GPT-5.4 vs Muse Wonder
As of 13 Oct 2026, Muse Wonder (max) leads on quality (66.3 vs 64.1 on the BenchLeader Index), but GPT-5.4 (xhigh) costs 1.4× less, so it is the better buy unless you need the extra quality.
GPT-5.4 
Muse Wonder Key differences
- Muse Wonder (max) leads on quality: 66.3 vs 64.1.
- GPT-5.4 (xhigh) is stronger in agents & tools, coding, instruction following, long context, maths, multimodal.
- Muse Wonder (max) is stronger in composite, knowledge, reasoning.
- GPT-5.4 (xhigh) is 1.4× cheaper ($5.63 vs $8.00 per 1M blended).
Choose GPT-5.4 (xhigh) if
- cost matters: $5.63 against $8.00 per million tokens blended
Choose Muse Wonder (max) if
- reasoning is the priority (88 vs 69 on the category score)
- knowledge is the priority (73 vs 60 on the category score)
- the wait for the first word matters: 60.8 s against 202.5 s to first answer
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-5.4 (xhigh) | Muse Wonder (max) | Leader |
|---|---|---|---|
| Reasoning | 69.4 | 87.8 | Muse Wonder |
| Coding | 64.7 | – | not comparable |
| Agents & tools | 63.6 | – | not comparable |
| Maths | 65.4 | – | not comparable |
| Knowledge | 59.9 | 73.0 | Muse Wonder |
| Instruction following | 72.1 | – | not comparable |
| Multimodal | 61.6 | – | not comparable |
| Long context | 66.2 | 65.5 | level |
| Composite | 66.0 | 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 | GPT-5.4 (xhigh) | Muse Wonder (max) |
|---|---|---|
| Blended price per 1M tokens | $5.63 | $8.00 |
| Input / output per 1M | $2.50 / $15.00 | $4.00 / $20.00 |
| Price per task: chat reply | $0.0055 | $0.0076 |
| Price per task: summarise a 30-page report | $0.039 | $0.060 |
| Price per task: code edit | $0.037 | $0.054 |
| Price per task: agentic coding session | $0.210 | $0.320 |
| Price per task: structured extraction | $0.0080 | $0.012 |
| Cost to run a full benchmark suite | – | $4.52 |
| Output speed | 94 tok/s | 85 tok/s |
| Time to first answer | 202.5 s | 60.8 s |
| Time to a complete answer | 207.8 s | 66.7 s |
Every benchmark
| Metric | GPT-5.4 (xhigh) | Muse Wonder (max) |
|---|---|---|
| BenchLeader Index | 64.1 | 66.3 |
| Agents & tools score | 63.6 | – |
| Coding score | 64.7 | – |
| Composite score | 66.0 | 78.2 |
| Instruction following score | 72.1 | – |
| Knowledge score | 59.9 | 73.0 |
| Long context score | 66.2 | 65.5 |
| Maths score | 65.4 | – |
| Multimodal score | 61.6 | – |
| Reasoning score | 69.4 | 87.8 |
| Blended price $/M | $5.63 | $8.00 |
| Output speed | 94 tok/s | 85 tok/s |
| Time to first answer | 202.5 s | 60.8 s |
| Context window | 1.1M | 1.0M |
| GPQA Diamond | 93.3% | – |
| FrontierMath Tiers 1–3 | 78.6% | – |
| FrontierMath Tier 4 | 49.0% | – |
| OTIS Mock AIME | 95.3% | – |
| SimpleQA Verified | 45.1% | – |
| Humanity's Last Exam | 36.2% | – |
| SciCode | 56.6% | – |
| WeirdML | 77.7% | – |
| ProofBench | 56.0% | – |
