Gemini 3.7 Flash vs Muse Spark 1.3
Full profiles: Gemini 3.7 Flash (Google) and Muse Spark 1.3 (Meta): every benchmark, price and rank.
Updated · Data from 9 sources
As of 24 Oct 2026, Gemini 3.7 Flash (high) and Muse Spark 1.3 (max) are neck and neck on quality (63.5 vs 67.1 on the BenchLeader Index, inside the ±5.6 margin of error), and Gemini 3.7 Flash (high) costs 1.3× less, which makes it the better buy for most workloads. Pick Gemini 3.7 Flash for multimodal (68 vs 66); pick Muse Spark 1.3 for agents & tools (66 vs 48).
Gemini 3.7 Flash benchmarks high Google
Muse Spark 1.3 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 Spark 1.3 | 65 vs 63 category score; Arena WebDev 1657 vs 1591 | Medium |
| Agents & tool use | Muse Spark 1.3 | 66 vs 48 category score; τ³-Banking (AA) 50.5% vs 32.8% | High |
| Maths | Either | 63 vs 63 category score; FrontierMath Tiers 1–3 71.6% vs 74.0% | Either |
| Reasoning | Muse Spark 1.3 | 77 vs 67 category score; CritPt 24.9% vs 14.3% | High |
| Knowledge | Muse Spark 1.3 | 73 vs 68 category score; AA-Omniscience 25 vs 26.5 | Medium |
| Long documents | Either | 66 vs 67 category score; AA-LCR 81.7% vs 83.0% | Either |
| Images and other media | Gemini 3.7 Flash | 68 vs 66 category score; Arena Vision 1314 vs 1308 | Medium |
| Chat quality (human preference) | Either | 68 vs 69 on Arena votes | Either |
| Lowest cost | Gemini 3.7 Flash | $1.50 vs $2.00 per 1M blended; agentic coding session $0.060 vs $0.092 | – |
| Fastest first answer | Gemini 3.7 Flash | 2.5 s (Gemini 3.7 Flash (high)) vs 90.1 s (Muse Spark 1.3 (max)) to the first answer token | – |
| High volume on a budget | Neither flagship | A smaller model is usually the better fit: Cheapest good LLMs, Fastest LLMs | – |
Key differences
- Gemini 3.7 Flash (high) and Muse Spark 1.3 (max) are neck and neck on quality (63.5 vs 67.1, within the ±5.6 margin).
- Gemini 3.7 Flash (high) is stronger in multimodal.
- Muse Spark 1.3 (max) is stronger in agents & tools, coding, composite, human preference, knowledge, long context, maths, reasoning.
- Gemini 3.7 Flash (high) is 1.3× cheaper ($1.50 vs $2.00 per 1M blended).
- Muse Spark 1.3 (max) streams 1.3× faster (116 vs 88 tokens per second).
At a glance
| Spec | Gemini 3.7 Flash | Muse Spark 1.3 |
|---|---|---|
| Developer | Meta | |
| Released | 13 Aug 2026 | 2 Sept 2026 |
| Context window (tokens) | 1,048,576 | 1,048,576 |
| Compared at | Gemini 3.7 Flash (high) | Muse Spark 1.3 (max) |
| Open weights | No | No |
| Price in / out / cached input per 1M | $0.750 / $3.75 / $0.075 | $1.25 / $4.25 / $0.150 |
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 3.7 Flash (high) | Muse Spark 1.3 (max) | Leader |
|---|---|---|---|
| Reasoning | 67.3 | 77.4 | Muse Spark 1.3 |
| Coding | 63.0 | 64.5 | Muse Spark 1.3 |
| Agents & tools | 47.5 | 65.6 | Muse Spark 1.3 |
| Maths | 63.3 | 63.4 | level |
| Knowledge | 68.0 | 72.8 | Muse Spark 1.3 |
| Human preference | 68.4 | 69.1 | level |
| Multimodal | 67.6 | 65.7 | Gemini 3.7 Flash |
| Long context | 65.9 | 66.6 | level |
| Composite | 73.2 | 83.3 | Muse Spark 1.3 |
Where sources disagree
Across the 45 benchmarks both have, Gemini 3.7 Flash leads 15, Muse Spark 1.3 leads 30. Every overall index that rates both puts Muse Spark 1.3 ahead.
