Model comparison

DeepSeek-V3.1 vs GPT-5.4 mini

GPT-5.4 mini is the stronger model overall, scoring 45.0 to 42.8 on the Noometry Index. DeepSeek-V3.1 costs 4.0× less per token, which makes it the better buy when GPT-5.4 mini's lead doesn't matter for your workload.

Last verified October 11, 2026. 25 shared benchmarks.

DeepSeek-V3.1

DeepSeek

42.8

Rank #108 Confirmed

GPT-5.4 mini OpenAI

45.0

Rank #76 Confirmed

Summary

They share 25 benchmarks with published results for both. DeepSeek-V3.1 scores higher in 0 categories and GPT-5.4 mini in 8 categories; 6 gaps are clear of the uncertainty.
The widest gap is in knowledge, where GPT-5.4 mini leads 51.5 to 43.7.
The biggest single-benchmark swing is WeirdML: 38.4% for DeepSeek-V3.1 and 60.3% for GPT-5.4 mini.
DeepSeek-V3.1 is cheaper at $0.25 / $0.95 per million input/output tokens, against $0.75 / $4.50 for GPT-5.4 mini.
GPT-5.4 mini accepts more context: 400K tokens versus 164K.
DeepSeek-V3.1 has downloadable open weights; the other is API-only.

Side by side

DeepSeek-V3.1 and GPT-5.4 mini specifications
	DeepSeek-V3.1	GPT-5.4 mini
Provider	DeepSeek	OpenAI
Noometry Index	42.8	45.0
Released	2025-08-21	2026-03-17
Weights	Open	Proprietary
Context window	164K	400K
Max output	8K	128K
Input $ / M tokens	$0.25	$0.75
Output $ / M tokens	$0.95	$4.50
Results tracked	27	46

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Category by category

Coding GPT-5.4 mini leads

DeepSeek-V3.1: 40.3 (#144), GPT-5.4 mini: 45.2 (#72)

Coding benchmarks
Benchmark	DeepSeek-V3.1	GPT-5.4 mini
WeirdML	38.4%	60.3%
LMArena Coding	1417	1438
FrontierCode	—	27%
LMArena WebDev	—	1397
SciCode	—	49.9%
ALE-Bench	—	1,189

Agentic & Tool Use Not comparable

DeepSeek-V3.1: —, GPT-5.4 mini: 29.9 (#81)

Agentic & Tool Use benchmarks
Benchmark	DeepSeek-V3.1	GPT-5.4 mini
DeepResearch Bench	—	36.3%

Reasoning GPT-5.4 mini leads

DeepSeek-V3.1: 27.9 (#110), GPT-5.4 mini: 30.4 (#85)

Reasoning benchmarks
Benchmark	DeepSeek-V3.1	GPT-5.4 mini
Kagi LLM Benchmark	53.2%	37.9%
LMArena Hard Prompts	1417	1424
DTBench	82.7%	80%
LMCA	24.3%	40.8%
Epoch Capabilities Index	139.92	148.84
ForecastBench	58	57
ARC-AGI-2	—	18.9%
SimpleBench	40%	—
NYT Connections (extended)	—	61.8%
ARC-AGI-1	—	63.7%
CritPt	—	10%
Chess Puzzles	—	24%
Thematic Generalization	—	61.7%
Mystery Game Puzzles	—	11%

Math GPT-5.4 mini leads

DeepSeek-V3.1: 38.9 (#122), GPT-5.4 mini: 45.5 (#75)

Math benchmarks
Benchmark	DeepSeek-V3.1	GPT-5.4 mini
LMArena Math	1420	1419
FrontierMath (Tiers 1-3)	—	51.2%
FrontierMath Tier 4	—	9.8%
OTIS Mock AIME 2024-2025	—	88.9%
ProofBench	—	21%
FrontierMath (Feb 2025 set)	—	28.3%
FrontierMath Tier 4 (v1)	—	2.1%

Knowledge GPT-5.4 mini leads

DeepSeek-V3.1: 43.7 (#90), GPT-5.4 mini: 51.5 (#67)

Knowledge benchmarks
Benchmark	DeepSeek-V3.1	GPT-5.4 mini
Vectara Hallucination Rate	5.5%	5.5%
LMArena Expert	1405	1435
GPQA Diamond	—	86.9%
SimpleQA Verified	—	29.4%

Multimodal Not comparable

DeepSeek-V3.1: —, GPT-5.4 mini: 39.7 (#56)

Multimodal benchmarks
Benchmark	DeepSeek-V3.1	GPT-5.4 mini
LMArena Vision	—	1245

Multilingual Too close to call

DeepSeek-V3.1: 51.6 (#106), GPT-5.4 mini: 51.9 (#96)

Multilingual benchmarks
Benchmark	DeepSeek-V3.1	GPT-5.4 mini
LMArena Non-English	1400	1405
LMArena Chinese	1469	1446
LMArena French	1447	1440
LMArena German	1411	1409
LMArena Japanese	1378	1374
LMArena Korean	1337	1368
LMArena Russian	1405	1417
LMArena Spanish	1431	1405

Instruction Following Too close to call

DeepSeek-V3.1: 73.9 (#110), GPT-5.4 mini: 74.1 (#102)

Instruction Following benchmarks
Benchmark	DeepSeek-V3.1	GPT-5.4 mini
LMArena Instruction Following	1400	1405

Long Context GPT-5.4 mini leads

DeepSeek-V3.1: 36.3 (#232), GPT-5.4 mini: 43.0 (#112)

Long Context benchmarks
Benchmark	DeepSeek-V3.1	GPT-5.4 mini
LMArena Longer Query	1422	1407
Fiction.LiveBench	52.8%	—

Writing & Preference GPT-5.4 mini leads

DeepSeek-V3.1: 60.3 (#98), GPT-5.4 mini: 64.0 (#58)

Writing & Preference benchmarks
Benchmark	DeepSeek-V3.1	GPT-5.4 mini
LMArena Text	1420	1412
LMArena Creative Writing	1401	1370
EQ-Bench Creative Writing	1436	1665
LMArena Multi-Turn	1408	1429

Frequently asked questions

Is DeepSeek-V3.1 better than GPT-5.4 mini?

Which is cheaper, DeepSeek-V3.1 or GPT-5.4 mini?

DeepSeek-V3.1 is cheaper. It lists at $0.25 per million input tokens and $0.95 per million output tokens; GPT-5.4 mini lists at $0.75 and $4.50.

Is DeepSeek-V3.1 or GPT-5.4 mini better for coding?

GPT-5.4 mini scores higher on coding benchmarks: 45.2 versus 40.3 in the Noometry coding category.

Which has the bigger context window?

GPT-5.4 mini does, with 400K tokens against 164K.

How many benchmarks do DeepSeek-V3.1 and GPT-5.4 mini share?

25 benchmarks have published results for both models. DeepSeek-V3.1 has 27 scored results on Noometry and GPT-5.4 mini has 46.