Model comparison
DeepSeek-R1-Distill-Qwen-32B vs GPT-6.1 Sol
GPT-6.1 Sol is the stronger model overall, scoring 65.6 to 35.5 on the Noometry Index.
Last verified . 4 shared benchmarks.
DeepSeekSummary
- They share 4 benchmarks with published results for both. DeepSeek-R1-Distill-Qwen-32B scores higher in 0 categories and GPT-6.1 Sol in 7 categories; 7 gaps are clear of the uncertainty.
- The widest gap is in reasoning, where GPT-6.1 Sol leads 81.9 to 18.2.
- The biggest single-benchmark swing is Chess Puzzles: 1% for DeepSeek-R1-Distill-Qwen-32B and 61% for GPT-6.1 Sol.
- DeepSeek-R1-Distill-Qwen-32B has downloadable open weights; the other is API-only.
Side by side
| DeepSeek-R1-Distill-Qwen-32B | GPT-6.1 Sol | |
|---|---|---|
| Provider | DeepSeek | OpenAI |
| Noometry Index | 35.5 | 65.6 |
| Released | 2025-01-20 | 2026-09-29 |
| Weights | Open | Proprietary |
| Context window | — | 1.05M |
| Max output | — | 128K |
| Input $ / M tokens | — | $2 |
| Output $ / M tokens | — | $10 |
| Results tracked | 14 | 34 |
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Category by category
Coding GPT-6.1 Sol leads
DeepSeek-R1-Distill-Qwen-32B: 36.1 (#212), GPT-6.1 Sol: 63.2 (#8)
| Benchmark | DeepSeek-R1-Distill-Qwen-32B | GPT-6.1 Sol |
|---|---|---|
| DeepSWE | — | 75.2% |
| FrontierCode | — | 50.2% |
| LMArena WebDev | — | 1755 |
| SciCode | — | 55.8% |
| BigCodeBench Instruct | 43.9% | — |
| LiveBench Coding | 33.7% | — |
| LMArena Coding | — | 1487 |
| BigCodeBench Complete | 54.9% | — |
Agentic & Tool Use GPT-6.1 Sol leads
DeepSeek-R1-Distill-Qwen-32B: 28.1 (#94), GPT-6.1 Sol: 39.6 (#26)
| Benchmark | DeepSeek-R1-Distill-Qwen-32B | GPT-6.1 Sol |
|---|---|---|
| APEX-Agents | — | 60% |
| BALROG | 19.5% | — |
| GDP.pdf | — | 32% |
Reasoning GPT-6.1 Sol leads
DeepSeek-R1-Distill-Qwen-32B: 18.2 (#284), GPT-6.1 Sol: 81.9 (#2)
| Benchmark | DeepSeek-R1-Distill-Qwen-32B | GPT-6.1 Sol |
|---|---|---|
| Chess Puzzles | 1% | 61% |
| Epoch Capabilities Index | 137.44 | 166.09 |
| ARC-AGI-2 | — | 94.2% |
| NYT Connections (extended) | — | 95.5% |
| ARC-AGI-1 | — | 98.5% |
| CritPt | — | 31.7% |
| EBR-Bench | — | 54.3% |
| LiveBench Reasoning | 52.3% | — |
| LMArena Hard Prompts | — | 1466 |
| Mystery Game Puzzles | — | 80% |
| LiveBench Data Analysis | 45.4% | — |
| LiveBench | 45.5% | — |
Math GPT-6.1 Sol leads
DeepSeek-R1-Distill-Qwen-32B: 34.5 (#194), GPT-6.1 Sol: 93.7 (#1)
| Benchmark | DeepSeek-R1-Distill-Qwen-32B | GPT-6.1 Sol |
|---|---|---|
| OTIS Mock AIME 2024-2025 | 55.6% | 100% |
| FrontierMath (Tiers 1-3) | — | 93.7% |
| FrontierMath Tier 4 | — | 100% |
| ProofBench | — | 99% |
| LiveBench Math | 59.4% | — |
| LMArena Math | — | 1464 |
Knowledge GPT-6.1 Sol leads
DeepSeek-R1-Distill-Qwen-32B: 35.7 (#182), GPT-6.1 Sol: 71.8 (#4)
| Benchmark | DeepSeek-R1-Distill-Qwen-32B | GPT-6.1 Sol |
|---|---|---|
| GPQA Diamond | 64.1% | 95.4% |
| SimpleQA Verified | — | 73.9% |
| LMArena Expert | — | 1502 |
Multimodal Not comparable
DeepSeek-R1-Distill-Qwen-32B: —, GPT-6.1 Sol: 52.7 (#5)
| Benchmark | DeepSeek-R1-Distill-Qwen-32B | GPT-6.1 Sol |
|---|---|---|
| LMArena Vision | — | 1288 |
| Furniture Assembly | — | 80% |
Multilingual Not comparable
DeepSeek-R1-Distill-Qwen-32B: —, GPT-6.1 Sol: 54.3 (#46)
| Benchmark | DeepSeek-R1-Distill-Qwen-32B | GPT-6.1 Sol |
|---|---|---|
| LMArena Non-English | — | 1438 |
| LMArena Chinese | — | 1477 |
| LMArena Russian | — | 1455 |
Instruction Following GPT-6.1 Sol leads
DeepSeek-R1-Distill-Qwen-32B: 61.6 (#243), GPT-6.1 Sol: 77.0 (#29)
| Benchmark | DeepSeek-R1-Distill-Qwen-32B | GPT-6.1 Sol |
|---|---|---|
| LiveBench Instruction Following | 55.7% | — |
| LMArena Instruction Following | — | 1468 |
Long Context Not comparable
DeepSeek-R1-Distill-Qwen-32B: —, GPT-6.1 Sol: 44.9 (#54)
| Benchmark | DeepSeek-R1-Distill-Qwen-32B | GPT-6.1 Sol |
|---|---|---|
| LMArena Longer Query | — | 1465 |
Writing & Preference GPT-6.1 Sol leads
DeepSeek-R1-Distill-Qwen-32B: 49.6 (#188), GPT-6.1 Sol: 63.6 (#63)
| Benchmark | DeepSeek-R1-Distill-Qwen-32B | GPT-6.1 Sol |
|---|---|---|
| LMArena Text | — | 1447 |
| LMArena Creative Writing | — | 1432 |
| LMArena Multi-Turn | — | 1449 |
| LiveBench Language | 26.8% | — |
Frequently asked questions
Is DeepSeek-R1-Distill-Qwen-32B better than GPT-6.1 Sol?
GPT-6.1 Sol is the stronger model overall, scoring 65.6 to 35.5 on the Noometry Index.
Is DeepSeek-R1-Distill-Qwen-32B or GPT-6.1 Sol better for coding?
GPT-6.1 Sol scores higher on coding benchmarks: 63.2 versus 36.1 in the Noometry coding category.
How many benchmarks do DeepSeek-R1-Distill-Qwen-32B and GPT-6.1 Sol share?
4 benchmarks have published results for both models. DeepSeek-R1-Distill-Qwen-32B has 14 scored results on Noometry and GPT-6.1 Sol has 34.