Kimi K3.1 Pro vs Muse Spark
Full profiles: Kimi K3.1 Pro (Moonshot AI) and Muse Spark (Meta): every benchmark, price and rank.
Updated · Data from 8 sources
As of 24 Oct 2026, Kimi K3.1 Pro and Muse Spark are neck and neck on quality (66.8 vs 64.3, inside the ±6.9 margin of error) and close on price, so pick on the category that matters to you. Kimi K3.1 Pro leads in every category we measure both in.
Kimi K3.1 Pro benchmarks 
Muse Spark benchmarks Which 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 |
|---|---|---|---|
| Agents & tool use | Kimi K3.1 Pro | 67 vs 66 category score | Medium |
| Reasoning | Kimi K3.1 Pro | 81 vs 65 category score; CritPt 24.6% vs 11.3% | High |
| Knowledge | Kimi K3.1 Pro | 75 vs 63 category score; AA-Omniscience 29.5 vs 7.2 | High |
| Long documents | Kimi K3.1 Pro | 68 vs 64 category score; AA-LCR 86.3% vs 78.0% | Medium |
| Images and other media | Kimi K3.1 Pro | 67 vs 65 category score; MMMU-Pro 83.9% vs 80.5% | Medium |
| Chat quality (human preference) | – | Only Muse Spark has an Arena rating (68 category score) | Not comparable |
| 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 and Muse Spark are neck and neck on quality (66.8 vs 64.3, within the ±6.9 margin).
- Kimi K3.1 Pro is stronger in agents & tools, composite, knowledge, long context, multimodal, reasoning.
- Muse Spark is stronger in coding, human preference, instruction following, maths.
At a glance
| Spec | Kimi K3.1 Pro | Muse Spark |
|---|---|---|
| Developer | Moonshot AI | Meta |
| Released | 23 Oct 2026 | 8 Apr 2026 |
| Context window (tokens) | 1,048,576 | 262,144 |
| Compared at | Kimi K3.1 Pro | Muse Spark |
| Open weights | No | No |
| Price in / out / cached input per 1M | $2.00 / $10.00 / $0.200 | – |
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 | Muse Spark | Leader |
|---|---|---|---|
| Reasoning | 81.3 | 65.3 | Kimi K3.1 Pro |
| Coding | – | 65.0 | not comparable |
| Agents & tools | 67.3 | 66.1 | Kimi K3.1 Pro |
| Maths | – | 59.1 | not comparable |
| Knowledge | 74.8 | 63.3 | Kimi K3.1 Pro |
| Instruction following | – | 77.3 | not comparable |
| Human preference | – | 68.3 | not comparable |
| Multimodal | 67.0 | 64.5 | Kimi K3.1 Pro |
| Long context | 68.3 | 64.0 | Kimi K3.1 Pro |
| Composite | 75.8 | 64.5 | Kimi K3.1 Pro |
Where sources disagree
Across the 7 benchmarks both have, Kimi K3.1 Pro leads 7, Muse Spark leads 0. Every overall index that rates both puts Kimi K3.1 Pro ahead.
| Overall index | Kimi K3.1 Pro | Muse Spark | Leader |
|---|---|---|---|
| BenchLeader Index | 66.8 | 64.3 | neck and neck |
| AA Intelligence Index v4.3.2 | 55.1 | 31.3 | Kimi K3.1 Pro |
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 | Kimi K3.1 Pro | Muse Spark |
|---|---|---|
| Blended price per 1M tokens | $4.00 | – |
| Input / output per 1M | $2.00 / $10.00 | – / – |
| Cached input per 1M | $0.200 | – |
| Price per task: chat reply | $0.0038 | – |
| Price per task: summarize a 30-page report | $0.030 | – |
| Price per task: code edit | $0.027 | – |
| Price per task: agentic coding session | $0.160 | – |
| Price per task: structured extraction | $0.0060 | – |
| Cost to run a full benchmark suite | $2.11 | – |
| Output speed | 81 tok/s | – |
| Time to first answer | 27.7 s | – |
| Time to a complete answer | 33.9 s | – |
