DeepSeek V4 Pro vs Muse Wonder
As of 13 Oct 2026, Muse Wonder (max) leads on quality (66.3 vs 62.7 on the BenchLeader Index), but DeepSeek V4 Pro (max) costs 4.0× less, so it is the better buy unless you need the extra quality.
DeepSeek V4 Pro 
Muse Wonder Key differences
- Muse Wonder (max) leads on quality: 66.3 vs 62.7.
- DeepSeek V4 Pro (max) is stronger in agents & tools, coding, instruction following, maths.
- Muse Wonder (max) is stronger in composite, knowledge, long context, reasoning.
- DeepSeek V4 Pro (max) is 4.0× cheaper ($1.98 vs $8.00 per 1M blended).
Choose DeepSeek V4 Pro (max) if
- cost matters: $1.98 against $8.00 per million tokens blended
- the wait for the first word matters: 45.3 s against 60.8 s to first answer
- you want to run it yourself: its weights are open
Choose Muse Wonder (max) if
- reasoning is the priority (88 vs 65 on the category score)
- knowledge is the priority (73 vs 60 on the category score)
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 | DeepSeek V4 Pro (max) | Muse Wonder (max) | Leader |
|---|---|---|---|
| Reasoning | 65.1 | 87.8 | Muse Wonder |
| Coding | 58.3 | – | not comparable |
| Agents & tools | 63.7 | – | not comparable |
| Maths | 56.3 | – | not comparable |
| Knowledge | 59.7 | 73.0 | Muse Wonder |
| Instruction following | 74.3 | – | not comparable |
| Long context | 65.3 | 65.5 | level |
| Composite | 70.0 | 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 | DeepSeek V4 Pro (max) | Muse Wonder (max) |
|---|---|---|
| Blended price per 1M tokens | $1.98 | $8.00 |
| Input / output per 1M | $1.32 / $3.96 | $4.00 / $20.00 |
| Price per task: chat reply | $0.0017 | $0.0076 |
| Price per task: summarise a 30-page report | $0.018 | $0.060 |
| Price per task: code edit | $0.014 | $0.054 |
| Price per task: agentic coding session | $0.095 | $0.320 |
| Price per task: structured extraction | $0.0034 | $0.012 |
| Cost to run a full benchmark suite | $0.674 | $4.52 |
| Output speed | 100 tok/s | 85 tok/s |
| Time to first answer | 45.3 s | 60.8 s |
| Time to a complete answer | 50.2 s | 66.7 s |
Every benchmark
| Metric | DeepSeek V4 Pro (max) | Muse Wonder (max) |
|---|---|---|
| BenchLeader Index | 62.7 | 66.3 |
| Agents & tools score | 63.7 | – |
| Coding score | 58.3 | – |
| Composite score | 70.0 | 78.2 |
| Instruction following score | 74.3 | – |
| Knowledge score | 59.7 | 73.0 |
| Long context score | 65.3 | 65.5 |
| Maths score | 56.3 | – |
| Reasoning score | 65.1 | 87.8 |
| Blended price $/M | $1.98 | $8.00 |
| Output speed | 100 tok/s | 85 tok/s |
| Time to first answer | 45.3 s | 60.8 s |
| Context window | 1M | 1.0M |
| GPQA Diamond | 91.7% | – |
| FrontierMath Tiers 1–3 | 64.6% | – |
| FrontierMath Tier 4 | 26.8% | – |
| OTIS Mock AIME | 98.6% | – |
| SWE-bench Verified (Epoch) | 77.6% | – |
| SimpleQA Verified | 52.9% | – |
| SciCode | 51.0% | – |
| WeirdML | 66.2% | – |
| ProofBench | 16.0% | – |
| LiveBench | – | 81.2% |
| LiveBench Reasoning | – | 90.6% |