| Overall index | Gemini 3.7 Flash (high) | Muse Spark 1.3 (max) | Leader |
|---|---|---|---|
| BenchLeader Index | 63.5 | 67.1 | neck and neck |
| AA Intelligence Index v4.3.2 | 39.1 | 48.1 | Muse Spark 1.3 |
| Arena Text | 1490 | 1496 | Muse Spark 1.3 |
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 | Gemini 3.7 Flash (high) | Muse Spark 1.3 (max) |
|---|---|---|
| Blended price per 1M tokens | $1.50 | $2.00 |
| Input / output per 1M | $0.750 / $3.75 | $1.25 / $4.25 |
| Cached input per 1M | $0.075 | $0.150 |
| Price per task: chat reply | $0.0014 | $0.0018 |
| Price per task: summarize a 30-page report | $0.011 | $0.018 |
| Price per task: code edit | $0.010 | $0.014 |
| Price per task: agentic coding session | $0.060 | $0.092 |
| Price per task: structured extraction | $0.0023 | $0.0034 |
| Cost to run a full benchmark suite | – | $1.60 |
| Output speed | 88 tok/s | 116 tok/s |
| Time to first answer | 2.5 s | 90.1 s |
| Time to a complete answer | – | 94.4 s |
Each model is compared at its best-ranked reasoning-effort setting. Gemini 3.7 Flash (high) scores 63.5 and takes 2 s to its first answer token; Gemini 3.7 Flash (medium) scores 63.1 in 2 s, Gemini 3.7 Flash (low) scores 60.3 in 2 s. Muse Spark 1.3 (max) scores 67.1 and takes 90 s to its first answer token; Muse Spark 1.3 (xhigh) scores 64.9 in 30 s, Muse Spark 1.3 scores 59.8 in 3 s. 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
113 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 | Gemini 3.7 Flash (high) | Muse Spark 1.3 (max) |
|---|---|---|---|
| BenchLeader Index | BenchLeader | 63.5 | 67.1 |
| Agents & tools score | BenchLeader | 47.5 | 65.6 |
| Coding score | BenchLeader | 63.0 | 64.5 |
| Composite score | BenchLeader | 73.2 | 83.3 |
| Human preference score | BenchLeader | 68.4 | 69.1 |
| Knowledge score | BenchLeader | 68.0 | 72.8 |
| Long context score | BenchLeader | 65.9 | 66.6 |
| Maths score | BenchLeader | 63.3 | 63.4 |
| Multimodal score | BenchLeader | 67.6 | 65.7 |
| Reasoning score | BenchLeader | 67.3 | 77.4 |
| Blended price $/M | BenchLeader | $1.50 | $2.00 |
| Output speed | BenchLeader | 88 tok/s | 116 tok/s |
| Time to first answer | BenchLeader | 2.5 s | 90.1 s |
| Context window | BenchLeader | 1,048,576 tokens | 1,048,576 tokens |
| Reasoning | |||
| GPQA Diamond | Epoch AI Benchmarking Hub | 94.8% | – |
| Arena Hard Prompts | Arena (LMArena) | 1509 | 1517 |
| LiveBench 2.0 Reasoning | LiveBench | 87.8%† | 89.7%† |
| LiveBench 1.0 Reasoning | LiveBench | 87.8% | 89.7%† |
| GPQA Diamond (AA) | Artificial Analysis | 94.5% | 93.5% |
| Humanity's Last Exam (AA) | Artificial Analysis | 47.9% | 48.7% |
| GPQA Diamond (Vals) | Vals AI | 93.9% | – |
| ARC-AGI-1 | ARC Prize | 95.5% | – |
| ARC-AGI-2 | ARC Prize | 84.6% | – |
| CritPt | Artificial Analysis | 14.3% | 24.9% |
