GPT-5.6 Sol vs Muse Spark Open 816B A42B
Full profiles: GPT-5.6 Sol (OpenAI) and Muse Spark Open 816B A42B (Meta): every benchmark, price and rank.
Updated · Data from 9 sources
As of 29 Oct 2026, GPT-5.6 Sol is ahead of Muse Spark Open 816B A42B on quality (65.4 vs 58.5 on the BenchLeader Index), but Muse Spark Open 816B A42B is 4.0× cheaper at $2.00 vs $8.00 per 1M tokens blended. GPT-5.6 Sol leads in every category we measure both in.
Key facts (as of 29 Oct 2026)
- GPT-5.6 Sol scores 65.4 on the BenchLeader Index and Muse Spark Open 816B A42B scores 58.5 (BenchLeader, 29 Oct 2026).
- GPT-5.6 Sol costs $8.00 per 1M tokens blended (list price, 29 Oct 2026).
- Muse Spark Open 816B A42B costs $2.00 per 1M tokens blended (list price, 29 Oct 2026).
- Of the 7 benchmarks both models have, GPT-5.6 Sol leads 6 (BenchLeader, 29 Oct 2026).
GPT-5.6 Sol benchmarks max OpenAI
Muse Spark Open 816B A42B benchmarks xhigh 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 | Either | 66 vs 66 category score; SciCode 57.1% vs 58.5% | Either |
| Maths | GPT-5.6 Sol | 71 vs 59 category score; FrontierMath Tiers 1–3 89.1% vs 69.8% | High |
| Reasoning | GPT-5.6 Sol | 65 vs 64 category score; GPQA Diamond 93.5% vs 88.6% | Medium |
| Knowledge | GPT-5.6 Sol | 64 vs 62 category score; SimpleQA Verified 69.7% vs 56.6% | Medium |
| Lowest cost | Muse Spark Open 816B A42B | $2.00 vs $8.00 per 1M blended; agentic coding session $0.092 vs $0.320 | – |
| High volume on a budget | Neither flagship | A smaller model is usually the better fit: Cheapest good LLMs, Fastest LLMs | – |
Key differences
- GPT-5.6 Sol (max) leads on quality: 65.4 vs 58.5.
- GPT-5.6 Sol (max) is stronger in agents & tools, coding, instruction following, knowledge, long context, maths, multimodal, reasoning.
- Muse Spark Open 816B A42B (xhigh) is 4.0× cheaper ($2.00 vs $8.00 per 1M blended).
At a glance
| Spec | GPT-5.6 Sol | Muse Spark Open 816B A42B |
|---|---|---|
| Developer | OpenAI | Meta |
| Released | 9 Jul 2026 | 15 Oct 2026 |
| Context window (tokens) | 1,050,000 | 1,048,576 |
| Compared at | GPT-5.6 Sol (max) | Muse Spark Open 816B A42B (xhigh) |
| Open weights | No | Yes |
| Price in / out / cached input per 1M | $4.00 / $20.00 / $0.400 | $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 | GPT-5.6 Sol (max) | Muse Spark Open 816B A42B (xhigh) | Leader |
|---|---|---|---|
| Reasoning | 65.1 | 63.6 | GPT-5.6 Sol |
| Coding | 65.8 | 65.5 | level |
| Agents & tools | 66.6 | – | not comparable |
| Maths | 70.8 | 59.4 | GPT-5.6 Sol |
| Knowledge | 63.9 | 62.2 | GPT-5.6 Sol |
| Instruction following | 71.1 | – | not comparable |
| Multimodal | 66.2 | – | not comparable |
| Long context | 66.9 | – | not comparable |
Where sources disagree
Across the 7 benchmarks both have, GPT-5.6 Sol leads 6, Muse Spark Open 816B A42B leads 1. Every overall index that rates both puts GPT-5.6 Sol ahead.
