# DeepSeek-V3.1-Terminus vs Mistral Medium 3.5

> DeepSeek-V3.1-Terminus is the stronger model overall, scoring 43.1 to 40.2 on the Noometry Index.

- Canonical page: https://noometry.com/compare/deepseek-v3-1-terminus-vs-mistral-medium-3-5
- Last updated: 2026-10-10
- Shared benchmarks: 11

## Summary

- They share 11 benchmarks with published results for both. DeepSeek-V3.1-Terminus scores higher in 5 categories and Mistral Medium 3.5 in 2 categories; 3 gaps are clear of the uncertainty.
- The widest gap is in reasoning, where DeepSeek-V3.1-Terminus leads 26.4 to 17.3.
- The biggest single-benchmark swing is Kagi LLM Benchmark: 57.4% for DeepSeek-V3.1-Terminus and 41.4% for Mistral Medium 3.5.
- DeepSeek-V3.1-Terminus is cheaper at $0.27 / $1 per million input/output tokens, against $1.50 / $7.50 for Mistral Medium 3.5.
- Mistral Medium 3.5 accepts more context: 262K tokens versus 164K.

## Snapshot

| | DeepSeek-V3.1-Terminus | Mistral Medium 3.5 |
|---|---|---|
| Provider | DeepSeek | Mistral AI |
| Noometry Index | 43.1 | 40.2 |
| Rank | 97 | 152 |
| Context | 164K | 262K |
| Input $/M | $0.27 | $1.50 |
| Output $/M | $1 | $7.50 |
| Weights | Open | Open |

## Coding

- DeepSeek-V3.1-Terminus: 42.0 (#113)
- Mistral Medium 3.5: 36.0 (#213)

| Benchmark | DeepSeek-V3.1-Terminus | Mistral Medium 3.5 |
|---|---|---|
| LMArena Coding | 1426 | 1461 |
| LMArena WebDev | — | 1264 |
| SciCode | 40.6% | — |
| ALE-Bench | 745.17 | — |

## Reasoning

- DeepSeek-V3.1-Terminus: 26.4 (#133)
- Mistral Medium 3.5: 17.3 (#295)

| Benchmark | DeepSeek-V3.1-Terminus | Mistral Medium 3.5 |
|---|---|---|
| Kagi LLM Benchmark | 57.4% | 41.4% |
| LMArena Hard Prompts | 1426 | 1436 |
| NYT Connections (extended) | — | 12.9% |
| CritPt | 1.7% | — |
| DTBench | 81.3% | — |
| LMCA | 28.6% | — |
| Epoch Capabilities Index | — | 141.35 |

## Math

- DeepSeek-V3.1-Terminus: 38.5 (#137)
- Mistral Medium 3.5: 39.1 (#113)

| Benchmark | DeepSeek-V3.1-Terminus | Mistral Medium 3.5 |
|---|---|---|
| LMArena Math | 1402 | 1431 |

## Knowledge

- DeepSeek-V3.1-Terminus: —
- Mistral Medium 3.5: 40.0 (#126)

| Benchmark | DeepSeek-V3.1-Terminus | Mistral Medium 3.5 |
|---|---|---|
| LMArena Expert | — | 1432 |

## Multimodal

- DeepSeek-V3.1-Terminus: —
- Mistral Medium 3.5: 38.3 (#65)

| Benchmark | DeepSeek-V3.1-Terminus | Mistral Medium 3.5 |
|---|---|---|
| LMArena Vision | — | 1223 |

## Multilingual

- DeepSeek-V3.1-Terminus: 52.1 (#92)
- Mistral Medium 3.5: 51.9 (#100)

| Benchmark | DeepSeek-V3.1-Terminus | Mistral Medium 3.5 |
|---|---|---|
| LMArena Non-English | 1407 | 1404 |
| LMArena Russian | 1436 | 1395 |
| LMArena Chinese | — | 1442 |
| LMArena French | — | 1448 |
| LMArena German | — | 1451 |
| LMArena Korean | — | 1385 |
| LMArena Spanish | — | 1409 |

## Instruction Following

- DeepSeek-V3.1-Terminus: 74.0 (#106)
- Mistral Medium 3.5: 74.6 (#90)

| Benchmark | DeepSeek-V3.1-Terminus | Mistral Medium 3.5 |
|---|---|---|
| LMArena Instruction Following | 1404 | 1415 |

## Long Context

- DeepSeek-V3.1-Terminus: 43.4 (#97)
- Mistral Medium 3.5: 43.2 (#103)

| Benchmark | DeepSeek-V3.1-Terminus | Mistral Medium 3.5 |
|---|---|---|
| LMArena Longer Query | 1421 | 1415 |

## Writing & Preference

- DeepSeek-V3.1-Terminus: 61.0 (#92)
- Mistral Medium 3.5: 58.5 (#117)

| Benchmark | DeepSeek-V3.1-Terminus | Mistral Medium 3.5 |
|---|---|---|
| LMArena Text | 1419 | 1421 |
| LMArena Creative Writing | 1403 | 1374 |
| LMArena Multi-Turn | 1411 | 1423 |
| EQ-Bench 4 | — | 993 |

## FAQ

### Is DeepSeek-V3.1-Terminus better than Mistral Medium 3.5?

DeepSeek-V3.1-Terminus is the stronger model overall, scoring 43.1 to 40.2 on the Noometry Index.

### Which is cheaper, DeepSeek-V3.1-Terminus or Mistral Medium 3.5?

DeepSeek-V3.1-Terminus is cheaper. It lists at $0.27 per million input tokens and $1 per million output tokens; Mistral Medium 3.5 lists at $1.50 and $7.50.

### Is DeepSeek-V3.1-Terminus or Mistral Medium 3.5 better for coding?

DeepSeek-V3.1-Terminus scores higher on coding benchmarks: 42.0 versus 36.0 in the Noometry coding category.

### Which has the bigger context window?

Mistral Medium 3.5 does, with 262K tokens against 164K.

### How many benchmarks do DeepSeek-V3.1-Terminus and Mistral Medium 3.5 share?

11 benchmarks have published results for both models. DeepSeek-V3.1-Terminus has 16 scored results on Noometry and Mistral Medium 3.5 has 22.