| MysteryMechanism | Vals AI | – | 36.0% |
| Chess Puzzles | Epoch AI Benchmarking Hub | 66.0% | 37.0% |
| Mystery Game Puzzles | Epoch AI Benchmarking Hub | 37.0% | 25.0% |
| LMCA | Epoch AI Benchmarking Hub | 50.4% | 53.9%† |
| DTBench | Epoch AI Benchmarking Hub | 96.8% | 96.5%† |
| ForecastBench | ForecastBench | 66.2% | – |
| BTF-3 | Epoch AI Benchmarking Hub | – | 14.1%† |
| Coding | |||
| SciCode | SciCode | 57.2% | 58.8% |
| FrontierCode | Cognition | 43.6%† | – |
| Arena Coding | Arena (LMArena) | 1520 | 1536 |
| Arena WebDev | Arena (LMArena) | 1591 | 1657 |
| LiveBench 2.0 Coding | LiveBench | 80.5%† | 90.2%† |
| LiveBench 1.0 Coding | LiveBench | 78.9% | 81.1%† |
| LiveCodeBench | Vals AI | 88.7% | – |
| IOI | Vals AI | 67.8% | 56.6% |
Show all 113 benchmarks
| Metric | Publisher | Gemini 3.7 Flash (high) | Muse Spark 1.3 (max) |
|---|---|---|---|
| Coding | |||
| SWE-bench (Vals) | Vals AI | 80.8% | – |
| Code Migration | Vals AI | 34.8% | 47.4% |
| ProgramBench | Vals AI | 0.0% | 2.5% |
| SWE-bench Multimodal | Vals AI | – | 43.1% |
| Vibe Code Bench 1-100 | Vals AI | – | 20.5% |
| Vibe Code Bench v1.1 | Vals AI | 70.4% | 85.9% |
| DeepSWE v1.1 | Epoch AI Benchmarking Hub | 65.3% | – |
| CursorBench | Cursor | – | 41.6% |
| ALE-Bench | Epoch AI Benchmarking Hub | 904.3 | 1688.3† |
| FrontierSWE | Epoch AI Benchmarking Hub | 20.3% | 25.8% |
| Terminal-Bench 4.0 (AA) | Artificial Analysis | 13.6% | 33.3% |
| Terminal-Bench 2.1 (AA) | Artificial Analysis | 85.8% | 84.3% |
| Startrise Frontend | Startrise | – | 74.7%† |
| FrontierCode 1.1 (AA) | Artificial Analysis | – | 40.6% |
| Agents & tools | |||
| Terminal-Bench | Terminal-Bench | 11.2% | 14.6%† |
| Remote Labor Index | Scale AI / CAIS | 5.0%† | – |
| APEX-Agents | Mercor | 67.8%† | 47.6% |
| Arena Agent | Arena (LMArena) | -1 | 3.4 |
| LiveBench Long Agentic | LiveBench | 28.3%† | 40.4%† |
| LiveBench Browser | LiveBench | 56.0%† | 80.0%† |
| LiveBench Agentic Coding | LiveBench | 58.3% | 64.1%† |
| Terminal-Bench 2.1 (Vals) | Vals AI | 77.5% | 79.0% |
| HiL-Bench | Scale AI SEAL | – | 66.9%† |
| τ³-Banking (AA) | Artificial Analysis | 32.8% | 50.5% |
| ITBench SRE (AA) | Artificial Analysis | – | 33.2% |
| Analyst Agent (AA) | Artificial Analysis | 60.0% | 37.5% |
| CUA-bench | Vals AI | – | 5.8% |
| CyberBench | Vals AI | 43.8% | 72.7% |
| Finance Agent v2 | Vals AI | 59.0% | 60.0% |
| Harvey's Legal Agent Benchmark v1 | Vals AI | 8.8% | 23.8% |
| Legal Research Bench | Vals AI | 34.6% | 55.3% |
| SkillsBench | Vals AI | 65.9% | – |
| SREBench | Vals AI | 4.6% | 3.8% |
| Tax Agent Bench | Vals AI | 22.8% | 42.4% |
| Terminal-Bench 4.0 (Vals) | Vals AI | 12.1% | 24.8% |
| Terminal-Bench Science | Vals AI | 7.1% | 10.0% |
| AutomationBench | Artificial Analysis | 62.0% | 57.9% |
| GDP.pdf (AA) | Artificial Analysis | 23.6% | 26.6% |