Each model is compared at its best-ranked reasoning-effort setting. Kimi K3.1 Pro scores 66.8 and takes 28 s to its first answer token. Muse Spark scores 64.3. 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
73 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 | Muse Spark |
|---|---|---|---|
| BenchLeader Index | BenchLeader | 66.8 | 64.3 |
| Agents & tools score | BenchLeader | 67.3 | 66.1 |
| Composite score | BenchLeader | 75.8 | 64.5 |
| Knowledge score | BenchLeader | 74.8 | 63.3 |
| Long context score | BenchLeader | 68.3 | 64.0 |
| Multimodal score | BenchLeader | 67.0 | 64.5 |
| Reasoning score | BenchLeader | 81.3 | 65.3 |
| Coding score | BenchLeader | – | 65.0 |
| Human preference score | BenchLeader | – | 68.3 |
| Instruction following score | BenchLeader | – | 77.3 |
| Maths score | BenchLeader | – | 59.1 |
| Blended price $/M | BenchLeader | $4.00 | – |
| Output speed | BenchLeader | 81 tok/s | – |
| Time to first answer | BenchLeader | 27.7 s | – |
| Context window | BenchLeader | 1,048,576 tokens | 262,144 tokens |
| Reasoning | |||
| GPQA Diamond | Epoch AI Benchmarking Hub | – | 89.8% |
| Humanity's Last Exam | Scale AI / CAIS | – | 40.6% |
| Arena Hard Prompts | Arena (LMArena) | – | 1506 |
| LiveBench 2.0 Reasoning | LiveBench | 91.1% | – |
| GPQA Diamond (AA) | Artificial Analysis | – | 88.4% |
| Humanity's Last Exam (AA) | Artificial Analysis | 52.5% | 40.7% |
| GPQA Diamond (Vals) | Vals AI | – | 89.7% |
| CritPt | Artificial Analysis | 24.6% | 11.3% |
| Coding | |||
| SciCode | SciCode | – | 51.5% |
| Arena Coding | Arena (LMArena) | – | 1529 |
| LiveBench 2.0 Coding | LiveBench | 81.8% | – |
| SciCode (AA) | Artificial Analysis | 60.8% | – |
| SWE-bench (Vals) | Vals AI | – | 74.4% |
| SWE-Bench Pro | Scale AI SEAL | – | 55.0% |
| Vibe Code Bench v1.1 | Vals AI | – | 19.7% |
| SWE-Bench Pro (private) | Scale AI SEAL | – | 55.0% |
| SWE Atlas: Codebase QnA | Scale AI SEAL | – | 24.2% |
| SWE Atlas: Test Writing | Scale AI SEAL | – | 31.1% |
| Terminal-Bench 4.0 (AA) | Artificial Analysis | 67.2% | – |
| Terminal-Bench 2.1 (AA) | Artificial Analysis | – | 62.2% |
| FrontierCode 1.1 (AA) | Artificial Analysis | 47.1% | – |
| Agents & tools | |||
| LiveBench Long Agentic | LiveBench | 49.5% | – |
| LiveBench Browser | LiveBench | 80.0% | – |
| Terminal-Bench Hard | Artificial Analysis | – | 45.5% |
| τ²-Bench Telecom (AA) | Artificial Analysis | – | 91.5% |
Show all 73 benchmarks
| Metric | Publisher | Kimi K3.1 Pro | Muse Spark |
|---|---|---|---|
| Agents & tools | |||
| MCP Atlas | Scale AI SEAL | – | 82.2% |
| GDPval-AA v2.1 | Artificial Analysis | 67.3% | – |
| Terminal-Bench 2.0 (Vals) | Vals AI | – | 59.5% |
| AutomationBench | Artificial Analysis | 73.3% | – |
| GDP.pdf (AA) | Artificial Analysis | 31.4% | – |
| AA-Briefcase v1.1 | Artificial Analysis | 1678 | – |
| CWE-Bench (AA) | Artificial Analysis | 60.8% | – |
| DeepSec-Bench (AA) | Artificial Analysis | 36.7% | – |
| CyberGym end-to-end (AA) | Artificial Analysis | 94.7% | – |
| Maths | |||
| OTIS Mock AIME | Epoch AI Benchmarking Hub | – | 88.9% |
| ProofBench | Vals AI | – | 17.0% |
| AIME (Vals) | Vals AI | – | 96.9% |
| Arena Maths | Arena (LMArena) | – | 1467 |
| Knowledge | |||
| LiveBench 2.0 Data Analysis | LiveBench | 79.1% | – |
| LiveBench Research | LiveBench | 77.9% | – |
| AA-Omniscience | Artificial Analysis | 29.5 | 7.2 |
| MMLU-Pro | Vals AI | – | 87.3% |
| LegalBench | Vals AI | – | 84.2% |
| CorpFin | Vals AI | – | 65.1% |