| LiveBench Coding | – | 80.7% |
| LiveBench Agentic Coding | – | 62.7% |
| LiveBench Mathematics | – | 96.5% |
| LiveBench Data Analysis | – | 81.6% |
| LiveBench Language | – | 82.9% |
| LiveBench Instruction Following | – | 73.0% |
| AA Intelligence Index v4.3.2 | 36 | 52.4 |
| IFBench | 76.5% | – |
| AA-LCR | 80.3% | 80.7% |
| AA-Omniscience | 0.8 | 25.5 |
| Terminal-Bench Hard | 46.2% | – |
| GPQA Diamond (AA) | 92.8% | – |
| Humanity's Last Exam (AA) | 41.0% | 50.1% |
| SciCode (AA) | 51.0% | 60.3% |
| τ²-Bench Telecom (AA) | 96.2% | – |
| LiveCodeBench | 87.5% | – |
| MMLU-Pro | 87.3% | – |
| IOI | 51.6% | – |
| LegalBench | 82.4% | – |
| CorpFin | 65.4% | – |
| TaxEval | 73.1% | – |
| Terminal-Bench 2.1 (Vals) | 54.7% | – |
| SWE-bench (Vals) | 96.4% | – |
| GPQA Diamond (Vals) | 92.4% | – |
| Vals Index | 47.6 | – |
| AIME 2026 | 96.7% | – |
| HMMT February 2026 | 93.9% | – |
| MathArena Apex | 28.1% | – |
| ARC-AGI-1 | 90.0% | – |
| ARC-AGI-2 | 61.3% | – |
| CritPt | 18.0% | 28.3% |
| GDPval-AA v2.1 | 47.5% | 63.5% |
| τ³-Banking (AA) | 39.6% | – |
| ITBench SRE (AA) | 38.3% | – |
| Analyst Agent (AA) | 18.8% | – |
| APEX-Agents (AA) | 24.3% | – |
| CaseLaw v2 | 59.4% | – |
| Code Migration | 41.5% | – |
| CyberBench | 72.9% | – |
| Excel Modeling Benchmark | 52.8% | – |
| Finance Agent v2 | 50.4% | – |
| Harvey's Legal Agent Benchmark | 7.5% | – |
| Legal Research Bench | 40.9% | – |
| MedCode | 42.5% | – |
| MedScribe | 80.2% | – |
| ProgramBench | 0.0% | – |
| Public Benefits Bench | 62.9% | – |
| SkillsBench | 53.8% | – |
| Tax Agent Bench | 58.7% | – |
| Terminal-Bench 4.0 (Vals) | 14.1% | – |
| Terminal-Bench Science | 0.0% | – |
| Vibe Code Bench 1-100 | 17.5% | – |
| Vibe Code Bench v1.1 | 82.3% | – |
| Chess Puzzles | 47.0% | – |
| Mystery Game Puzzles | 43.0% | – |
| LMCA | 41.2% | – |
| DTBench | 90.7% | – |
| ALE-Bench | 1403.2 | – |
| Terminal-Bench 4.0 (AA) | 14.7% | 52.0% |
| Terminal-Bench 2.1 (AA) | 78.7% | – |
| AutomationBench | 56.7% | 68.1% |
| GDP.pdf | 11.4% | 30.6% |
| MLCR | 17.8% | – |
| EnterpriseOps-Gym | 49.6% | – |
| AA-Omniscience: accuracy | 49.1% | 41.1% |
| AA-Omniscience: non-hallucination | 5.9% | 73.5% |
| AA-Briefcase v1.1 | 1257 | 1659 |
| Terminal-Bench-Science 0.1 (AA) | 5.7% | – |
| AA Openness Index | 44.4 | – |
Data as of 2026-10-13. Best configuration of each model; every score links to its source on the model pages.
DeepSeek V4 Pro vs Muse Wonder: questions
- Is DeepSeek V4 Pro better than Muse Wonder?
- Muse Wonder (max) leads on quality: 66.3 vs 62.7. 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, DeepSeek V4 Pro or Muse Wonder?
- DeepSeek V4 Pro is cheaper: $1.98 against $8.00 per million tokens, blended at three input tokens per output token.
- Which is faster, DeepSeek V4 Pro or Muse Wonder?
- DeepSeek V4 Pro streams faster: 100 against 85 output tokens per second.
- Which has the larger context window?
- Muse Wonder accepts more context: 1.0M against 1M tokens.