Model comparison

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.

Last verified October 10, 2026. 11 shared benchmarks.

DeepSeek-V3.1-Terminus

DeepSeek

43.1

Rank #97 Confirmed

Mistral Medium 3.5

Mistral AI

40.2

Rank #152 Confirmed

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.

Side by side

DeepSeek-V3.1-Terminus and Mistral Medium 3.5 specifications
	DeepSeek-V3.1-Terminus	Mistral Medium 3.5
Provider	DeepSeek	Mistral AI
Noometry Index	43.1	40.2
Released	2025-09-22	—
Weights	Open	Open
Context window	164K	262K
Max output	147K	210K
Input $ / M tokens	$0.27	$1.50
Output $ / M tokens	$1	$7.50
Results tracked	16	22

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Category by category

Coding DeepSeek-V3.1-Terminus leads

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

Coding benchmarks
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 leads

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

Reasoning benchmarks
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 Too close to call

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

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

Knowledge Not comparable

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

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

Multimodal Not comparable

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

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

Multilingual Too close to call

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

Multilingual benchmarks
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 Too close to call

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

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

Long Context Too close to call

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

Long Context benchmarks
Benchmark	DeepSeek-V3.1-Terminus	Mistral Medium 3.5
LMArena Longer Query	1421	1415

Writing & Preference DeepSeek-V3.1-Terminus leads

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

Writing & Preference benchmarks
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

Frequently asked questions

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.