Model comparison
DeepSeek-V2 (MoE-236B, May 2024) vs Mistral Medium
Mistral Medium has enough public results to be ranked (#218); DeepSeek-V2 (MoE-236B, May 2024) does not yet, so treat this comparison as directional.
Last verified . 0 shared benchmarks.
DeepSeek
Mistral AISummary
- The widest gap is in coding, where DeepSeek-V2 (MoE-236B, May 2024) leads 40.4 to 34.2.
Side by side
| DeepSeek-V2 (MoE-236B, May 2024) | Mistral Medium | |
|---|---|---|
| Provider | DeepSeek | Mistral AI |
| Noometry Index | 40.3 | 36.3 |
| Released | 2024-05-07 | 2023-12-11 |
| Weights | Open | Open |
| Context window | — | 262K |
| Max output | — | 262K |
| Input $ / M tokens | — | $1.50 |
| Output $ / M tokens | — | $7.50 |
| Results tracked | 10 | 36 |
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Category by category
Coding DeepSeek-V2 (MoE-236B, May 2024) leads
DeepSeek-V2 (MoE-236B, May 2024): 40.4 (#139), Mistral Medium: 34.2 (#243)
| Benchmark | DeepSeek-V2 (MoE-236B, May 2024) | Mistral Medium |
|---|---|---|
| FrontierCode | — | 8% |
| SciCode | — | 40.2% |
| WeirdML | — | 43.7% |
| BigCodeBench Instruct | 48.9% | — |
| LMArena Coding | — | 1434 |
| BigCodeBench Complete | 59.4% | — |
| ALE-Bench | — | 763.98 |
Agentic & Tool Use Not comparable
DeepSeek-V2 (MoE-236B, May 2024): —, Mistral Medium: 28.3 (#90)
| Benchmark | DeepSeek-V2 (MoE-236B, May 2024) | Mistral Medium |
|---|---|---|
| Berkeley Function Calling Leaderboard | — | 37.7% |
Reasoning Not comparable
DeepSeek-V2 (MoE-236B, May 2024): —, Mistral Medium: 24.0 (#167)
| Benchmark | DeepSeek-V2 (MoE-236B, May 2024) | Mistral Medium |
|---|---|---|
| Kagi LLM Benchmark | — | 50% |
| CritPt | — | 0% |
| LMArena Hard Prompts | — | 1426 |
| DTBench | — | 75.5% |
| LMCA | — | 26.1% |
| Surface Evolver Bench | — | 26.9% |
| BIG-Bench Hard | 78.8% | — |
| Epoch Capabilities Index | 124.77 | — |
| HellaSwag | 87.1% | — |
| PIQA | 83.9% | — |
| WinoGrande | 86.3% | — |
Math Not comparable
DeepSeek-V2 (MoE-236B, May 2024): —, Mistral Medium: 28.1 (#245)
| Benchmark | DeepSeek-V2 (MoE-236B, May 2024) | Mistral Medium |
|---|---|---|
| OTIS Mock AIME 2024-2025 | — | 32.2% |
| ProofBench | — | 9% |
| LMArena Math | — | 1408 |
| MATH Level 5 | — | 81.6% |
| FrontierMath (Feb 2025 set) | — | 0.3% |
Knowledge Not comparable
DeepSeek-V2 (MoE-236B, May 2024): —, Mistral Medium: 25.0 (#265)
| Benchmark | DeepSeek-V2 (MoE-236B, May 2024) | Mistral Medium |
|---|---|---|
| GPQA Diamond | — | 59.5% |
| Humanity's Last Exam | — | 4.5% |
| Vectara Hallucination Rate | — | 22.7% |
| LMArena Expert | — | 1408 |
| ARC (AI2) Challenge | 92.2% | — |
| MMLU | 78.4% | — |
| TriviaQA | 80% | — |
Multimodal Not comparable
DeepSeek-V2 (MoE-236B, May 2024): —, Mistral Medium: 35.3 (#88)
| Benchmark | DeepSeek-V2 (MoE-236B, May 2024) | Mistral Medium |
|---|---|---|
| LMArena Vision | — | 1172 |
Multilingual Not comparable
DeepSeek-V2 (MoE-236B, May 2024): —, Mistral Medium: 52.1 (#91)
| Benchmark | DeepSeek-V2 (MoE-236B, May 2024) | Mistral Medium |
|---|---|---|
| LMArena Non-English | — | 1408 |
| LMArena Chinese | — | 1447 |
| LMArena French | — | 1459 |
| LMArena German | — | 1432 |
| LMArena Japanese | — | 1378 |
| LMArena Korean | — | 1380 |
| LMArena Russian | — | 1411 |
| LMArena Spanish | — | 1433 |
Instruction Following Not comparable
DeepSeek-V2 (MoE-236B, May 2024): —, Mistral Medium: 73.7 (#116)
| Benchmark | DeepSeek-V2 (MoE-236B, May 2024) | Mistral Medium |
|---|---|---|
| LMArena Instruction Following | — | 1398 |
Long Context Not comparable
DeepSeek-V2 (MoE-236B, May 2024): —, Mistral Medium: 42.9 (#114)
| Benchmark | DeepSeek-V2 (MoE-236B, May 2024) | Mistral Medium |
|---|---|---|
| LMArena Longer Query | — | 1406 |
Writing & Preference Not comparable
DeepSeek-V2 (MoE-236B, May 2024): —, Mistral Medium: 60.0 (#103)
| Benchmark | DeepSeek-V2 (MoE-236B, May 2024) | Mistral Medium |
|---|---|---|
| LMArena Text | — | 1424 |
| LMArena Creative Writing | — | 1391 |
| Short-Story Creative Writing | — | 77.3% |
| LMArena Multi-Turn | — | 1418 |
Frequently asked questions
Is DeepSeek-V2 (MoE-236B, May 2024) better than Mistral Medium?
Mistral Medium has enough public results to be ranked (#218); DeepSeek-V2 (MoE-236B, May 2024) does not yet, so treat this comparison as directional.
Is DeepSeek-V2 (MoE-236B, May 2024) or Mistral Medium better for coding?
DeepSeek-V2 (MoE-236B, May 2024) scores higher on coding benchmarks: 40.4 versus 34.2 in the Noometry coding category.
How many benchmarks do DeepSeek-V2 (MoE-236B, May 2024) and Mistral Medium share?
0 benchmarks have published results for both models. DeepSeek-V2 (MoE-236B, May 2024) has 10 scored results on Noometry and Mistral Medium has 36.