Claude Opus 5.5 vs DeepSeek V4 Pro
Claude Opus 5.5 
DeepSeek V4 Pro Verdict
- Claude Opus 5.5 (thinking) leads on quality: 70.7 vs 63.7.
- Claude Opus 5.5 (thinking) is stronger in composite, knowledge, long context, multimodal, reasoning.
- DeepSeek V4 Pro (max) is stronger in agents & tools, coding, instruction following, maths.
- DeepSeek V4 Pro (max) is 15× cheaper ($0.544 vs $8.00 per 1M blended).
- DeepSeek V4 Pro (max) streams 1.6× faster (79 vs 48 tokens per second).
| Metric | Claude Opus 5.5 (thinking) | DeepSeek V4 Pro (max) |
|---|---|---|
| BenchLeader Index | 70.7 | 63.7 |
| Composite score | 95.0 | 73.1 |
| Knowledge score | 85.0 | 60.3 |
| Long context score | 68.5 | 66.3 |
| Multimodal score | 71.9 | – |
| Reasoning score | 95.0 | 67.1 |
| Agents & tools score | – | 63.6 |
| Coding score | – | 59.2 |
| Instruction following score | – | 74.3 |
| Maths score | – | 57.1 |
| Blended price $/M | $8.00 | $0.544 |
| Output speed | 48 tok/s | 79 tok/s |
| Time to first answer | 4.2 s | 57.3 s |
| Context window | 1M | 1M |
| 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% |
| AA Intelligence Index | 57.6 | 36 |
| IFBench | – | 76.5% |
| AA-LCR | 84.7% | 80.3% |
| MMMU-Pro | 87.7% | – |
| AA-Omniscience | 46.4 | 0.8 |
| Terminal-Bench Hard | – | 46.2% |
| GPQA Diamond (AA) | – | 92.8% |
| Humanity's Last Exam (AA) | 61.4% | 41.0% |
| SciCode (AA) | 66.9% | 51.0% |
| 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 | – | 52.4 |
| AIME 2026 | – | 96.7% |
| HMMT February 2026 | – | 93.9% |
| MathArena Apex | – | 28.1% |
| ARC-AGI-1 | – | 90.0% |
| ARC-AGI-2 | – | 61.3% |
| CritPt | 31.7% | 18.0% |
| GDPval (AA) | 67.3% | 47.1% |
| τ²-Bench 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% |
| 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) | – | 1.0% |
| 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) | 59.6% | 14.7% |
| Terminal-Bench 2.1 (AA) | – | 78.7% |
| AutomationBench | 69.5% | 56.7% |
| GDP.pdf | 26.2% | 11.4% |
| MLCR | – | 17.8% |
| Harvey LAB | 91.2% | – |
| EnterpriseOps-Gym | – | 49.6% |
| AA-Omniscience: accuracy | 66.2% | 49.1% |
| AA-Omniscience: non-hallucination | 41.4% | 5.9% |
| AA-Briefcase | 1822 | 1261 |
| AA Openness Index | – | 44.4 |
Data as of 2026-09-22. Best configuration of each model; every score links to its source on the model pages.
Claude Opus 5.5 vs DeepSeek V4 Pro: questions
- Is Claude Opus 5.5 better than DeepSeek V4 Pro?
- Claude Opus 5.5 (thinking) leads on quality: 70.7 vs 63.7. The BenchLeader Index combines every independent quality benchmark; Claude Opus 5.5 (thinking) is ahead overall as of 2026-09-22, but check the category scores for your use.
- Which is cheaper, Claude Opus 5.5 or DeepSeek V4 Pro?
- DeepSeek V4 Pro is cheaper: $0.544 against $8.00 per million tokens, blended at three input tokens per output token.
- Which is faster, Claude Opus 5.5 or DeepSeek V4 Pro?
- DeepSeek V4 Pro streams faster: 79 against 48 output tokens per second.
- Which has the larger context window?
- Both accept 1M tokens of context.