Model comparison
DeepSeek-V3.1-Terminus vs Mistral Medium 3.1
DeepSeek-V3.1-Terminus is the stronger model overall, scoring 42.6 to 31.5 on the Noometry Index.
Last verified . 0 shared benchmarks.
DeepSeek
Mistral AISummary
- The widest gap is in reasoning, where DeepSeek-V3.1-Terminus leads 25.7 to 10.1.
- DeepSeek-V3.1-Terminus is cheaper at $0.30 / $1 per million input/output tokens, against $0.40 / $2 for Mistral Medium 3.1.
- DeepSeek-V3.1-Terminus accepts more context: 164K tokens versus 131K.
- DeepSeek-V3.1-Terminus has downloadable open weights; the other is API-only.
Side by side
| DeepSeek-V3.1-Terminus | Mistral Medium 3.1 | |
|---|---|---|
| Provider | DeepSeek | Mistral AI |
| Noometry Index | 42.6 | 31.5 |
| Released | 2025-09-22 | — |
| Weights | Open | Proprietary |
| Context window | 164K | 131K |
| Max output | 66K | 105K |
| Input $ / M tokens | $0.30 | $0.40 |
| Output $ / M tokens | $1 | $2 |
| Results tracked | 16 | 3 |
Sponsored placements are available on pages like this one. Advertise on Noometry
Category by category
Coding Not comparable
DeepSeek-V3.1-Terminus: 41.5 (#114), Mistral Medium 3.1: —
| Benchmark | DeepSeek-V3.1-Terminus | Mistral Medium 3.1 |
|---|---|---|
| SciCode | 40.6% | — |
| LMArena Coding | 1426 | — |
| ALE-Bench | 745.17 | — |
Reasoning DeepSeek-V3.1-Terminus leads
DeepSeek-V3.1-Terminus: 25.7 (#126), Mistral Medium 3.1: 10.1 (#336)
| Benchmark | DeepSeek-V3.1-Terminus | Mistral Medium 3.1 |
|---|---|---|
| Kagi LLM Benchmark | 57.4% | — |
| NYT Connections (extended) | — | 6.5% |
| CritPt | 1.7% | — |
| Thematic Generalization | — | 20.3% |
| LMArena Hard Prompts | 1427 | — |
| DTBench | 81.3% | — |
| LMCA | 28.6% | — |
Math Not comparable
DeepSeek-V3.1-Terminus: 35.7 (#138), Mistral Medium 3.1: —
| Benchmark | DeepSeek-V3.1-Terminus | Mistral Medium 3.1 |
|---|---|---|
| LMArena Math | 1402 | — |
Multilingual Not comparable
DeepSeek-V3.1-Terminus: 52.3 (#87), Mistral Medium 3.1: —
| Benchmark | DeepSeek-V3.1-Terminus | Mistral Medium 3.1 |
|---|---|---|
| LMArena Non-English | 1407 | — |
| LMArena Russian | 1434 | — |
Instruction Following Not comparable
DeepSeek-V3.1-Terminus: 74.4 (#96), Mistral Medium 3.1: —
| Benchmark | DeepSeek-V3.1-Terminus | Mistral Medium 3.1 |
|---|---|---|
| LMArena Instruction Following | 1406 | — |
Long Context Not comparable
DeepSeek-V3.1-Terminus: 43.5 (#88), Mistral Medium 3.1: —
| Benchmark | DeepSeek-V3.1-Terminus | Mistral Medium 3.1 |
|---|---|---|
| LMArena Longer Query | 1426 | — |
Writing & Preference DeepSeek-V3.1-Terminus leads
DeepSeek-V3.1-Terminus: 61.3 (#87), Mistral Medium 3.1: 55.6 (#140)
| Benchmark | DeepSeek-V3.1-Terminus | Mistral Medium 3.1 |
|---|---|---|
| LMArena Text | 1420 | — |
| LMArena Creative Writing | 1404 | — |
| EQ-Bench Creative Writing | — | 1476 |
| LMArena Multi-Turn | 1411 | — |
Frequently asked questions
Is DeepSeek-V3.1-Terminus better than Mistral Medium 3.1?
DeepSeek-V3.1-Terminus is the stronger model overall, scoring 42.6 to 31.5 on the Noometry Index.
Which is cheaper, DeepSeek-V3.1-Terminus or Mistral Medium 3.1?
DeepSeek-V3.1-Terminus is cheaper. It lists at $0.30 per million input tokens and $1 per million output tokens; Mistral Medium 3.1 lists at $0.40 and $2.
Which has the bigger context window?
DeepSeek-V3.1-Terminus does, with 164K tokens against 131K.
How many benchmarks do DeepSeek-V3.1-Terminus and Mistral Medium 3.1 share?
0 benchmarks have published results for both models. DeepSeek-V3.1-Terminus has 16 scored results on Noometry and Mistral Medium 3.1 has 3.