| Overall index | GPT-5.6 Sol (max) | Muse Spark Open 816B A42B (xhigh) | Leader |
|---|---|---|---|
| BenchLeader Index | 65.4 | 58.5 | GPT-5.6 Sol |
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 | GPT-5.6 Sol (max) | Muse Spark Open 816B A42B (xhigh) |
|---|---|---|
| Blended price per 1M tokens | $8.00 | $2.00 |
| Input / output per 1M | $4.00 / $20.00 | $1.25 / $4.25 |
| Cached input per 1M | $0.400 | $0.150 |
| Price per task: chat reply | $0.0076 | $0.0018 |
| Price per task: summarize a 30-page report | $0.060 | $0.018 |
| Price per task: code edit | $0.054 | $0.014 |
| Price per task: agentic coding session | $0.320 | $0.092 |
| Price per task: structured extraction | $0.012 | $0.0034 |
| Output speed | 85 tok/s | – |
| Time to first answer | 86.2 s | – |
| Time to a complete answer | 92.1 s | – |
Each model is compared at its best-ranked reasoning-effort setting. GPT-5.6 Sol (max) scores 65.4 and takes 86 s to its first answer token; GPT-5.6 Sol (xhigh) scores 64.2 in 22 s, GPT-5.6 Sol (high) scores 63.6 in 11 s. Muse Spark Open 816B A42B (xhigh) scores 58.5. 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
130 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 | GPT-5.6 Sol (max) | Muse Spark Open 816B A42B (xhigh) |
|---|---|---|---|
| BenchLeader Index | BenchLeader | 65.4 | 58.5 |
| Agents & tools score | BenchLeader | 66.6 | – |
| Coding score | BenchLeader | 65.8 | 65.5 |
| Instruction following score | BenchLeader | 71.1 | – |
| Knowledge score | BenchLeader | 63.9 | 62.2 |
| Long context score | BenchLeader | 66.9 | – |
| Maths score | BenchLeader | 70.8 | 59.4 |
| Multimodal score | BenchLeader | 66.2 | – |
| Reasoning score | BenchLeader | 65.1 | 63.6 |
| Blended price $/M | BenchLeader | $8.00 | $2.00 |
| Output speed | BenchLeader | 85 tok/s | – |
| Time to first answer | BenchLeader | 86.2 s | – |
| Context window | BenchLeader | 1,050,000 tokens | 1,048,576 tokens |
| Reasoning | |||
| GPQA Diamond | Epoch AI Benchmarking Hub | 93.5% | 88.6% |
| SimpleBench | SimpleBench | 64.8%† | – |
| Arena Hard Prompts | Arena (LMArena) | 1511† | – |
| LiveBench 1.0 Reasoning | LiveBench | 91.7% | – |
| GPQA Diamond (AA) | Artificial Analysis | 94.1% | – |
| Humanity's Last Exam (AA) | Artificial Analysis | 49.5% | – |
| GPQA Diamond (Vals) | Vals AI | 95.2% | – |
| EnigmaEval | Scale AI SEAL | 37.1%† | – |
| Kagi LLM Benchmark | Kagi LLM Benchmark | 67.0%† | – |
| ARC-AGI-1 | ARC Prize | 96.5% | – |
| ARC-AGI-2 | ARC Prize | 92.5% | – |
| ARC-AGI-3 | ARC Prize | 7.8% | – |
| CritPt | Artificial Analysis | 32.3% | – |
| CritPt v2 hard subset (AA) | Artificial Analysis | 56.0% | – |
| MysteryMechanism | Vals AI | 33.3% | – |
| Chess Puzzles | Epoch AI Benchmarking Hub | 59.0% | – |
| Mystery Game Puzzles | Epoch AI Benchmarking Hub | 58.0% | – |
| LMCA | Epoch AI Benchmarking Hub | 58.4% | – |
| DTBench | Epoch AI Benchmarking Hub | 95.5% | – |
