Model comparison
DeepSeek-R1-Distill-Qwen-32B vs Mistral Medium 3.5
Mistral Medium 3.5 is the stronger model overall, scoring 40.2 to 35.5 on the Noometry Index.
Last verified . 1 shared benchmarks.
DeepSeek
Mistral AISummary
- They share 1 benchmark with published results for both. DeepSeek-R1-Distill-Qwen-32B scores higher in 2 categories and Mistral Medium 3.5 in 4 categories; 4 gaps are clear of the uncertainty.
- The widest gap is in instruction following, where Mistral Medium 3.5 leads 74.6 to 61.6.
Side by side
| DeepSeek-R1-Distill-Qwen-32B | Mistral Medium 3.5 | |
|---|---|---|
| Provider | DeepSeek | Mistral AI |
| Noometry Index | 35.5 | 40.2 |
| Released | 2025-01-20 | — |
| Weights | Open | Open |
| Context window | — | 262K |
| Max output | — | 210K |
| Input $ / M tokens | — | $1.50 |
| Output $ / M tokens | — | $7.50 |
| Results tracked | 14 | 22 |
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Category by category
Coding Too close to call
DeepSeek-R1-Distill-Qwen-32B: 36.1 (#212), Mistral Medium 3.5: 36.0 (#213)
| Benchmark | DeepSeek-R1-Distill-Qwen-32B | Mistral Medium 3.5 |
|---|---|---|
| LMArena WebDev | — | 1264 |
| BigCodeBench Instruct | 43.9% | — |
| LiveBench Coding | 33.7% | — |
| LMArena Coding | — | 1461 |
| BigCodeBench Complete | 54.9% | — |
Agentic & Tool Use Not comparable
DeepSeek-R1-Distill-Qwen-32B: 28.1 (#94), Mistral Medium 3.5: —
| Benchmark | DeepSeek-R1-Distill-Qwen-32B | Mistral Medium 3.5 |
|---|---|---|
| BALROG | 19.5% | — |
Reasoning Too close to call
DeepSeek-R1-Distill-Qwen-32B: 18.2 (#284), Mistral Medium 3.5: 17.3 (#295)
| Benchmark | DeepSeek-R1-Distill-Qwen-32B | Mistral Medium 3.5 |
|---|---|---|
| Epoch Capabilities Index | 137.44 | 141.35 |
| Kagi LLM Benchmark | — | 41.4% |
| NYT Connections (extended) | — | 12.9% |
| Chess Puzzles | 1% | — |
| LiveBench Reasoning | 52.3% | — |
| LMArena Hard Prompts | — | 1436 |
| LiveBench Data Analysis | 45.4% | — |
| LiveBench | 45.5% | — |
Math Mistral Medium 3.5 leads
DeepSeek-R1-Distill-Qwen-32B: 34.5 (#194), Mistral Medium 3.5: 39.1 (#113)
| Benchmark | DeepSeek-R1-Distill-Qwen-32B | Mistral Medium 3.5 |
|---|---|---|
| OTIS Mock AIME 2024-2025 | 55.6% | — |
| LiveBench Math | 59.4% | — |
| LMArena Math | — | 1431 |
Knowledge Mistral Medium 3.5 leads
DeepSeek-R1-Distill-Qwen-32B: 35.7 (#182), Mistral Medium 3.5: 40.0 (#126)
| Benchmark | DeepSeek-R1-Distill-Qwen-32B | Mistral Medium 3.5 |
|---|---|---|
| GPQA Diamond | 64.1% | — |
| LMArena Expert | — | 1432 |
Multimodal Not comparable
DeepSeek-R1-Distill-Qwen-32B: —, Mistral Medium 3.5: 38.3 (#65)
| Benchmark | DeepSeek-R1-Distill-Qwen-32B | Mistral Medium 3.5 |
|---|---|---|
| LMArena Vision | — | 1223 |
Multilingual Not comparable
DeepSeek-R1-Distill-Qwen-32B: —, Mistral Medium 3.5: 51.9 (#100)
| Benchmark | DeepSeek-R1-Distill-Qwen-32B | Mistral Medium 3.5 |
|---|---|---|
| LMArena Non-English | — | 1404 |
| LMArena Chinese | — | 1442 |
| LMArena French | — | 1448 |
| LMArena German | — | 1451 |
| LMArena Korean | — | 1385 |
| LMArena Russian | — | 1395 |
| LMArena Spanish | — | 1409 |
Instruction Following Mistral Medium 3.5 leads
DeepSeek-R1-Distill-Qwen-32B: 61.6 (#243), Mistral Medium 3.5: 74.6 (#90)
| Benchmark | DeepSeek-R1-Distill-Qwen-32B | Mistral Medium 3.5 |
|---|---|---|
| LiveBench Instruction Following | 55.7% | — |
| LMArena Instruction Following | — | 1415 |
Long Context Not comparable
DeepSeek-R1-Distill-Qwen-32B: —, Mistral Medium 3.5: 43.2 (#103)
| Benchmark | DeepSeek-R1-Distill-Qwen-32B | Mistral Medium 3.5 |
|---|---|---|
| LMArena Longer Query | — | 1415 |
Writing & Preference Mistral Medium 3.5 leads
DeepSeek-R1-Distill-Qwen-32B: 49.6 (#188), Mistral Medium 3.5: 58.5 (#117)
| Benchmark | DeepSeek-R1-Distill-Qwen-32B | Mistral Medium 3.5 |
|---|---|---|
| LMArena Text | — | 1421 |
| LMArena Creative Writing | — | 1374 |
| EQ-Bench 4 | — | 993 |
| LMArena Multi-Turn | — | 1423 |
| LiveBench Language | 26.8% | — |
Frequently asked questions
Is DeepSeek-R1-Distill-Qwen-32B better than Mistral Medium 3.5?
Mistral Medium 3.5 is the stronger model overall, scoring 40.2 to 35.5 on the Noometry Index.
Is DeepSeek-R1-Distill-Qwen-32B or Mistral Medium 3.5 better for coding?
They score almost the same on coding (36.1 vs 36.0); test both on your own repository before choosing.
How many benchmarks do DeepSeek-R1-Distill-Qwen-32B and Mistral Medium 3.5 share?
1 benchmark has published results for both models. DeepSeek-R1-Distill-Qwen-32B has 14 scored results on Noometry and Mistral Medium 3.5 has 22.