GPT-5.5 Pro vs Muse Wonder Full
Full profiles: GPT-5.5 Pro (OpenAI) and Muse Wonder Full (Meta): every benchmark, price and rank.
Updated · Data from 7 sources
As of 21 Oct 2026, GPT-5.5 Pro (xhigh) and Muse Wonder Full (max) are neck and neck on quality (65.3 vs 70.7, inside the ±12.0 margin of error) and close on price, so pick on the category that matters to you. Muse Wonder Full leads in every category we measure both in.
GPT-5.5 Pro benchmarks 
Muse Wonder Full 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 |
|---|---|---|---|
| Reasoning | Muse Wonder Full | 95 vs 78 category score; CritPt 32.9% vs 30.6% | High |
| High volume on a budget | Neither flagship | A smaller model is usually the better fit: Cheapest good LLMs, Fastest LLMs | – |
Key differences
- GPT-5.5 Pro (xhigh) and Muse Wonder Full (max) are neck and neck on quality (65.3 vs 70.7, within the ±12.0 margin).
- GPT-5.5 Pro (xhigh) is stronger in maths.
- Muse Wonder Full (max) is stronger in reasoning, coding, composite, knowledge, long context.
At a glance
| Spec | GPT-5.5 Pro | Muse Wonder Full |
|---|---|---|
| Developer | OpenAI | Meta |
| Released | 23 Apr 2026 | 12 Oct 2026 |
| Context window (tokens) | 1,050,000 | 1,000,000 |
| Compared at | GPT-5.5 Pro (xhigh) | Muse Wonder Full (max) |
| Open weights | No | No |
| Price in / out / cached input per 1M | $30.00 / $180.00 / – | – |
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-5.5 Pro (xhigh) | Muse Wonder Full (max) | Leader |
|---|---|---|---|
| Reasoning | 77.7 | 95.0 | Muse Wonder Full |
| Coding | – | 72.2 | not comparable |
| Maths | 71.3 | – | not comparable |
| Knowledge | – | 71.3 | not comparable |
| Long context | – | 67.0 | not comparable |
| Composite | – | 92.1 | not comparable |
Where sources disagree
Across the 1 benchmarks both have, GPT-5.5 Pro leads 0, Muse Wonder Full leads 1.
| Overall index | GPT-5.5 Pro (xhigh) | Muse Wonder Full (max) | Leader |
|---|---|---|---|
| BenchLeader Index | 65.3 | 70.7 | neck and neck |
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-5.5 Pro (xhigh) | Muse Wonder Full (max) |
|---|---|---|
| Blended price per 1M tokens | $67.50 | – |
| Input / output per 1M | $30.00 / $180.00 | – / – |
| Price per task: chat reply | $0.066 | – |
| Price per task: summarize a 30-page report | $0.468 | – |
| Price per task: code edit | $0.450 | – |
| Price per task: agentic coding session | $2.52 | – |
| Price per task: structured extraction | $0.096 | – |
| Output speed | 24 tok/s | – |
| Time to first answer | 4.3 s | – |
Each model is compared at its best-ranked reasoning-effort setting. GPT-5.5 Pro (xhigh) scores 65.3 and takes 4 s to its first answer token. Muse Wonder Full (max) scores 70.7. 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
46 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-5.5 Pro (xhigh) | Muse Wonder Full (max) |
|---|---|---|---|
| BenchLeader Index | BenchLeader | 65.3 | 70.7 |
| Maths score | BenchLeader | 71.3 | – |
| Reasoning score | BenchLeader | 77.7 | 95.0 |
| Coding score | BenchLeader | – | 72.2 |
| Composite score | BenchLeader | – | 92.1 |
| Knowledge score | BenchLeader | – | 71.3 |
| Long context score | BenchLeader | – | 67.0 |
| Blended price $/M | BenchLeader | $67.50 | – |
| Output speed | BenchLeader | 24 tok/s | – |
| Time to first answer | BenchLeader | 4.3 s | – |
| Context window | BenchLeader | 1,050,000 tokens | 1,000,000 tokens |
| Reasoning | |||
| SimpleBench | SimpleBench | 76.9%† | – |
| Humanity's Last Exam (AA) | Artificial Analysis | – | 53.6% |
| ARC-AGI-1 | ARC Prize | 95.0% | – |
| ARC-AGI-2 | ARC Prize | 84.2% | – |
| CritPt | Artificial Analysis | 30.6% | 32.9% |
| MysteryMechanism | Vals AI | – | 35.1% |
