Model comparison
DeepSeek LLM 67B vs Mistral Small 3.1
Mistral Small 3.1 is the stronger model overall, scoring 31.7 to 24.9 on the Noometry Index.
Last verified . 14 shared benchmarks.
Summary
- They share 14 benchmarks with published results for both. DeepSeek LLM 67B scores higher in 0 categories and Mistral Small 3.1 in 8 categories; 8 gaps are clear of the uncertainty.
- The widest gap is in knowledge, where Mistral Small 3.1 leads 22.6 to 7.0.
- The biggest single-benchmark swing is GPQA Diamond: 24.6% for DeepSeek LLM 67B and 41.9% for Mistral Small 3.1.
Side by side
| DeepSeek LLM 67B | Mistral Small 3.1 | |
|---|---|---|
| Provider | DeepSeek | Mistral AI |
| Noometry Index | 24.9 | 31.7 |
| Released | 2023-11-29 | 2025-03-17 |
| Weights | Open | Open |
| Context window | — | 128K |
| Max output | — | 102K |
| Input $ / M tokens | — | $0.35 |
| Output $ / M tokens | — | $0.56 |
| Results tracked | 15 | 28 |
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Category by category
Coding Mistral Small 3.1 leads
DeepSeek LLM 67B: 31.9 (#278), Mistral Small 3.1: 38.3 (#179)
| Benchmark | DeepSeek LLM 67B | Mistral Small 3.1 |
|---|---|---|
| LMArena Coding | 1096 | 1309 |
Reasoning Mistral Small 3.1 leads
DeepSeek LLM 67B: 16.5 (#304), Mistral Small 3.1: 19.7 (#254)
| Benchmark | DeepSeek LLM 67B | Mistral Small 3.1 |
|---|---|---|
| Chess Puzzles | 0% | 1% |
| LMArena Hard Prompts | 1070 | 1278 |
| Epoch Capabilities Index | 110.5 | 127.48 |
Math Mistral Small 3.1 leads
DeepSeek LLM 67B: 8.7 (#324), Mistral Small 3.1: 14.7 (#301)
| Benchmark | DeepSeek LLM 67B | Mistral Small 3.1 |
|---|---|---|
| OTIS Mock AIME 2024-2025 | 0.8% | 3.9% |
| LMArena Math | 1108 | 1262 |
| Omni-MATH | — | 24.8% |
| MATH Level 5 | 6.4% | — |
Knowledge Mistral Small 3.1 leads
DeepSeek LLM 67B: 7.0 (#313), Mistral Small 3.1: 22.6 (#271)
| Benchmark | DeepSeek LLM 67B | Mistral Small 3.1 |
|---|---|---|
| GPQA Diamond | 24.6% | 41.9% |
| MMLU-Pro | — | 61% |
| GPQA (HELM) | — | 39.2% |
| LMArena Expert | — | 1257 |
Multimodal Not comparable
DeepSeek LLM 67B: —, Mistral Small 3.1: 33.2 (#99)
| Benchmark | DeepSeek LLM 67B | Mistral Small 3.1 |
|---|---|---|
| LMArena Vision | — | 1136 |
Multilingual Mistral Small 3.1 leads
DeepSeek LLM 67B: 29.4 (#267), Mistral Small 3.1: 41.2 (#209)
| Benchmark | DeepSeek LLM 67B | Mistral Small 3.1 |
|---|---|---|
| LMArena Non-English | 1073 | 1255 |
| LMArena Chinese | 1132 | 1253 |
| LMArena French | — | 1273 |
| LMArena German | — | 1266 |
| LMArena Japanese | — | 1208 |
| LMArena Korean | — | 1206 |
| LMArena Russian | — | 1263 |
| LMArena Spanish | — | 1283 |
Instruction Following Mistral Small 3.1 leads
DeepSeek LLM 67B: 55.4 (#277), Mistral Small 3.1: 63.6 (#230)
| Benchmark | DeepSeek LLM 67B | Mistral Small 3.1 |
|---|---|---|
| LMArena Instruction Following | 1079 | 1264 |
| IFEval | — | 75% |
Long Context Mistral Small 3.1 leads
DeepSeek LLM 67B: 33.1 (#265), Mistral Small 3.1: 39.5 (#178)
| Benchmark | DeepSeek LLM 67B | Mistral Small 3.1 |
|---|---|---|
| LMArena Longer Query | 1092 | 1299 |
Writing & Preference Mistral Small 3.1 leads
DeepSeek LLM 67B: 31.6 (#282), Mistral Small 3.1: 37.0 (#259)
| Benchmark | DeepSeek LLM 67B | Mistral Small 3.1 |
|---|---|---|
| LMArena Text | 1105 | 1277 |
| LMArena Creative Writing | 1067 | 1253 |
| LMArena Multi-Turn | 1082 | 1270 |
| EQ-Bench Creative Writing | — | 761 |
| WildBench | — | 78.8% |
Frequently asked questions
Is DeepSeek LLM 67B better than Mistral Small 3.1?
Mistral Small 3.1 is the stronger model overall, scoring 31.7 to 24.9 on the Noometry Index.
Is DeepSeek LLM 67B or Mistral Small 3.1 better for coding?
Mistral Small 3.1 scores higher on coding benchmarks: 38.3 versus 31.9 in the Noometry coding category.
How many benchmarks do DeepSeek LLM 67B and Mistral Small 3.1 share?
14 benchmarks have published results for both models. DeepSeek LLM 67B has 15 scored results on Noometry and Mistral Small 3.1 has 28.