| ForecastBench | ForecastBench | 65.5% | – |
| BTF-3 | Epoch AI Benchmarking Hub | 13.7% | – |
| Coding | |||
| SciCode | SciCode | 57.1% | 58.5% |
| WeirdML | WeirdML | 87.0% | – |
| FrontierCode | Cognition | 47.5%† | – |
| GSO-Bench | GSO-Bench | 76.5%† | – |
Show all 130 benchmarks
| Metric | Publisher | GPT-5.6 Sol (max) | Muse Spark Open 816B A42B (xhigh) |
|---|---|---|---|
| Coding | |||
| Arena Coding | Arena (LMArena) | 1533† | – |
| Arena WebDev | Arena (LMArena) | 1616† | – |
| LiveBench 1.0 Coding | LiveBench | 83.9% | – |
| SciCode (AA) | Artificial Analysis | 57.1% | – |
| LiveCodeBench | Vals AI | 82.6% | – |
| IOI | Vals AI | 91.2% | – |
| SWE-bench (Vals) | Vals AI | 96.2% | – |
| Code Migration | Vals AI | 52.9% | – |
| ProgramBench | Vals AI | 1.5% | – |
| Vibe Code Bench 1-100 | Vals AI | 20.0% | – |
| Vibe Code Bench v1.1 | Vals AI | 80.5% | – |
| SWE Atlas: Codebase QnA | Scale AI SEAL | 46.0%† | – |
| SWE Atlas: Test Writing | Scale AI SEAL | 45.9%† | – |
| MirrorCode | Epoch AI Benchmarking Hub | 20.0%† | – |
| Surface Evolver Bench | Epoch AI Benchmarking Hub | 93.1%† | – |
| DeepSWE v1.1 | Epoch AI Benchmarking Hub | 72.7% | – |
| CursorBench | Cursor | 41.7% | – |
| ALE-Bench | Epoch AI Benchmarking Hub | 2176.9 | 1590.1 |
| FrontierSWE | Epoch AI Benchmarking Hub | 32.2% | – |
| Terminal-Bench 4.0 (AA) | Artificial Analysis | 39.9% | – |
| Terminal-Bench 2.1 (AA) | Artificial Analysis | 88.0% | – |
| Startrise Frontend | Startrise | 66.2%† | – |
| Agents & tools | |||
| Terminal-Bench | Terminal-Bench | 37.3% | – |
| OSWorld-Verified 2.0 | OSWorld | 27.3% | – |
| APEX-Agents | Mercor | – | 33.4%† |
| Arena Agent | Arena (LMArena) | 4.8† | – |
| LiveBench Agentic Coding | LiveBench | 56.2% | – |
| Terminal-Bench Hard | Artificial Analysis | 65.9% | – |
| τ²-Bench Telecom (AA) | Artificial Analysis | 85.1% | – |
| Terminal-Bench 2.1 (Vals) | Vals AI | 85.8% | – |
| HiL-Bench | Scale AI SEAL | 32.3%† | – |
| τ³-bench Banking | τ²-bench | 46.9%† | – |
| τ³-Banking (AA) | Artificial Analysis | 44.3% | – |
| ITBench SRE (AA) | Artificial Analysis | 56.2% | – |
| Analyst Agent (AA) | Artificial Analysis | 47.5% | – |
| CUA-bench | Vals AI | 8.3% | – |
| CyberBench | Vals AI | 76.3% | – |
| Finance Agent v2 | Vals AI | 53.8% | – |
| Harvey's Legal Agent Benchmark v1 | Vals AI | 2.5% | – |
| Legal Research Bench | Vals AI | 48.1% | – |
| SkillsBench | Vals AI | 54.1% | – |
| SREBench | Vals AI | 30.5% | – |
| Tax Agent Bench | Vals AI | 31.1% | – |
| Terminal-Bench 4.0 (Vals) | Vals AI | 37.9% | – |
| Terminal-Bench Science | Vals AI | 20.0% | – |
| Time Horizon Index: KSP | Vals AI | 23.8% | – |
| Web Search Index | Vals AI | 43.6% | – |
| Arena Search | Arena (LMArena) | 1258† | – |
| BALROG | BALROG | 60.0% | – |
| PostTrainBench | Epoch AI Benchmarking Hub | 36.2% | – |
| GBAEval | Epoch AI Benchmarking Hub | 52.6%† | – |
| Vending-Bench 2 | Andon Labs | 9619.4† | – |
