Model comparison
DeepSeek-V3.1-Terminus vs Mistral Small 3.1
DeepSeek-V3.1-Terminus is the stronger model overall, scoring 42.6 to 31.4 on the Noometry Index.
Last verified . 10 shared benchmarks.
DeepSeek
Mistral AISummary
- They share 10 benchmarks with published results for both. DeepSeek-V3.1-Terminus scores higher in 7 categories and Mistral Small 3.1 in 0 categories; 7 gaps are clear of the uncertainty.
- The widest gap is in writing & preference, where DeepSeek-V3.1-Terminus leads 61.3 to 37.2.
- Mistral Small 3.1 is cheaper at $0.35 / $0.56 per million input/output tokens, against $0.30 / $1 for DeepSeek-V3.1-Terminus.
- DeepSeek-V3.1-Terminus accepts more context: 164K tokens versus 128K.
Side by side
| DeepSeek-V3.1-Terminus | Mistral Small 3.1 | |
|---|---|---|
| Provider | DeepSeek | Mistral AI |
| Noometry Index | 42.6 | 31.4 |
| Released | 2025-09-22 | 2025-03-17 |
| Weights | Open | Open |
| Context window | 164K | 128K |
| Max output | 66K | 102K |
| Input $ / M tokens | $0.30 | $0.35 |
| Output $ / M tokens | $1 | $0.56 |
| Results tracked | 16 | 28 |
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Category by category
Coding DeepSeek-V3.1-Terminus leads
DeepSeek-V3.1-Terminus: 41.5 (#114), Mistral Small 3.1: 37.7 (#175)
| Benchmark | DeepSeek-V3.1-Terminus | Mistral Small 3.1 |
|---|---|---|
| LMArena Coding | 1426 | 1309 |
| SciCode | 40.6% | — |
| ALE-Bench | 745.17 | — |
Reasoning DeepSeek-V3.1-Terminus leads
DeepSeek-V3.1-Terminus: 25.7 (#126), Mistral Small 3.1: 18.9 (#249)
| Benchmark | DeepSeek-V3.1-Terminus | Mistral Small 3.1 |
|---|---|---|
| LMArena Hard Prompts | 1427 | 1278 |
| Kagi LLM Benchmark | 57.4% | — |
| CritPt | 1.7% | — |
| Chess Puzzles | — | 1% |
| DTBench | 81.3% | — |
| LMCA | 28.6% | — |
| Epoch Capabilities Index | — | 127.48 |
Math DeepSeek-V3.1-Terminus leads
DeepSeek-V3.1-Terminus: 35.7 (#138), Mistral Small 3.1: 13.7 (#295)
| Benchmark | DeepSeek-V3.1-Terminus | Mistral Small 3.1 |
|---|---|---|
| LMArena Math | 1402 | 1261 |
| OTIS Mock AIME 2024-2025 | — | 3.9% |
| Omni-MATH | — | 24.8% |
Knowledge Not comparable
DeepSeek-V3.1-Terminus: —, Mistral Small 3.1: 22.6 (#266)
| Benchmark | DeepSeek-V3.1-Terminus | Mistral Small 3.1 |
|---|---|---|
| GPQA Diamond | — | 41.9% |
| MMLU-Pro | — | 61% |
| GPQA (HELM) | — | 39.2% |
| LMArena Expert | — | 1258 |
Multimodal Not comparable
DeepSeek-V3.1-Terminus: —, Mistral Small 3.1: 32.6 (#93)
| Benchmark | DeepSeek-V3.1-Terminus | Mistral Small 3.1 |
|---|---|---|
| LMArena Vision | — | 1136 |
Multilingual DeepSeek-V3.1-Terminus leads
DeepSeek-V3.1-Terminus: 52.3 (#87), Mistral Small 3.1: 41.4 (#204)
| Benchmark | DeepSeek-V3.1-Terminus | Mistral Small 3.1 |
|---|---|---|
| LMArena Non-English | 1407 | 1255 |
| LMArena Russian | 1434 | 1263 |
| LMArena Chinese | — | 1254 |
| LMArena French | — | 1270 |
| LMArena German | — | 1266 |
| LMArena Japanese | — | 1210 |
| LMArena Korean | — | 1206 |
| LMArena Spanish | — | 1283 |
Instruction Following DeepSeek-V3.1-Terminus leads
DeepSeek-V3.1-Terminus: 74.4 (#96), Mistral Small 3.1: 63.8 (#225)
| Benchmark | DeepSeek-V3.1-Terminus | Mistral Small 3.1 |
|---|---|---|
| LMArena Instruction Following | 1406 | 1264 |
| IFEval | — | 75% |
Long Context DeepSeek-V3.1-Terminus leads
DeepSeek-V3.1-Terminus: 43.5 (#88), Mistral Small 3.1: 39.5 (#172)
| Benchmark | DeepSeek-V3.1-Terminus | Mistral Small 3.1 |
|---|---|---|
| LMArena Longer Query | 1426 | 1300 |
Writing & Preference DeepSeek-V3.1-Terminus leads
DeepSeek-V3.1-Terminus: 61.3 (#87), Mistral Small 3.1: 37.2 (#254)
| Benchmark | DeepSeek-V3.1-Terminus | Mistral Small 3.1 |
|---|---|---|
| LMArena Text | 1420 | 1278 |
| LMArena Creative Writing | 1404 | 1253 |
| LMArena Multi-Turn | 1411 | 1270 |
| EQ-Bench Creative Writing | — | 761 |
| WildBench | — | 78.8% |
Frequently asked questions
Is DeepSeek-V3.1-Terminus better than Mistral Small 3.1?
DeepSeek-V3.1-Terminus is the stronger model overall, scoring 42.6 to 31.4 on the Noometry Index.
Which is cheaper, DeepSeek-V3.1-Terminus or Mistral Small 3.1?
Mistral Small 3.1 is cheaper. It lists at $0.35 per million input tokens and $0.56 per million output tokens; DeepSeek-V3.1-Terminus lists at $0.30 and $1.
Is DeepSeek-V3.1-Terminus or Mistral Small 3.1 better for coding?
DeepSeek-V3.1-Terminus scores higher on coding benchmarks: 41.5 versus 37.7 in the Noometry coding category.
Which has the bigger context window?
DeepSeek-V3.1-Terminus does, with 164K tokens against 128K.
How many benchmarks do DeepSeek-V3.1-Terminus and Mistral Small 3.1 share?
10 benchmarks have published results for both models. DeepSeek-V3.1-Terminus has 16 scored results on Noometry and Mistral Small 3.1 has 28.