| TaxEval | Vals AI | – | 77.7% |
| PRBench Finance | Scale AI SEAL | – | 52.4% |
| PRBench Legal | Scale AI SEAL | – | 52.3% |
| MultiNRC | Scale AI SEAL | – | 59.0% |
| CaseLaw v2 | Vals AI | – | 63.1% |
| MedCode | Vals AI | – | 51.3% |
| MedScribe | Vals AI | – | 85.9% |
| AA-Omniscience: accuracy | Artificial Analysis | 51.0% | 49.6% |
| AA-Omniscience: non-hallucination | Artificial Analysis | 56.1% | 15.8% |
| Instruction following | |||
| IFBench | Artificial Analysis | – | 75.9% |
| MultiChallenge | Scale AI SEAL | – | 75.5% |
| TutorBench | Scale AI SEAL | – | 68.5% |
| Arena Instruction Following | Arena (LMArena) | – | 1465 |
| Human preference | |||
| Arena Text | Arena (LMArena) | – | 1489 |
| Arena Creative Writing | Arena (LMArena) | – | 1464 |
| Arena Multi-turn | Arena (LMArena) | – | 1494 |
| Arena Longer Queries | Arena (LMArena) | – | 1476 |
| Multimodal | |||
| Arena Vision | Arena (LMArena) | – | 1306 |
| LiveBench Design | LiveBench | 77.8% | – |
| MMMU-Pro | Artificial Analysis | 83.9% | 80.5% |
| MMMU-Pro (official) | MMMU | – | 80.4%† |
| MMMU-Pro (Vals) | Vals AI | – | 87.4% |
| Long context | |||
| AA-LCR | Artificial Analysis | 86.3% | 78.0% |
| Arena Document | Arena (LMArena) | – | 1467 |
| Composite | |||
| Epoch Capabilities Index | Epoch AI Benchmarking Hub | – | 152.0 |
| LiveBench 2.0 | LiveBench | 76.7% | – |
| AA Intelligence Index v4.3.2 | Artificial Analysis | 55.1 | 31.3 |
| AA Cyber Index | Artificial Analysis | 64.1 | – |
| Safety & honesty | |||
| FORTRESS | Scale AI SEAL | – | 20.2% |
Data as of 2026-10-24. Best configuration of each model; every score links to its source on the model pages.
What changed
- Kimi K3.1 Pro: BenchLeader Index 65.6 → 66.8.
- Kimi K3.1 Pro: 5 new results (FrontierCode 1.1 (AA), AA Cyber Index, CWE-Bench (AA)…).
- Kimi K3.1 Pro: first results.
- Muse Spark: 1 new result (PRBench Legal).
- Muse Spark: 1 new result (SWE Atlas: Codebase QnA).
- Muse Spark: 2 new results (PRBench Legal, MultiNRC).
- Muse Spark: 1 new result (PRBench Finance).
- Muse Spark: 1 new result (PRBench Finance).
- Muse Spark: 1 new result (TutorBench); 1 score revision.
- Muse Spark: BenchLeader Index 64.9 → 64.4.
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- Muse Spark vs Muse Wonder Full
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- Kimi K3 vs Muse Spark
Rankings: Best LLM overall · Best LLM for agents · Best cheap LLMs
Kimi K3.1 Pro vs Muse Spark: questions
- Is Kimi K3.1 Pro better than Muse Spark?
- Kimi K3.1 Pro and Muse Spark are neck and neck on quality (66.8 vs 64.3, within the ±6.9 margin). The BenchLeader Index combines every independent quality benchmark; the two are within the margin of error as of 2026-10-24, so check the category scores for your use.
- Is Kimi K3.1 Pro better than Muse Spark for agents and tool use?
- Kimi K3.1 Pro scores higher in agentic tasks (67 vs 66 on the category index, where 50 is average).
- Which is better for long documents?
- Kimi K3.1 Pro scores higher on long-context benchmarks (68 vs 64). Kimi K3.1 Pro accepts more context: 1,048,576 against 262,144 tokens for Muse Spark.
- Do independent benchmarks agree on Kimi K3.1 Pro vs Muse Spark?
- Across the 7 benchmarks both have, Kimi K3.1 Pro leads 7, Muse Spark leads 0. Every overall index that rates both puts Kimi K3.1 Pro ahead.
- When was Kimi K3.1 Pro released?
- Kimi K3.1 Pro was released on 23 Oct 2026.