| Chess Puzzles | Epoch AI Benchmarking Hub | 62.0% | – |
| LMCA | Epoch AI Benchmarking Hub | 53.9% | – |
| DTBench | Epoch AI Benchmarking Hub | 96.0% | – |
| Coding | |||
| Arena WebDev | Arena (LMArena) | – | 1726 |
| SciCode (AA) | Artificial Analysis | – | 62.6% |
| IOI | Vals AI | – | 79.8% |
| Code Migration | Vals AI | – | 61.0% |
| ProgramBench | Vals AI | – | 0.5% |
| Vibe Code Bench 1-100 | Vals AI | – | 34.0% |
| Vibe Code Bench v1.1 | Vals AI | – | 86.0% |
| Terminal-Bench 4.0 (AA) | Artificial Analysis | – | 57.1% |
| FrontierCode 1.1 (AA) | Artificial Analysis | – | 44.9% |
| Agents & tools | |||
| GDPval-AA v2.1 | Artificial Analysis | – | 67.8% |
| CyberBench | Vals AI | – | 73.6% |
| Finance Agent v2 | Vals AI | – | 59.1% |
| Harvey's Legal Agent Benchmark | Vals AI | – | 23.3% |
| Legal Research Bench | Vals AI | – | 53.4% |
| SREBench | Vals AI | – | 11.8% |
| Tax Agent Bench | Vals AI | – | 43.0% |
Show all 46 benchmarks
| Metric | Publisher | GPT-5.5 Pro (xhigh) | Muse Wonder Full (max) |
|---|---|---|---|
| Agents & tools | |||
| Terminal-Bench 4.0 (Vals) | Vals AI | – | 58.1% |
| Terminal-Bench Science | Vals AI | – | 37.1% |
| AutomationBench | Artificial Analysis | – | 71.3% |
| GDP.pdf (AA) | Artificial Analysis | – | 32.6% |
| Harvey LAB-AA v1.1 | Harvey | – | 13.1% |
| AA-Briefcase v1.1 | Artificial Analysis | – | 1729 |
| Maths | |||
| FrontierMath Tiers 1–3 | Epoch AI Benchmarking Hub | 87.7% | – |
| FrontierMath Tier 4 | Epoch AI Benchmarking Hub | 78.0% | – |
| Knowledge | |||
| AA-Omniscience | Artificial Analysis | – | 30.1 |
| LegalBench | Vals AI | – | 87.4% |
| BioMysteryBench | Vals AI | – | 73.3% |
| Excel Modeling Benchmark | Vals AI | – | 71.9% |
| MedCode | Vals AI | – | 49.9% |
| MedScribe | Vals AI | – | 89.3% |
| Public Benefits Bench | Vals AI | – | 73.8% |
| AA-Omniscience: accuracy | Artificial Analysis | – | 43.2% |
| AA-Omniscience: non-hallucination | Artificial Analysis | – | 77.0% |
| Long context | |||
| AA-LCR | Artificial Analysis | – | 83.7% |
| Composite | |||
| Epoch Capabilities Index | Epoch AI Benchmarking Hub | 162.9† | – |
| AA Intelligence Index v4.3.2 | Artificial Analysis | – | 55.8 |
| Vals Index | Vals AI | – | 66.8 |
Data as of 2026-10-21. Best configuration of each model; every score links to its source on the model pages.
What changed
- Muse Wonder Full (max): 1 new result (FrontierCode 1.1 (AA)).
- Muse Wonder Full (max): BenchLeader Index 68.6 → 70.7.
- Muse Wonder Full (max): 1 new result (Arena WebDev); 2 score revisions.
- Muse Wonder Full (max): 21 new results (IOI, LegalBench, Vals Index…).
- GPT-5.5 Pro (xhigh): 1 new result (Chess Puzzles).
- Muse Wonder Full (max): 1 new result (Harvey LAB-AA v1.1).
- Muse Wonder Full (max): first results.
- GPT-5.5 Pro (xhigh): BenchLeader Index 66.5 → 65.6.
- GPT-5.5 Pro (xhigh): BenchLeader Index 67.1 → 66.5.
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Rankings: Best LLM overall · Best LLM for coding · Best LLM for agents · Best cheap LLMs
GPT-5.5 Pro vs Muse Wonder Full: questions
- Is GPT-5.5 Pro better than Muse Wonder Full?
- GPT-5.5 Pro (xhigh) and Muse Wonder Full (max) are neck and neck on quality (65.3 vs 70.7, within the ±12.0 margin). The BenchLeader Index combines every independent quality benchmark; the two are within the margin of error as of 2026-10-21, so check the category scores for your use.
- Which is better for long documents?
- Both take about 1.1M tokens: GPT-5.5 Pro 1,050,000, Muse Wonder Full 1,000,000.
- Do independent benchmarks agree on GPT-5.5 Pro vs Muse Wonder Full?
- Across the 1 benchmarks both have, GPT-5.5 Pro leads 0, Muse Wonder Full leads 1.
- When was Muse Wonder Full released?
- Muse Wonder Full was released on 12 Oct 2026.