Model comparison
Claude Opus 5.5 vs DeepSeek-R1-Distill-Qwen-14B
Claude Opus 5.5 is the stronger model overall, scoring 68.6 to 32.7 on the Noometry Index.
Last verified . 3 shared benchmarks.
DeepSeekSummary
- They share 3 benchmarks with published results for both. Claude Opus 5.5 scores higher in 4 categories and DeepSeek-R1-Distill-Qwen-14B in 0 categories; 4 gaps are clear of the uncertainty.
- The widest gap is in reasoning, where Claude Opus 5.5 leads 80.2 to 19.2.
- The biggest single-benchmark swing is OTIS Mock AIME 2024-2025: 100% for Claude Opus 5.5 and 50.6% for DeepSeek-R1-Distill-Qwen-14B.
- DeepSeek-R1-Distill-Qwen-14B has downloadable open weights; the other is API-only.
Side by side
| Claude Opus 5.5 | DeepSeek-R1-Distill-Qwen-14B | |
|---|---|---|
| Provider | Anthropic | DeepSeek |
| Noometry Index | 68.6 | 32.7 |
| Released | 2026-09-22 | 2025-01-20 |
| Weights | Proprietary | Open |
| Context window | 1M | — |
| Max output | 128K | — |
| Input $ / M tokens | $4 | — |
| Output $ / M tokens | $20 | — |
| Results tracked | 44 | 7 |
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Category by category
Coding Claude Opus 5.5 leads
Claude Opus 5.5: 71.9 (#3), DeepSeek-R1-Distill-Qwen-14B: 36.9 (#200)
| Benchmark | Claude Opus 5.5 | DeepSeek-R1-Distill-Qwen-14B |
|---|---|---|
| FrontierCode | 54.6% | — |
| CursorBench | 57.8% | — |
| LMArena WebDev | 1813 | — |
| FrontierSWE | 62.3% | — |
| SciCode | 66.9% | — |
| BigCodeBench Instruct | — | 38.1% |
| LMArena Coding | 1547 | — |
| MirrorCode | 77.4% | — |
| BigCodeBench Complete | — | 48.4% |
| ALE-Bench | 2,147 | — |
Agentic & Tool Use Not comparable
Claude Opus 5.5: 45.3 (#15), DeepSeek-R1-Distill-Qwen-14B: —
| Benchmark | Claude Opus 5.5 | DeepSeek-R1-Distill-Qwen-14B |
|---|---|---|
| APEX-Agents | 73.5% | — |
| GDP.pdf | 30.6% | — |
| Vending-Bench 2 | 9,235 | — |
Reasoning Claude Opus 5.5 leads
Claude Opus 5.5: 80.2 (#3), DeepSeek-R1-Distill-Qwen-14B: 19.2 (#263)
| Benchmark | Claude Opus 5.5 | DeepSeek-R1-Distill-Qwen-14B |
|---|---|---|
| Epoch Capabilities Index | 167.33 | 135.43 |
| ARC-AGI-2 | 93.3% | — |
| NYT Connections (extended) | 88.5% | — |
| ARC-AGI-1 | 98.5% | — |
| CritPt | 31.7% | — |
| Chess Puzzles | — | 1% |
| EBR-Bench | 71.4% | — |
| LMArena Hard Prompts | 1535 | — |
| Mystery Game Puzzles | 71% | — |
| DTBench | 98.9% | — |
| LMCA | 68.2% | — |
Math Claude Opus 5.5 leads
Claude Opus 5.5: 91.8 (#3), DeepSeek-R1-Distill-Qwen-14B: 35.5 (#184)
| Benchmark | Claude Opus 5.5 | DeepSeek-R1-Distill-Qwen-14B |
|---|---|---|
| OTIS Mock AIME 2024-2025 | 100% | 50.6% |
| FrontierMath (Tiers 1-3) | 91.2% | — |
| FrontierMath Tier 4 | 95% | — |
| ProofBench | 100% | — |
| LMArena Math | 1506 | — |
| MATH Level 5 | — | 87.1% |
| FrontierMath Erdős | 2.9% | — |
Knowledge Claude Opus 5.5 leads
Claude Opus 5.5: 66.4 (#10), DeepSeek-R1-Distill-Qwen-14B: 24.1 (#270)
| Benchmark | Claude Opus 5.5 | DeepSeek-R1-Distill-Qwen-14B |
|---|---|---|
| GPQA Diamond | 90.6% | 44.7% |
| SimpleQA Verified | 72.2% | — |
| LMArena Expert | 1547 | — |
Multimodal Not comparable
Claude Opus 5.5: 57.8 (#1), DeepSeek-R1-Distill-Qwen-14B: —
| Benchmark | Claude Opus 5.5 | DeepSeek-R1-Distill-Qwen-14B |
|---|---|---|
| LMArena Vision | 1321 | — |
| Blueprint-Bench 2 | 51.2% | — |
| Furniture Assembly | 83.3% | — |
Multilingual Not comparable
Claude Opus 5.5: 59.1 (#2), DeepSeek-R1-Distill-Qwen-14B: —
| Benchmark | Claude Opus 5.5 | DeepSeek-R1-Distill-Qwen-14B |
|---|---|---|
| LMArena Non-English | 1507 | — |
| LMArena Chinese | 1588 | — |
| LMArena French | 1514 | — |
| LMArena Russian | 1520 | — |
| LMArena Spanish | 1507 | — |
Instruction Following Not comparable
Claude Opus 5.5: 80.0 (#3), DeepSeek-R1-Distill-Qwen-14B: —
| Benchmark | Claude Opus 5.5 | DeepSeek-R1-Distill-Qwen-14B |
|---|---|---|
| LMArena Instruction Following | 1537 | — |
Long Context Not comparable
Claude Opus 5.5: 47.1 (#19), DeepSeek-R1-Distill-Qwen-14B: —
| Benchmark | Claude Opus 5.5 | DeepSeek-R1-Distill-Qwen-14B |
|---|---|---|
| LMArena Longer Query | 1532 | — |
Writing & Preference Not comparable
Claude Opus 5.5: 78.2 (#3), DeepSeek-R1-Distill-Qwen-14B: —
| Benchmark | Claude Opus 5.5 | DeepSeek-R1-Distill-Qwen-14B |
|---|---|---|
| LMArena Text | 1515 | — |
| LMArena Creative Writing | 1533 | — |
| EQ-Bench Creative Writing | 2050 | — |
| LMArena Multi-Turn | 1499 | — |
Frequently asked questions
Is Claude Opus 5.5 better than DeepSeek-R1-Distill-Qwen-14B?
Claude Opus 5.5 is the stronger model overall, scoring 68.6 to 32.7 on the Noometry Index.
Is Claude Opus 5.5 or DeepSeek-R1-Distill-Qwen-14B better for coding?
Claude Opus 5.5 scores higher on coding benchmarks: 71.9 versus 36.9 in the Noometry coding category.
How many benchmarks do Claude Opus 5.5 and DeepSeek-R1-Distill-Qwen-14B share?
3 benchmarks have published results for both models. Claude Opus 5.5 has 44 scored results on Noometry and DeepSeek-R1-Distill-Qwen-14B has 7.