| GSO-Bench | 31.4% | – |
| LiveBench | 78.0% | 81.2% |
| LiveBench Reasoning | 88.1% | 90.6% |
| LiveBench Coding | 77.5% | 80.7% |
| LiveBench Agentic Coding | 53.8% | 62.7% |
| LiveBench Mathematics | 94.2% | 96.5% |
| LiveBench Data Analysis | 79.3% | 81.6% |
| LiveBench Language | 82.6% | 82.9% |
| LiveBench Instruction Following | 70.2% | 73.0% |
| AA Intelligence Index v4.3.2 | 39.0 | 52.4 |
| IFBench | 74.0% | – |
| AA-LCR | 82.0% | 80.7% |
| MMMU-Pro | 78.4% | – |
| AA-Omniscience | 5.8 | 25.5 |
| Terminal-Bench Hard | 57.6% | – |
| GPQA Diamond (AA) | 92.0% | – |
| Humanity's Last Exam (AA) | 43.7% | 50.1% |
| SciCode (AA) | – | 60.3% |
| τ²-Bench Telecom (AA) | 87.1% | – |
| AIME (Vals) | 96.7% | – |
| LiveCodeBench | 84.1% | – |
| MMLU-Pro | 87.5% | – |
| LegalBench | 86.0% | – |
| CorpFin | 65.3% | – |
| TaxEval | 74.0% | – |
| MedQA | 96.1% | – |
| SWE-bench (Vals) | 78.2% | – |
| GPQA Diamond (Vals) | 91.7% | – |
| AIME 2026 | 99.2% | – |
| HMMT February 2026 | 97.7% | – |
| MathArena Apex | 54.2% | – |
| SWE-Bench Pro | 59.1% | – |
| MCP Atlas | 70.6% | – |
| ARC-AGI-1 | 93.7% | – |
| ARC-AGI-2 | 74.0% | – |
| CritPt | 23.4% | 28.3% |
| GDPval-AA v2.1 | 37.3% | 63.5% |
| τ³-Banking (AA) | 39.6% | – |
| APEX-Agents (AA) | 33.3% | – |
| CaseLaw v2 | 63.8% | – |
| Code Migration | 35.0% | – |
| Harvey's Legal Agent Benchmark | 0.0% | – |
| MedCode | 41.3% | – |
| MedScribe | 77.5% | – |
| MMMU-Pro (Vals) | 87.5% | – |
| MortgageTax | 68.3% | – |
| ProgramBench | 0.0% | – |
| SAGE | 43.3% | – |
| SkillsBench | 51.7% | – |
| Vibe Code Bench v1.1 | 67.4% | – |
| SWE-Bench Pro (private) | 59.1% | – |
| SWE Atlas: Codebase QnA | 40.8% | – |
| SWE Atlas: Refactoring | 44.3% | – |
| SWE Atlas: Test Writing | 44.4% | – |
| Chess Puzzles | 44.0% | – |
| EBR-bench | 25.4% | – |
| Mystery Game Puzzles | 37.0% | – |
| CL-bench | 27.9% | – |
| CL-bench Life | 21.7% | – |
| METR Time Horizons | 74.3% | – |
| DeepSWE v1.1 | 51.8% | – |
| LMCA | 52.0% | – |
| DTBench | 94.4% | – |
| Terminal-Bench 4.0 (AA) | – | 52.0% |
| Terminal-Bench 2.1 (AA) | 78.3% | – |
| AutomationBench | – | 68.1% |
| GDP.pdf | – | 30.6% |
| AA-Omniscience: accuracy | 50.9% | 41.1% |
| AA-Omniscience: non-hallucination | 8.3% | 73.5% |
| AA-Briefcase v1.1 | – | 1659 |
Data as of 2026-10-13. Best configuration of each model; every score links to its source on the model pages.
GPT-5.4 vs Muse Wonder: questions
- Is GPT-5.4 better than Muse Wonder?
- Muse Wonder (max) leads on quality: 66.3 vs 64.1. 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, GPT-5.4 or Muse Wonder?
- GPT-5.4 is cheaper: $5.63 against $8.00 per million tokens, blended at three input tokens per output token.
- Which is faster, GPT-5.4 or Muse Wonder?
- GPT-5.4 streams faster: 94 against 85 output tokens per second.
- Which has the larger context window?
- GPT-5.4 accepts more context: 1.1M against 1.0M tokens.