| AutomationBench | Artificial Analysis | 60.1% | – |
| GDP.pdf (AA) | Artificial Analysis | 27.2% | – |
| EnterpriseOps-Gym | Artificial Analysis | 42.9% | – |
| AA-Briefcase v1.1 | Artificial Analysis | 1478 | – |
| Terminal-Bench-Science 0.1 (AA) | Artificial Analysis | 22.4% | – |
| FACTS Search | 88.5%† | – | |
| Maths | |||
| FrontierMath Tiers 1–3 | Epoch AI Benchmarking Hub | 89.1% | 69.8% |
| FrontierMath Tier 4 | Epoch AI Benchmarking Hub | 82.9% | 31.7% |
| OTIS Mock AIME | Epoch AI Benchmarking Hub | 100.0% | 98.1% |
| ProofBench | Vals AI | 83.0% | – |
| LiveBench Mathematics | LiveBench | 96.2% | – |
| Arena Maths | Arena (LMArena) | 1495† | – |
| Knowledge | |||
| SimpleQA Verified | Epoch AI Benchmarking Hub | 69.7% | 56.6% |
| LiveBench 1.0 Data Analysis | LiveBench | 79.8% | – |
| MMLU-Pro | Vals AI | 89.1% | – |
| LegalBench | Vals AI | 87.0% | – |
| CorpFin | Vals AI | 64.4% | – |
| TaxEval | Vals AI | 74.8% | – |
| PRBench Finance | Scale AI SEAL | 50.5% | – |
| PRBench Legal | Scale AI SEAL | 50.5% | – |
| BioMysteryBench | Vals AI | 71.1% | – |
| Excel Modeling Benchmark | Vals AI | 72.3% | – |
| MedCode | Vals AI | 44.0% | – |
| MedScribe | Vals AI | 85.2% | – |
| Public Benefits Bench v1.1 | Vals AI | 66.5% | – |
| DrugDiscoveryBench | Scale AI SEAL | 56.5% | – |
| EBR-bench | Epoch AI Benchmarking Hub | 44.8% | – |
| GDP.pdf | Epoch AI Benchmarking Hub | 30.7% | – |
| Instruction following | |||
| LiveBench Language | LiveBench | 87.7% | – |
| LiveBench Instruction Following | LiveBench | 71.8% | – |
| IFBench | Artificial Analysis | 72.7% | – |
| Arena Instruction Following | Arena (LMArena) | 1491† | – |
| Human preference | |||
| Arena Text | Arena (LMArena) | 1485† | – |
| EQ-Bench 4 | EQ-Bench | 1236† | – |
| Arena Creative Writing | Arena (LMArena) | 1470† | – |
| Arena Multi-turn | Arena (LMArena) | 1490† | – |
| Arena Longer Queries | Arena (LMArena) | 1498† | – |
| Multimodal | |||
| Arena Vision | Arena (LMArena) | 1281† | – |
| MMMU-Pro | Artificial Analysis | 83.4% | – |
| MMMU-Pro (Vals) | Vals AI | 88.8% | – |
| MortgageTax | Vals AI | 67.3% | – |
| Blueprint-Bench 2 | Epoch AI Benchmarking Hub | 33.6%† | – |
| Long context | |||
| AA-LCR v1.1 | Artificial Analysis | 84.0% | – |
| Arena Document | Arena (LMArena) | 1489† | – |
| MLCR | Artificial Analysis | 30.0% | – |
| Composite | |||
| Epoch Capabilities Index | Epoch AI Benchmarking Hub | 162.7† | – |
| LiveBench 1.0 | LiveBench | 81.0% | – |
| AA Intelligence Index v4.3.2 | Artificial Analysis | 47.0 | – |
| AA Progress Index v1 | Artificial Analysis | 331.5 | – |
| Vals RSI Index | Vals AI | 23.9% | – |
| Vals Science Index | Vals AI | 41.5% | – |
| Vals Multimodal Index | Vals AI | 72.6% | – |
| Safety & honesty | |||
| FORTRESS | Scale AI SEAL | 20.1%† | – |
Data as of 2026-10-29. Best configuration of each model; every score links to its source on the model pages.
