index…).
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Rankings: Best LLM overall · Best LLM for coding · Best LLM for agents · Best cheap LLMs
Kimi K3.1 Pro Together vs Muse Wonder Full: questions
- Is Kimi K3.1 Pro Together better than Muse Wonder Full?
- Kimi K3.1 Pro Together (max) and Muse Wonder Full (max) are neck and neck on quality (60.5 vs 62.2, within the ±3.3 margin). The BenchLeader Index combines every independent quality benchmark; the two are within the margin of error as of 9 Nov 2026, so check the category scores for your use.
- When was Kimi K3.1 Pro Together released?
- Kimi K3.1 Pro Together was released on 23 Oct 2026.