Model comparison
DeepSeek-R1-Distill-Qwen-1.5B vs GPT-6 Sol
GPT-6 Sol is the stronger model overall, scoring 61.8 to 26.1 on the Noometry Index.
Last verified . 2 shared benchmarks.
DeepSeekSummary
- They share 2 benchmarks with published results for both. DeepSeek-R1-Distill-Qwen-1.5B scores higher in 0 categories and GPT-6 Sol in 4 categories; 4 gaps are clear of the uncertainty.
- The widest gap is in math, where GPT-6 Sol leads 87.2 to 23.0.
- The biggest single-benchmark swing is OTIS Mock AIME 2024-2025: 21.4% for DeepSeek-R1-Distill-Qwen-1.5B and 100% for GPT-6 Sol.
- DeepSeek-R1-Distill-Qwen-1.5B has downloadable open weights; the other is API-only.
Side by side
| DeepSeek-R1-Distill-Qwen-1.5B | GPT-6 Sol | |
|---|---|---|
| Provider | DeepSeek | OpenAI |
| Noometry Index | 26.1 | 61.8 |
| Released | 2025-01-20 | 2026-09-22 |
| Weights | Open | Proprietary |
| Context window | — | 1.05M |
| Max output | — | 128K |
| Input $ / M tokens | — | $2 |
| Output $ / M tokens | — | $10 |
| Results tracked | 5 | 45 |
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Category by category
Coding GPT-6 Sol leads
DeepSeek-R1-Distill-Qwen-1.5B: 21.8 (#336), GPT-6 Sol: 60.1 (#11)
| Benchmark | DeepSeek-R1-Distill-Qwen-1.5B | GPT-6 Sol |
|---|---|---|
| DeepSWE | — | 68.8% |
| FrontierCode | — | 49.3% |
| LMArena WebDev | — | 1688 |
| SciCode | — | 57.6% |
| BigCodeBench Instruct | 7% | — |
| LMArena Coding | — | 1447 |
| BigCodeBench Complete | 7.9% | — |
| ALE-Bench | — | 2,462 |
Agentic & Tool Use Not comparable
DeepSeek-R1-Distill-Qwen-1.5B: —, GPT-6 Sol: 37.2 (#36)
| Benchmark | DeepSeek-R1-Distill-Qwen-1.5B | GPT-6 Sol |
|---|---|---|
| APEX-Agents | — | 54.3% |
| GDP.pdf | — | 26.4% |
| Vending-Bench 2 | — | 14,428 |
Reasoning GPT-6 Sol leads
DeepSeek-R1-Distill-Qwen-1.5B: 19.2 (#262), GPT-6 Sol: 74.0 (#9)
| Benchmark | DeepSeek-R1-Distill-Qwen-1.5B | GPT-6 Sol |
|---|---|---|
| ARC-AGI-2 | — | 89.6% |
| NYT Connections (extended) | — | 90.1% |
| ARC-AGI-1 | — | 95.5% |
| CritPt | — | 30.9% |
| Chess Puzzles | 0% | — |
| EBR-Bench | — | 53.3% |
| LMArena Hard Prompts | — | 1418 |
| Mystery Game Puzzles | — | 56% |
| DTBench | — | 97.3% |
| LMCA | — | 59.1% |
| Epoch Capabilities Index | — | 162.72 |
Math GPT-6 Sol leads
DeepSeek-R1-Distill-Qwen-1.5B: 23.0 (#274), GPT-6 Sol: 87.2 (#7)
| Benchmark | DeepSeek-R1-Distill-Qwen-1.5B | GPT-6 Sol |
|---|---|---|
| OTIS Mock AIME 2024-2025 | 21.4% | 100% |
| FrontierMath (Tiers 1-3) | — | 89.8% |
| FrontierMath Tier 4 | — | 90% |
| ProofBench | — | 83% |
| LMArena Math | — | 1402 |
Knowledge GPT-6 Sol leads
DeepSeek-R1-Distill-Qwen-1.5B: 16.0 (#290), GPT-6 Sol: 64.8 (#15)
| Benchmark | DeepSeek-R1-Distill-Qwen-1.5B | GPT-6 Sol |
|---|---|---|
| GPQA Diamond | 33.6% | 94.3% |
| SimpleQA Verified | — | 60.7% |
| Vectara Hallucination Rate | — | 6.5% |
| LMArena Expert | — | 1439 |
Multimodal Not comparable
DeepSeek-R1-Distill-Qwen-1.5B: —, GPT-6 Sol: 47.6 (#10)
| Benchmark | DeepSeek-R1-Distill-Qwen-1.5B | GPT-6 Sol |
|---|---|---|
| LMArena Vision | — | 1245 |
| Blueprint-Bench 2 | — | 36.9% |
| Furniture Assembly | — | 58.3% |
Multilingual Not comparable
DeepSeek-R1-Distill-Qwen-1.5B: —, GPT-6 Sol: 50.5 (#118)
| Benchmark | DeepSeek-R1-Distill-Qwen-1.5B | GPT-6 Sol |
|---|---|---|
| LMArena Non-English | — | 1385 |
| LMArena Chinese | — | 1405 |
| LMArena French | — | 1410 |
| LMArena German | — | 1390 |
| LMArena Japanese | — | 1385 |
| LMArena Korean | — | 1341 |
| LMArena Russian | — | 1401 |
| LMArena Spanish | — | 1384 |
Instruction Following Not comparable
DeepSeek-R1-Distill-Qwen-1.5B: —, GPT-6 Sol: 74.5 (#94)
| Benchmark | DeepSeek-R1-Distill-Qwen-1.5B | GPT-6 Sol |
|---|---|---|
| LMArena Instruction Following | — | 1412 |
Long Context Not comparable
DeepSeek-R1-Distill-Qwen-1.5B: —, GPT-6 Sol: 43.1 (#108)
| Benchmark | DeepSeek-R1-Distill-Qwen-1.5B | GPT-6 Sol |
|---|---|---|
| LMArena Longer Query | — | 1411 |
Writing & Preference Not comparable
DeepSeek-R1-Distill-Qwen-1.5B: —, GPT-6 Sol: 71.9 (#18)
| Benchmark | DeepSeek-R1-Distill-Qwen-1.5B | GPT-6 Sol |
|---|---|---|
| LMArena Text | — | 1395 |
| LMArena Creative Writing | — | 1378 |
| EQ-Bench Creative Writing | — | 2125 |
| LMArena Multi-Turn | — | 1412 |
Frequently asked questions
Is DeepSeek-R1-Distill-Qwen-1.5B better than GPT-6 Sol?
GPT-6 Sol is the stronger model overall, scoring 61.8 to 26.1 on the Noometry Index.
Is DeepSeek-R1-Distill-Qwen-1.5B or GPT-6 Sol better for coding?
GPT-6 Sol scores higher on coding benchmarks: 60.1 versus 21.8 in the Noometry coding category.
How many benchmarks do DeepSeek-R1-Distill-Qwen-1.5B and GPT-6 Sol share?
2 benchmarks have published results for both models. DeepSeek-R1-Distill-Qwen-1.5B has 5 scored results on Noometry and GPT-6 Sol has 45.