Model comparison

DeepSeek-V3.1 vs o4-mini

DeepSeek-V3.1 is the stronger model overall, scoring 42.8 to 41.6 on the Noometry Index.

Last verified October 12, 2026. 26 shared benchmarks.

DeepSeek-V3.1

DeepSeek

42.8

Rank #108 Confirmed

o4-mini OpenAI

41.6

Rank #132 Confirmed

Summary

They share 26 benchmarks with published results for both. DeepSeek-V3.1 scores higher in 4 categories and o4-mini in 4 categories; 6 gaps are clear of the uncertainty.
The widest gap is in long context, where o4-mini leads 45.5 to 36.3.
The biggest single-benchmark swing is Fiction.LiveBench: 52.8% for DeepSeek-V3.1 and 77.8% for o4-mini.
DeepSeek-V3.1 is cheaper at $0.25 / $0.95 per million input/output tokens, against $1.10 / $4.40 for o4-mini.
o4-mini accepts more context: 200K tokens versus 164K.
DeepSeek-V3.1 has downloadable open weights; the other is API-only.

Side by side

DeepSeek-V3.1 and o4-mini specifications
	DeepSeek-V3.1	o4-mini
Provider	DeepSeek	OpenAI
Noometry Index	42.8	41.6
Released	2025-08-21	2025-04-16
Weights	Open	Proprietary
Context window	164K	200K
Max output	8K	100K
Input $ / M tokens	$0.25	$1.10
Output $ / M tokens	$0.95	$4.40
Results tracked	27	60

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Category by category

Coding Too close to call

DeepSeek-V3.1: 40.3 (#144), o4-mini: 40.9 (#127)

Coding benchmarks
Benchmark	DeepSeek-V3.1	o4-mini
WeirdML	38.4%	52.6%
LMArena Coding	1417	1368
SWE-bench Verified (bash only)	—	45%
Aider Polyglot	—	72%
GSO	—	3.6%
CadEval	—	62%
ALE-Bench	—	826.17
AlgoTune	—	1.72

Agentic & Tool Use Not comparable

DeepSeek-V3.1: —, o4-mini: 32.6 (#61)

Agentic & Tool Use benchmarks
Benchmark	DeepSeek-V3.1	o4-mini
Berkeley Function Calling Leaderboard	—	53.2%
GDPval	—	25.3%
METR Time Horizons	—	63.9%

Reasoning DeepSeek-V3.1 leads

DeepSeek-V3.1: 27.9 (#110), o4-mini: 24.6 (#162)

Reasoning benchmarks
Benchmark	DeepSeek-V3.1	o4-mini
SimpleBench	40%	38.7%
Kagi LLM Benchmark	53.2%	67.6%
LMArena Hard Prompts	1417	1351
DTBench	82.7%	77.6%
LMCA	24.3%	26.5%
Epoch Capabilities Index	139.92	145.64
ForecastBench	58	61.8
ARC-AGI-2	—	6.1%
ARC-AGI-1	—	58.7%
CritPt	—	0.6%
Chess Puzzles	—	26%
EnigmaEval	—	9.2%
Mystery Game Puzzles	—	5%

Math o4-mini leads

DeepSeek-V3.1: 38.9 (#122), o4-mini: 40.8 (#89)

Math benchmarks
Benchmark	DeepSeek-V3.1	o4-mini
LMArena Math	1420	1389
FrontierMath (Tiers 1-3)	—	36.1%
FrontierMath Tier 4	—	4.9%
OTIS Mock AIME 2024-2025	—	81.7%
Omni-MATH	—	72%
MATH Level 5	—	97.8%
FrontierMath (Feb 2025 set)	—	24.8%
FrontierMath Tier 4 (v1)	—	6.3%

Knowledge Too close to call

DeepSeek-V3.1: 43.7 (#90), o4-mini: 43.6 (#91)

Knowledge benchmarks
Benchmark	DeepSeek-V3.1	o4-mini
Vectara Hallucination Rate	5.5%	18.6%
LMArena Expert	1405	1343
GPQA Diamond	—	79.6%
Humanity's Last Exam	—	18.1%
SimpleQA Verified	—	19.6%
MMLU-Pro	—	82%
Confabulations	—	15.8%
GPQA (HELM)	—	73.5%

Multimodal Not comparable

DeepSeek-V3.1: —, o4-mini: 40.2 (#49)

Multimodal benchmarks
Benchmark	DeepSeek-V3.1	o4-mini
LMArena Vision	—	1194
GeoBench	—	64%
VPCT	—	57.5%

Multilingual DeepSeek-V3.1 leads

DeepSeek-V3.1: 51.6 (#106), o4-mini: 47.0 (#154)

Multilingual benchmarks
Benchmark	DeepSeek-V3.1	o4-mini
LMArena Non-English	1400	1337
LMArena Chinese	1469	1354
LMArena French	1447	1364
LMArena German	1411	1336
LMArena Japanese	1378	1308
LMArena Korean	1337	1312
LMArena Russian	1405	1334
LMArena Spanish	1431	1347

Instruction Following o4-mini leads

DeepSeek-V3.1: 73.9 (#110), o4-mini: 75.2 (#68)

Instruction Following benchmarks
Benchmark	DeepSeek-V3.1	o4-mini
LMArena Instruction Following	1400	1321
IFEval	—	92.8%

Long Context o4-mini leads

DeepSeek-V3.1: 36.3 (#232), o4-mini: 45.5 (#33)

Long Context benchmarks
Benchmark	DeepSeek-V3.1	o4-mini
Fiction.LiveBench	52.8%	77.8%
LMArena Longer Query	1422	1315

Writing & Preference DeepSeek-V3.1 leads

DeepSeek-V3.1: 60.3 (#98), o4-mini: 54.0 (#152)

Writing & Preference benchmarks
Benchmark	DeepSeek-V3.1	o4-mini
LMArena Text	1420	1353
LMArena Creative Writing	1401	1294
LMArena Multi-Turn	1408	1350
Short-Story Creative Writing	—	75%
EQ-Bench Creative Writing	1436	—
WildBench	—	85.4%

Frequently asked questions

Is DeepSeek-V3.1 better than o4-mini?

DeepSeek-V3.1 is the stronger model overall, scoring 42.8 to 41.6 on the Noometry Index.

Which is cheaper, DeepSeek-V3.1 or o4-mini?

DeepSeek-V3.1 is cheaper. It lists at $0.25 per million input tokens and $0.95 per million output tokens; o4-mini lists at $1.10 and $4.40.

Is DeepSeek-V3.1 or o4-mini better for coding?

They score almost the same on coding (40.3 vs 40.9); test both on your own repository before choosing.

Which has the bigger context window?

o4-mini does, with 200K tokens against 164K.

How many benchmarks do DeepSeek-V3.1 and o4-mini share?

26 benchmarks have published results for both models. DeepSeek-V3.1 has 27 scored results on Noometry and o4-mini has 60.