Model comparison

DeepSeek-V3.1-Terminus vs Mistral Large

DeepSeek-V3.1-Terminus is the stronger model overall, scoring 42.6 to 31.6 on the Noometry Index.

Last verified October 10, 2026. 15 shared benchmarks.

DeepSeek-V3.1-Terminus

DeepSeek

42.6

Rank #96 Confirmed

Mistral Large

Mistral AI

31.6

Rank #258 Confirmed

Summary

They share 15 benchmarks with published results for both. DeepSeek-V3.1-Terminus scores higher in 7 categories and Mistral Large 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 40.9.
The biggest single-benchmark swing is DTBench: 81.3% for DeepSeek-V3.1-Terminus and 65.1% for Mistral Large.
DeepSeek-V3.1-Terminus is cheaper at $0.30 / $1 per million input/output tokens, against $2 / $6 for Mistral Large.
DeepSeek-V3.1-Terminus accepts more context: 164K tokens versus 131K.

Side by side

DeepSeek-V3.1-Terminus and Mistral Large specifications
	DeepSeek-V3.1-Terminus	Mistral Large
Provider	DeepSeek	Mistral AI
Noometry Index	42.6	31.6
Released	2025-09-22	2024-02-26
Weights	Open	Open
Context window	164K	131K
Max output	66K	16K
Input $ / M tokens	$0.30	$2
Output $ / M tokens	$1	$6
Results tracked	16	51

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Category by category

Coding DeepSeek-V3.1-Terminus leads

DeepSeek-V3.1-Terminus: 41.5 (#114), Mistral Large: 33.8 (#240)

Coding benchmarks
Benchmark	DeepSeek-V3.1-Terminus	Mistral Large
SciCode	40.6%	36.2%
LMArena Coding	1426	1277
ALE-Bench	745.17	264.7
BigCodeBench Instruct	—	30%
LiveBench Coding	—	47.1%
BigCodeBench Complete	—	38.3%
HumanEval+	—	62.2%
MBPP+	—	59.5%

Agentic & Tool Use Not comparable

DeepSeek-V3.1-Terminus: —, Mistral Large: 28.4 (#83)

Agentic & Tool Use benchmarks
Benchmark	DeepSeek-V3.1-Terminus	Mistral Large
Berkeley Function Calling Leaderboard	—	38.4%

Reasoning DeepSeek-V3.1-Terminus leads

DeepSeek-V3.1-Terminus: 25.7 (#126), Mistral Large: 15.4 (#305)

Reasoning benchmarks
Benchmark	DeepSeek-V3.1-Terminus	Mistral Large
CritPt	1.7%	0%
LMArena Hard Prompts	1427	1257
DTBench	81.3%	65.1%
LMCA	28.6%	16.7%
SimpleBench	—	22.5%
Kagi LLM Benchmark	57.4%	—
LiveBench Reasoning	—	43.5%
LiveBench Data Analysis	—	50.1%
Epoch Capabilities Index	—	128.52
ForecastBench	—	57.1
LiveBench	—	48.4%

Math DeepSeek-V3.1-Terminus leads

DeepSeek-V3.1-Terminus: 35.7 (#138), Mistral Large: 17.1 (#285)

Math benchmarks
Benchmark	DeepSeek-V3.1-Terminus	Mistral Large
LMArena Math	1402	1262
OTIS Mock AIME 2024-2025	—	8.5%
Omni-MATH	—	28.1%
LiveBench Math	—	42.5%
MATH Level 5	—	50.3%
FrontierMath (Feb 2025 set)	—	0.3%

Knowledge Not comparable

DeepSeek-V3.1-Terminus: —, Mistral Large: 30.0 (#224)

Knowledge benchmarks
Benchmark	DeepSeek-V3.1-Terminus	Mistral Large
GPQA Diamond	—	51.3%
MMLU-Pro	—	59.9%
Confabulations	—	21.4%
Vectara Hallucination Rate	—	4.5%
GPQA (HELM)	—	43.5%
LMArena Expert	—	1232
MMLU	—	80%

Multilingual DeepSeek-V3.1-Terminus leads

DeepSeek-V3.1-Terminus: 52.3 (#87), Mistral Large: 40.1 (#214)

Multilingual benchmarks
Benchmark	DeepSeek-V3.1-Terminus	Mistral Large
LMArena Non-English	1407	1237
LMArena Russian	1434	1257
LMArena Chinese	—	1240
LMArena French	—	1324
LMArena German	—	1254
LMArena Japanese	—	1187
LMArena Korean	—	1202
LMArena Spanish	—	1268

Instruction Following DeepSeek-V3.1-Terminus leads

DeepSeek-V3.1-Terminus: 74.4 (#96), Mistral Large: 68.1 (#186)

Instruction Following benchmarks
Benchmark	DeepSeek-V3.1-Terminus	Mistral Large
LMArena Instruction Following	1406	1249
LiveBench Instruction Following	—	67.9%
IFEval	—	87.7%

Long Context DeepSeek-V3.1-Terminus leads

DeepSeek-V3.1-Terminus: 43.5 (#88), Mistral Large: 38.3 (#194)

Long Context benchmarks
Benchmark	DeepSeek-V3.1-Terminus	Mistral Large
LMArena Longer Query	1426	1262

Writing & Preference DeepSeek-V3.1-Terminus leads

DeepSeek-V3.1-Terminus: 61.3 (#87), Mistral Large: 40.9 (#237)

Writing & Preference benchmarks
Benchmark	DeepSeek-V3.1-Terminus	Mistral Large
LMArena Text	1420	1266
LMArena Creative Writing	1404	1243
LMArena Multi-Turn	1411	1260
Short-Story Creative Writing	—	69%
EQ-Bench Creative Writing	—	985
WildBench	—	80.1%
LiveBench Language	—	39.4%

Frequently asked questions

Is DeepSeek-V3.1-Terminus better than Mistral Large?

DeepSeek-V3.1-Terminus is the stronger model overall, scoring 42.6 to 31.6 on the Noometry Index.

Which is cheaper, DeepSeek-V3.1-Terminus or Mistral Large?

DeepSeek-V3.1-Terminus is cheaper. It lists at $0.30 per million input tokens and $1 per million output tokens; Mistral Large lists at $2 and $6.

Is DeepSeek-V3.1-Terminus or Mistral Large better for coding?

DeepSeek-V3.1-Terminus scores higher on coding benchmarks: 41.5 versus 33.8 in the Noometry coding category.

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 Large share?

15 benchmarks have published results for both models. DeepSeek-V3.1-Terminus has 16 scored results on Noometry and Mistral Large has 51.