Gemini 3.1 Pro vs Muse Wonder
As of 13 Oct 2026, Muse Wonder (max) leads on quality (66.3 vs 62.4 on the BenchLeader Index), but Gemini 3.1 Pro costs 1.8× less, so it is the better buy unless you need the extra quality.
Gemini 3.1 Pro 
Muse Wonder Key differences
- Muse Wonder (max) leads on quality: 66.3 vs 62.4.
- Gemini 3.1 Pro is stronger in agents & tools, coding, human preference, instruction following, long context, maths, multimodal.
- Muse Wonder (max) is stronger in composite, knowledge, reasoning.
- Gemini 3.1 Pro is 1.8× cheaper ($4.50 vs $8.00 per 1M blended).
- Gemini 3.1 Pro streams 1.6× faster (134 vs 85 tokens per second).
Choose Gemini 3.1 Pro if
- cost matters: $4.50 against $8.00 per million tokens blended
- you need fast output: 134 against 85 tokens per second
- the wait for the first word matters: 21.7 s against 60.8 s to first answer
Choose Muse Wonder (max) if
- reasoning is the priority (88 vs 69 on the category score)
- knowledge is the priority (73 vs 68 on the category score)
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 | Gemini 3.1 Pro | Muse Wonder (max) | Leader |
|---|---|---|---|
| Reasoning | 68.6 | 87.8 | Muse Wonder |
| Coding | 57.3 | – | not comparable |
| Agents & tools | 56.7 | – | not comparable |
| Maths | 61.0 | – | not comparable |
| Knowledge | 68.2 | 73.0 | Muse Wonder |
| Instruction following | 68.4 | – | not comparable |
| Human preference | 59.5 | – | not comparable |
| Multimodal | 64.9 | – | not comparable |
| Long context | 66.2 | 65.5 | level |
| Composite | 62.9 | 78.2 | Muse Wonder |
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 | Gemini 3.1 Pro | Muse Wonder (max) |
|---|---|---|
| Blended price per 1M tokens | $4.50 | $8.00 |
| Input / output per 1M | $2.00 / $12.00 | $4.00 / $20.00 |
| Price per task: chat reply | $0.0044 | $0.0076 |
| Price per task: summarise a 30-page report | $0.031 | $0.060 |
| Price per task: code edit | $0.030 | $0.054 |
| Price per task: agentic coding session | $0.168 | $0.320 |
| Price per task: structured extraction | $0.0064 | $0.012 |
| Cost to run a full benchmark suite | $1.30 | $4.52 |
| Output speed | 134 tok/s | 85 tok/s |
| Time to first answer | 21.7 s | 60.8 s |
| Time to a complete answer | 25.4 s | 66.7 s |
Every benchmark
| Metric | Gemini 3.1 Pro | Muse Wonder (max) |
|---|---|---|
| BenchLeader Index | 62.4 | 66.3 |
| Agents & tools score | 56.7 | – |
| Coding score | 57.3 | – |
| Composite score | 62.9 | 78.2 |
| Human preference score | 59.5 | – |
| Instruction following score | 68.4 | – |
| Knowledge score | 68.2 | 73.0 |
| Long context score | 66.2 | 65.5 |
| Maths score | 61.0 | – |
| Multimodal score | 64.9 | – |
| Reasoning score | 68.6 | 87.8 |
| Blended price $/M | $4.50 | $8.00 |
| Output speed | 134 tok/s | 85 tok/s |
| Time to first answer | 21.7 s | 60.8 s |
| Context window | 1.0M | 1.0M |
| GPQA Diamond | 94.1% | – |
| FrontierMath Tiers 1–3 | 59.6% | – |
| FrontierMath Tier 4 | 26.8% | – |
| OTIS Mock AIME | 95.6% | – |
| Humanity's Last Exam | 46.4% | – |
| Terminal-Bench | 80.2% | – |
| SimpleBench | 79.6% | – |
| SciCode | 58.9% | – |
| WeirdML | 72.1% | – |
| APEX-Agents | 35.3% | – |
| ProofBench | 26.0% | – |
| GSO-Bench | 22.6% | – |
| Epoch Capabilities Index | 154.8 | – |
| LMArena Text | 1487 | – |
| LMArena Hard Prompts | 1508 | – |
| LMArena Coding | 1522 | – |
