Model comparison
DeepSeek-V3.1-Terminus vs Mistral Small
DeepSeek-V3.1-Terminus is the stronger model overall, scoring 43.1 to 33.4 on the Noometry Index. Mistral Small costs 1.7× less per token, which makes it the better buy when DeepSeek-V3.1-Terminus's lead doesn't matter for your workload.
Last verified . 16 shared benchmarks.
DeepSeek
Mistral AISummary
- They share 16 benchmarks with published results for both. DeepSeek-V3.1-Terminus scores higher in 7 categories and Mistral Small in 0 categories; 7 gaps are clear of the uncertainty.
- The widest gap is in math, where DeepSeek-V3.1-Terminus leads 38.5 to 16.4.
- The biggest single-benchmark swing is Kagi LLM Benchmark: 57.4% for DeepSeek-V3.1-Terminus and 37.8% for Mistral Small.
- Mistral Small is cheaper at $0.15 / $0.60 per million input/output tokens, against $0.27 / $1 for DeepSeek-V3.1-Terminus.
- Mistral Small accepts more context: 262K tokens versus 164K.
Side by side
| DeepSeek-V3.1-Terminus | Mistral Small | |
|---|---|---|
| Provider | DeepSeek | Mistral AI |
| Noometry Index | 43.1 | 33.4 |
| Released | 2025-09-22 | 2024-02-26 |
| Weights | Open | Open |
| Context window | 164K | 262K |
| Max output | 147K | 256K |
| Input $ / M tokens | $0.27 | $0.15 |
| Output $ / M tokens | $1 | $0.60 |
| Results tracked | 16 | 39 |
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Category by category
Coding DeepSeek-V3.1-Terminus leads
DeepSeek-V3.1-Terminus: 42.0 (#113), Mistral Small: 34.0 (#247)
| Benchmark | DeepSeek-V3.1-Terminus | Mistral Small |
|---|---|---|
| SciCode | 40.6% | 26.5% |
| LMArena Coding | 1426 | 1362 |
| ALE-Bench | 745.17 | 497.62 |
| BigCodeBench Instruct | — | 36.1% |
| LiveBench Coding | — | 36.2% |
| BigCodeBench Complete | — | 46.6% |
Agentic & Tool Use Not comparable
DeepSeek-V3.1-Terminus: —, Mistral Small: 28.1 (#93)
| Benchmark | DeepSeek-V3.1-Terminus | Mistral Small |
|---|---|---|
| Berkeley Function Calling Leaderboard | — | 37.1% |
Reasoning DeepSeek-V3.1-Terminus leads
DeepSeek-V3.1-Terminus: 26.4 (#133), Mistral Small: 19.8 (#250)
| Benchmark | DeepSeek-V3.1-Terminus | Mistral Small |
|---|---|---|
| Kagi LLM Benchmark | 57.4% | 37.8% |
| CritPt | 1.7% | 0% |
| LMArena Hard Prompts | 1426 | 1335 |
| DTBench | 81.3% | 70.9% |
| LMCA | 28.6% | 20.6% |
| LiveBench Reasoning | — | 44.8% |
| LiveBench Data Analysis | — | 53.7% |
| LiveBench | — | 44% |
Math DeepSeek-V3.1-Terminus leads
DeepSeek-V3.1-Terminus: 38.5 (#137), Mistral Small: 16.4 (#293)
| Benchmark | DeepSeek-V3.1-Terminus | Mistral Small |
|---|---|---|
| LMArena Math | 1402 | 1341 |
| OTIS Mock AIME 2024-2025 | — | 5.8% |
| LiveBench Math | — | 39.9% |
| MATH Level 5 | — | 46.8% |
Knowledge Not comparable
DeepSeek-V3.1-Terminus: —, Mistral Small: 31.0 (#222)
| Benchmark | DeepSeek-V3.1-Terminus | Mistral Small |
|---|---|---|
| GPQA Diamond | — | 47.5% |
| Vectara Hallucination Rate | — | 5.1% |
| LMArena Expert | — | 1291 |
| MMLU | — | 68.7% |
Multimodal Not comparable
DeepSeek-V3.1-Terminus: —, Mistral Small: 33.5 (#96)
| Benchmark | DeepSeek-V3.1-Terminus | Mistral Small |
|---|---|---|
| LMArena Vision | — | 1142 |
Multilingual DeepSeek-V3.1-Terminus leads
DeepSeek-V3.1-Terminus: 52.1 (#92), Mistral Small: 45.5 (#169)
| Benchmark | DeepSeek-V3.1-Terminus | Mistral Small |
|---|---|---|
| LMArena Non-English | 1407 | 1315 |
| LMArena Russian | 1436 | 1324 |
| LMArena Chinese | — | 1340 |
| LMArena French | — | 1337 |
| LMArena German | — | 1340 |
| LMArena Japanese | — | 1275 |
| LMArena Korean | — | 1259 |
| LMArena Spanish | — | 1346 |
Instruction Following DeepSeek-V3.1-Terminus leads
DeepSeek-V3.1-Terminus: 74.0 (#106), Mistral Small: 66.4 (#209)
| Benchmark | DeepSeek-V3.1-Terminus | Mistral Small |
|---|---|---|
| LMArena Instruction Following | 1404 | 1310 |
| LiveBench Instruction Following | — | 63.7% |
Long Context DeepSeek-V3.1-Terminus leads
DeepSeek-V3.1-Terminus: 43.4 (#97), Mistral Small: 40.4 (#156)
| Benchmark | DeepSeek-V3.1-Terminus | Mistral Small |
|---|---|---|
| LMArena Longer Query | 1421 | 1327 |
Writing & Preference DeepSeek-V3.1-Terminus leads
DeepSeek-V3.1-Terminus: 61.0 (#92), Mistral Small: 52.5 (#171)
| Benchmark | DeepSeek-V3.1-Terminus | Mistral Small |
|---|---|---|
| LMArena Text | 1419 | 1338 |
| LMArena Creative Writing | 1403 | 1305 |
| LMArena Multi-Turn | 1411 | 1344 |
| LiveBench Language | — | 30.5% |
Frequently asked questions
Is DeepSeek-V3.1-Terminus better than Mistral Small?
DeepSeek-V3.1-Terminus is the stronger model overall, scoring 43.1 to 33.4 on the Noometry Index. Mistral Small costs 1.7× less per token, which makes it the better buy when DeepSeek-V3.1-Terminus's lead doesn't matter for your workload.
Which is cheaper, DeepSeek-V3.1-Terminus or Mistral Small?
Mistral Small is cheaper. It lists at $0.15 per million input tokens and $0.60 per million output tokens; DeepSeek-V3.1-Terminus lists at $0.27 and $1.
Is DeepSeek-V3.1-Terminus or Mistral Small better for coding?
DeepSeek-V3.1-Terminus scores higher on coding benchmarks: 42.0 versus 34.0 in the Noometry coding category.
Which has the bigger context window?
Mistral Small does, with 262K tokens against 164K.
How many benchmarks do DeepSeek-V3.1-Terminus and Mistral Small share?
16 benchmarks have published results for both models. DeepSeek-V3.1-Terminus has 16 scored results on Noometry and Mistral Small has 39.