What changed
- GPT-5.6 Sol (max): 2 new results (AA Progress Index v1, CritPt v2 hard subset (AA)).
- GPT-5.6 Sol (max): 1 new result (AA-Briefcase v1.1).
- GPT-5.6 Sol (max): 3 new results (Harvey's Legal Agent Benchmark v1, Vals RSI Index, Vals Science Index).
- GPT-5.6 Sol (max): 1 score revision.
- GPT-5.6 Sol (max): 1 new result (ForecastBench).
- Muse Spark Open 816B A42B (xhigh): BenchLeader Index 57.4 → 58.6.
- Muse Spark Open 816B A42B (xhigh): 2 new results (SciCode, ALE-Bench).
- GPT-5.6 Sol (max): 5 new results (AutomationBench, GDP.pdf (AA), MLCR…).
- Muse Spark Open 816B A42B (xhigh): first results.
- GPT-5.6 Sol (max): 1 score revision.
Related comparisons
- GPT-5.6 Sol vs Claude Opus 5.5
- GPT-5.6 Sol vs Gemini 4 Carbon
- GPT-5.6 Sol vs GPT-6 Astra
- Muse Spark Open 816B A42B vs Claude Opus 5.5
- Muse Spark Open 816B A42B vs Gemini 4 Carbon
- Muse Spark Open 816B A42B vs GPT-6 Astra
- Muse Spark Open 816B A42B vs GPT-6.1 Sol
- GPT-5.6 Sol vs Muse Wonder
Rankings: Best LLM overall · Best LLM for agents · Best cheap LLMs
GPT-5.6 Sol vs Muse Spark Open 816B A42B: questions
- Is GPT-5.6 Sol better than Muse Spark Open 816B A42B?
- GPT-5.6 Sol (max) leads on quality: 65.4 vs 58.5. The BenchLeader Index combines every independent quality benchmark; GPT-5.6 Sol (max) is ahead overall as of 29 Oct 2026, but check the category scores for your use.
- GPT-5.6 Sol vs Muse Spark Open 816B A42B: which is cheaper, and will that change?
- Muse Spark Open 816B A42B is cheaper today: $2.00 against $8.00 per million tokens, blended at three input tokens per output token. No price change has been announced for either.
- Is GPT-5.6 Sol or Muse Spark Open 816B A42B better for coding?
- They are level in coding (66 vs 66 on the category index). On SciCode, the top shared coding benchmark, it is 57.1% for GPT-5.6 Sol against 58.5% for Muse Spark Open 816B A42B.
- Which is better for long documents?
- Both take about 1.1M tokens: GPT-5.6 Sol 1,050,000, Muse Spark Open 816B A42B 1,048,576.
- Do independent benchmarks agree on GPT-5.6 Sol vs Muse Spark Open 816B A42B?
- Across the 7 benchmarks both have, GPT-5.6 Sol leads 6, Muse Spark Open 816B A42B leads 1. Every overall index that rates both puts GPT-5.6 Sol ahead.
More questions (1)
- When was Muse Spark Open 816B A42B released?
- Muse Spark Open 816B A42B was released on 15 Oct 2026.