| Harvey LAB-AA v1.1 | Harvey | – | 8.9% |
| EnterpriseOps-Gym | Artificial Analysis | 50.4%† | – |
| AA-Briefcase v1.1 | Artificial Analysis | – | 1581 |
| Terminal-Bench-Science 0.1 (AA) | Artificial Analysis | – | 10.9% |
| FACTS Search | 80.9%† | – | |
| Maths | |||
| FrontierMath Tiers 1–3 | Epoch AI Benchmarking Hub | 71.6% | 74.0% |
| FrontierMath Tier 4 | Epoch AI Benchmarking Hub | 36.6% | 46.3% |
| OTIS Mock AIME | Epoch AI Benchmarking Hub | 97.2% | 99.2%† |
| ProofBench | Vals AI | 58.0%† | 58.0% |
| LiveBench Mathematics | LiveBench | 93.5% | 96.0%† |
| Arena Maths | Arena (LMArena) | 1505 | 1510 |
| Knowledge | |||
| SimpleQA Verified | Epoch AI Benchmarking Hub | 69.2% | – |
| LiveBench 2.0 Data Analysis | LiveBench | 68.0%† | 79.6%† |
| LiveBench Research | LiveBench | 76.5%† | 68.6%† |
| LiveBench 1.0 Data Analysis | LiveBench | 68.0% | 79.6%† |
| AA-Omniscience | Artificial Analysis | 26.5 | 25 |
| MMLU-Pro | Vals AI | 90.1% | – |
| LegalBench | Vals AI | 87.3% | – |
| TaxEval | Vals AI | 74.7% | – |
| PRBench Finance | Scale AI SEAL | – | 59.5%† |
| PRBench Legal | Scale AI SEAL | – | 61.6%† |
| Excel Modeling Benchmark | Vals AI | 71.3% | 67.4% |
| MedCode | Vals AI | 53.4% | – |
| MedScribe | Vals AI | 83.9% | – |
| DrugDiscoveryBench | Scale AI SEAL | – | 62.2%† |
| GDP.pdf | Epoch AI Benchmarking Hub | 23.8% | 27.6%† |
| AA-Omniscience: accuracy | Artificial Analysis | 55.3% | 43.6% |
| AA-Omniscience: non-hallucination | Artificial Analysis | 35.5% | 67.1% |
| Instruction following | |||
| LiveBench Language | LiveBench | 85.5% | 82.8%† |
| LiveBench Instruction Following | LiveBench | 79.9% | 78.0%† |
| Arena Instruction Following | Arena (LMArena) | 1487 | 1485 |
| Human preference | |||
| Arena Text | Arena (LMArena) | 1490 | 1496 |
| Arena Creative Writing | Arena (LMArena) | 1492 | 1463 |
| Arena Multi-turn | Arena (LMArena) | 1489 | 1494 |
| Arena Longer Queries | Arena (LMArena) | 1501 | 1497 |
| Multimodal | |||
| Arena Vision | Arena (LMArena) | 1314 | 1308 |
| LiveBench Design | LiveBench | 73.2%† | 74.8%† |
| MMMU-Pro | Artificial Analysis | 85.5% | 82.0%† |
| MMMU-Pro (Vals) | Vals AI | 89.0% | – |
| MortgageTax | Vals AI | 66.7% | – |
| SAGE | Vals AI | 49.2% | – |
| AA-3D | Artificial Analysis | – | 1037 |
| Long context | |||
| AA-LCR | Artificial Analysis | 81.7% | 83.0% |
| Arena Document | Arena (LMArena) | – | 1468 |
| MLCR | Artificial Analysis | 12.2% | 13.9% |
| Composite | |||
| Epoch Capabilities Index | Epoch AI Benchmarking Hub | 158.0† | 157.2† |
| LiveBench 2.0 | LiveBench | 67.2%† | 74.8%† |
| LiveBench 1.0 | LiveBench | 78.8% | 81.6%† |
| AA Intelligence Index v4.3.2 | Artificial Analysis | 39.1 | 48.1 |
| Vals RSI Index | Vals AI | 18.3% | 19.6% |
Data as of 2026-10-24. Best configuration of each model; every score links to its source on the model pages.
