Model comparison
DeepSeek LLM 67B vs Mistral Medium 3.5
Mistral Medium 3.5 is the stronger model overall, scoring 40.2 to 24.9 on the Noometry Index.
Last verified . 11 shared benchmarks.
DeepSeek
Mistral AISummary
- They share 11 benchmarks with published results for both. DeepSeek LLM 67B scores higher in 0 categories and Mistral Medium 3.5 in 8 categories; 7 gaps are clear of the uncertainty.
- The widest gap is in knowledge, where Mistral Medium 3.5 leads 40.0 to 7.0.
Side by side
| DeepSeek LLM 67B | Mistral Medium 3.5 | |
|---|---|---|
| Provider | DeepSeek | Mistral AI |
| Noometry Index | 24.9 | 40.2 |
| Released | 2023-11-29 | — |
| Weights | Open | Open |
| Context window | — | 262K |
| Max output | — | 210K |
| Input $ / M tokens | — | $1.50 |
| Output $ / M tokens | — | $7.50 |
| Results tracked | 15 | 22 |
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Category by category
Coding Mistral Medium 3.5 leads
DeepSeek LLM 67B: 31.9 (#278), Mistral Medium 3.5: 36.0 (#213)
| Benchmark | DeepSeek LLM 67B | Mistral Medium 3.5 |
|---|---|---|
| LMArena Coding | 1096 | 1461 |
| LMArena WebDev | — | 1264 |
Reasoning Too close to call
DeepSeek LLM 67B: 16.5 (#304), Mistral Medium 3.5: 17.3 (#295)
| Benchmark | DeepSeek LLM 67B | Mistral Medium 3.5 |
|---|---|---|
| LMArena Hard Prompts | 1070 | 1436 |
| Epoch Capabilities Index | 110.5 | 141.35 |
| Kagi LLM Benchmark | — | 41.4% |
| NYT Connections (extended) | — | 12.9% |
| Chess Puzzles | 0% | — |
Math Mistral Medium 3.5 leads
DeepSeek LLM 67B: 8.7 (#324), Mistral Medium 3.5: 39.1 (#113)
| Benchmark | DeepSeek LLM 67B | Mistral Medium 3.5 |
|---|---|---|
| LMArena Math | 1108 | 1431 |
| OTIS Mock AIME 2024-2025 | 0.8% | — |
| MATH Level 5 | 6.4% | — |
Knowledge Mistral Medium 3.5 leads
DeepSeek LLM 67B: 7.0 (#313), Mistral Medium 3.5: 40.0 (#126)
| Benchmark | DeepSeek LLM 67B | Mistral Medium 3.5 |
|---|---|---|
| GPQA Diamond | 24.6% | — |
| LMArena Expert | — | 1432 |
Multimodal Not comparable
DeepSeek LLM 67B: —, Mistral Medium 3.5: 38.3 (#65)
| Benchmark | DeepSeek LLM 67B | Mistral Medium 3.5 |
|---|---|---|
| LMArena Vision | — | 1223 |
Multilingual Mistral Medium 3.5 leads
DeepSeek LLM 67B: 29.4 (#267), Mistral Medium 3.5: 51.9 (#100)
| Benchmark | DeepSeek LLM 67B | Mistral Medium 3.5 |
|---|---|---|
| LMArena Non-English | 1073 | 1404 |
| LMArena Chinese | 1132 | 1442 |
| LMArena French | — | 1448 |
| LMArena German | — | 1451 |
| LMArena Korean | — | 1385 |
| LMArena Russian | — | 1395 |
| LMArena Spanish | — | 1409 |
Instruction Following Mistral Medium 3.5 leads
DeepSeek LLM 67B: 55.4 (#277), Mistral Medium 3.5: 74.6 (#90)
| Benchmark | DeepSeek LLM 67B | Mistral Medium 3.5 |
|---|---|---|
| LMArena Instruction Following | 1079 | 1415 |
Long Context Mistral Medium 3.5 leads
DeepSeek LLM 67B: 33.1 (#265), Mistral Medium 3.5: 43.2 (#103)
| Benchmark | DeepSeek LLM 67B | Mistral Medium 3.5 |
|---|---|---|
| LMArena Longer Query | 1092 | 1415 |
Writing & Preference Mistral Medium 3.5 leads
DeepSeek LLM 67B: 31.6 (#282), Mistral Medium 3.5: 58.5 (#117)
| Benchmark | DeepSeek LLM 67B | Mistral Medium 3.5 |
|---|---|---|
| LMArena Text | 1105 | 1421 |
| LMArena Creative Writing | 1067 | 1374 |
| LMArena Multi-Turn | 1082 | 1423 |
| EQ-Bench 4 | — | 993 |
Frequently asked questions
Is DeepSeek LLM 67B better than Mistral Medium 3.5?
Mistral Medium 3.5 is the stronger model overall, scoring 40.2 to 24.9 on the Noometry Index.
Is DeepSeek LLM 67B or Mistral Medium 3.5 better for coding?
Mistral Medium 3.5 scores higher on coding benchmarks: 36.0 versus 31.9 in the Noometry coding category.
How many benchmarks do DeepSeek LLM 67B and Mistral Medium 3.5 share?
11 benchmarks have published results for both models. DeepSeek LLM 67B has 15 scored results on Noometry and Mistral Medium 3.5 has 22.