| LMArena WebDev | 1447 | – |
| LMArena Vision | 1296 | – |
| LMArena Agent | -7.8 | – |
| LiveBench | – | 81.2% |
| LiveBench Reasoning | – | 90.6% |
| LiveBench Coding | – | 80.7% |
| LiveBench Agentic Coding | – | 62.7% |
| LiveBench Mathematics | – | 96.5% |
| LiveBench Data Analysis | – | 81.6% |
| LiveBench Language | – | 82.9% |
| LiveBench Instruction Following | – | 73.0% |
| AA Intelligence Index v4.3.2 | 29.7 | 52.4 |
| IFBench | 77.1% | – |
| AA-LCR | 82.0% | 80.7% |
| MMMU-Pro | 82.4% | – |
| AA-Omniscience | 31.9 | 25.5 |
| Terminal-Bench Hard | 53.8% | – |
| GPQA Diamond (AA) | 94.1% | – |
| Humanity's Last Exam (AA) | 47.0% | 50.1% |
| SciCode (AA) | 58.7% | 60.3% |
| τ²-Bench Telecom (AA) | 95.6% | – |
| AIME 2026 | 98.3% | – |
| HMMT February 2026 | 94.7% | – |
| MathArena Apex | 60.9% | – |
| MultiChallenge | 71.4% | – |
| PRBench Finance | 41.9% | – |
| MultiNRC | 64.7% | – |
| HiL-Bench | 35.3% | – |
| TutorBench | 53.0% | – |
| EQ-Bench 4 | 1142 | – |
| ARC-AGI-1 | 98.0% | – |
| ARC-AGI-2 | 77.1% | – |
| ARC-AGI-3 | 0.4% | – |
| CritPt | 17.7% | 28.3% |
| GDPval-AA v2.1 | 14.6% | 63.5% |
| τ³-Banking (AA) | 21.4% | – |
| ITBench SRE (AA) | 30.3% | – |
| Analyst Agent (AA) | 41.3% | – |
| APEX-Agents (AA) | 32.0% | – |
| FORTRESS | 29.8% | – |
| MASK | 42.4% | – |
| SWE Atlas: Codebase QnA | 13.5% | – |
| SWE Atlas: Refactoring | 33.8% | – |
| SWE Atlas: Test Writing | 29.8% | – |
| VTB | 29.0% | – |
| LMArena Maths | 1488 | – |
| LMArena Creative Writing | 1481 | – |
| LMArena Instruction Following | 1480 | – |
| LMArena Multi-turn | 1497 | – |
| LMArena Longer Queries | 1500 | – |
| LMArena Document | 1459 | – |
| Chess Puzzles | 55.0% | – |
| EBR-bench | 14.3% | – |
| BALROG | 57.0% | – |
| PostTrainBench | 22.0% | – |
| ExploitBench | 26.1% | – |
| CL-bench | 20.8% | – |
| CL-bench Life | 16.9% | – |
| METR Time Horizons | 77.0% | – |
| DeepSWE v1.1 | 11.7% | – |
| ForecastBench | 59.0% | – |
| GBAEval | 0.8% | – |
| ALE-Bench | 1160.6 | – |
| AlgoTune | 2.0 | – |
| Vending-Bench 2 | 911.2 | – |
| Blueprint-Bench 2 | 26.5% | – |
| GDP.pdf | 17.0% | – |
| Terminal-Bench 4.0 (AA) | 4.0% | 52.0% |
| Terminal-Bench 2.1 (AA) | 73.8% | – |
| AutomationBench | 35.4% | 68.1% |
| GDP.pdf | 17.8% | 30.6% |
| MLCR | 15.6% | – |
| Harvey LAB-AA v1.1 | 0.0% | – |
| EnterpriseOps-Gym | 42.2% | – |
| AA-Omniscience: accuracy | 54.9% | 41.1% |
| AA-Omniscience: non-hallucination | 49.1% | 73.5% |
| AA-Briefcase v1.1 | 456 | 1659 |
| Global-MMLU-Lite (AA) | 93.2% | – |
| BrowseComp | 31.2% | – |
| DeepSearchQA | 60.2% | – |
| FACTS Search | 83.7% | – |
Data as of 2026-10-13. Best configuration of each model; every score links to its source on the model pages.
Gemini 3.1 Pro vs Muse Wonder: questions
- Is Gemini 3.1 Pro better than Muse Wonder?
- Muse Wonder (max) leads on quality: 66.3 vs 62.4. The BenchLeader Index combines every independent quality benchmark; Muse Wonder (max) is ahead overall as of 2026-10-13, but check the category scores for your use.
- Which is cheaper, Gemini 3.1 Pro or Muse Wonder?
- Gemini 3.1 Pro is cheaper: $4.50 against $8.00 per million tokens, blended at three input tokens per output token.
- Which is faster, Gemini 3.1 Pro or Muse Wonder?
- Gemini 3.1 Pro streams faster: 134 against 85 output tokens per second.
- Which has the larger context window?
- Both accept 1.0M tokens of context.