What changed
- Gemini 3.7 Flash (high): 2 new results (Harvey's Legal Agent Benchmark v1, Vals RSI Index).
- Muse Spark 1.3 (max): 3 new results (Harvey's Legal Agent Benchmark v1, Vals RSI Index, SWE-bench Multimodal); 1 score revision.
- Gemini 3.7 Flash (high): input price moved from $0.38/M to $0.75/M (97% up); output price moved from $1.88/M to $3.75/M (99% up).
- Gemini 3.7 Flash (high): 1 score revision; input price moved from $0.75/M to $0.38/M (49% down); output price moved from $3.75/M to $1.88/M (50% down).
- Muse Spark 1.3 (max): 1 score revision.
- Gemini 3.7 Flash (high): 1 new result (ForecastBench).
- Muse Spark 1.3 (max): 1 score revision.
- Gemini 3.7 Flash (high): BenchLeader Index 62.9 → 63.5.
- Gemini 3.7 Flash (high): BenchLeader Index 60.8 → 62.9.
- Gemini 3.7 Flash (high): 18 new results (AA Intelligence Index v4.3.2, GPQA Diamond (AA), Humanity's Last Exam (AA)…).
Related comparisons
- Gemini 3.7 Flash vs Claude Opus 5.5
- Gemini 3.7 Flash vs Gemini 4 Argon
- Gemini 3.7 Flash vs Muse Wonder Full
- Muse Spark 1.3 vs Claude Opus 5.5
- Muse Spark 1.3 vs Gemini 4 Argon
- Muse Spark 1.3 vs Muse Wonder Full
- Muse Spark 1.3 vs Claude Fable 5.1
- Gemini 3.5 Flash vs Muse Spark 1.3
Rankings: Best LLM overall · Best LLM for agents · Best cheap LLMs
Gemini 3.7 Flash vs Muse Spark 1.3: questions
- Is Gemini 3.7 Flash better than Muse Spark 1.3?
- Gemini 3.7 Flash (high) and Muse Spark 1.3 (max) are neck and neck on quality (63.5 vs 67.1, within the ±5.6 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.
- Which is cheaper, Gemini 3.7 Flash or Muse Spark 1.3, and will that change?
- Gemini 3.7 Flash is cheaper today: $1.50 against $2.00 per million tokens, blended at three input tokens per output token. No price change has been announced for either.
- Is Gemini 3.7 Flash better than Muse Spark 1.3 for coding?
- Muse Spark 1.3 scores higher in coding (65 vs 63 on the category index, where 50 is average). On Arena WebDev, the top shared coding benchmark, it is 1591 for Gemini 3.7 Flash against 1657 for Muse Spark 1.3.
- Is Gemini 3.7 Flash better than Muse Spark 1.3 for agents and tool use?
- Muse Spark 1.3 scores higher in agentic tasks (66 vs 48 on the category index, where 50 is average). On τ³-Banking (AA), the top shared agents & tools benchmark, it is 32.8% for Gemini 3.7 Flash against 50.5% for Muse Spark 1.3.
- Which is better for long documents?
- They are level on long-context benchmarks (66 vs 67). Both accept 1,048,576 tokens of context.
- Which has lower latency?
- Gemini 3.7 Flash (high) answers first: 2.5 s against 90.1 s to the first answer token, as Artificial Analysis measures it. Reasoning effort drives most of this: a higher setting thinks longer before it answers.
- Which is faster, Gemini 3.7 Flash or Muse Spark 1.3?
- Muse Spark 1.3 streams faster: 116 against 88 output tokens per second.
- Do independent benchmarks agree on Gemini 3.7 Flash vs Muse Spark 1.3?
- Across the 45 benchmarks both have, Gemini 3.7 Flash leads 15, Muse Spark 1.3 leads 30. Every overall index that rates both puts Muse Spark 1.3 ahead.
- When was Muse Spark 1.3 released?
- Muse Spark 1.3 was released on 2 Sept 2026.