Gemini 4 Argon vs Muse Spark 1.3
Gemini 4 Argon 
Muse Spark 1.3 Verdict
- Gemini 4 Argon (high) leads on quality: 70.0 vs 67.7.
- Gemini 4 Argon (high) is stronger in coding, composite, human preference, knowledge, maths, reasoning.
- Muse Spark 1.3 (max) is stronger in agents & tools, long context, multimodal.
- Muse Spark 1.3 (max) is 2.0× cheaper ($2.00 vs $4.00 per 1M blended).
| Metric | Gemini 4 Argon (high) | Muse Spark 1.3 (max) |
|---|---|---|
| BenchLeader Index | 70.0 | 67.7 |
| Agents & tools score | 67.5 | 70.3 |
| Coding score | 72.1 | 64.6 |
| Composite score | 89.2 | 84.1 |
| Human preference score | 73.2 | 69.4 |
| Knowledge score | 75.7 | 72.9 |
| Long context score | 65.0 | 66.8 |
| Maths score | 71.9 | 63.6 |
| Reasoning score | 82.0 | 78.1 |
| Multimodal score | – | 65.9 |
| Blended price $/M | $4.00 | $2.00 |
| Output speed | – | 175 tok/s |
| Time to first answer | – | 70.5 s |
| Context window | 1M | 1.0M |
| FrontierMath Tiers 1–3 | – | 74.0% |
| FrontierMath Tier 4 | – | 46.3% |
| SciCode | 61.8% | 58.8% |
| ProofBench | – | 58.0% |
| LMArena Text | 1525 | 1494 |
| LMArena Hard Prompts | 1551 | 1517 |
| LMArena Coding | 1562 | 1538 |
| LMArena WebDev | 1678 | 1657 |
| LMArena Vision | – | 1309 |
| LMArena Agent | 9.3 | 4 |
| AA Intelligence Index v4.3.2 | 52.6 | 48.1 |
| AA-LCR | 79.7% | 83.0% |
| AA-Omniscience | 42.4 | 25 |
| GPQA Diamond (AA) | – | 93.5% |
| Humanity's Last Exam (AA) | 57.1% | 48.7% |
| SciCode (AA) | 61.8% | 58.8% |
| IOI | 100.0% | 56.6% |
| LegalBench | 88.3% | – |
| Terminal-Bench 2.1 (Vals) | – | 79.0% |
| Vals Index | 68.9 | 58.2 |
| CritPt | 27.1% | 24.9% |
| GDPval-AA v2.1 | 56.3% | 59.0% |
| τ³-Banking (AA) | – | 50.5% |
| ITBench SRE (AA) | – | 33.2% |
| BioMysteryBench | 76.3% | – |
| Code Migration | 68.2% | 47.4% |
| CUA-bench | 4.8% | 5.8% |
| CyberBench | 77.9% | 72.7% |
| Excel Modeling Benchmark | 75.2% | 67.4% |
| Finance Agent v2 | 65.4% | 60.0% |
| Harvey's Legal Agent Benchmark | 19.6% | 23.8% |
| Legal Research Bench | 54.8% | 55.3% |
| MedCode | 58.8% | – |
| MedScribe | 87.4% | – |
| MysteryMechanism | 45.5% | 36.0% |
| ProgramBench | 2.5% | – |
| Public Benefits Bench | 69.8% | – |
| SAGE | 53.6% | – |
| SREBench | 44.3% | – |
| Tax Agent Bench | 76.2% | 72.4% |
| Terminal-Bench 4.0 (Vals) | 57.6% | 24.8% |
| Terminal-Bench Science | 44.3% | 10.0% |
| Vibe Code Bench 1-100 | – | 20.5% |
| Vibe Code Bench v1.1 | 91.9% | 85.9% |
| LMArena Maths | 1528 | 1502 |
| LMArena Creative Writing | 1519 | 1456 |
| LMArena Instruction Following | 1529 | 1483 |
| LMArena Multi-turn | 1553 | 1487 |
| LMArena Longer Queries | 1545 | 1497 |
| LMArena Document | – | 1468 |
| Chess Puzzles | – | 38.0% |
| Mystery Game Puzzles | – | 25.0% |
| CursorBench | – | 41.6% |
| FrontierSWE | 55.0% | – |
| Terminal-Bench 4.0 (AA) | 57.1% | 33.3% |
| Terminal-Bench 2.1 (AA) | – | 84.3% |
| AutomationBench | 77.5% | 57.9% |
| GDP.pdf | 21.8% | 26.6% |
| MLCR | – | 43.3% |
| Harvey LAB | – | 8.9% |
| AA-Omniscience: accuracy | 49.9% | 43.6% |
| AA-Omniscience: non-hallucination | 84.9% | 67.1% |
| AA-Briefcase v1.1 | 1488 | 1581 |
Data as of 2026-10-11. Best configuration of each model; every score links to its source on the model pages.
Gemini 4 Argon vs Muse Spark 1.3: questions
- Is Gemini 4 Argon better than Muse Spark 1.3?
- Gemini 4 Argon (high) leads on quality: 70.0 vs 67.7. The BenchLeader Index combines every independent quality benchmark; Gemini 4 Argon (high) is ahead overall as of 2026-10-11, but check the category scores for your use.
- Is Gemini 4 Argon better than Muse Spark 1.3 for coding?
- Gemini 4 Argon scores higher in coding (72 vs 65 on the category index, where 50 is average).
- Is Gemini 4 Argon better than Muse Spark 1.3 for agentic tasks?
- Muse Spark 1.3 scores higher in agentic tasks (70 vs 68 on the category index, where 50 is average).
- Which is cheaper, Gemini 4 Argon or Muse Spark 1.3?
- Muse Spark 1.3 is cheaper: $2.00 against $4.00 per million tokens, blended at three input tokens per output token.
- Which has the larger context window?
- Muse Spark 1.3 accepts more context: 1.0M against 1M tokens.