Model comparison

DeepSeek-V3.1 vs GPT-5.1-Codex

DeepSeek-V3.1 is the stronger model overall, scoring 42.2 to 38.2 on the Noometry Index.

Last verified . 0 shared benchmarks.

DeepSeek-V3.1 DeepSeek

42.2

Rank #106 Confirmed

GPT-5.1-Codex OpenAI

38.2

Rank #178 Reported

Summary

  • The widest gap is in math, where DeepSeek-V3.1 leads 36.1 to 29.3.
  • DeepSeek-V3.1 is cheaper at $0.25 / $0.95 per million input/output tokens, against $1.25 / $10 for GPT-5.1-Codex.
  • GPT-5.1-Codex 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-5.1-Codex specifications
DeepSeek-V3.1GPT-5.1-Codex
ProviderDeepSeekOpenAI
Noometry Index42.238.2
Released2025-08-212025-11-12
WeightsOpenProprietary
Context window164K400K
Max output8K128K
Input $ / M tokens$0.25$1.25
Output $ / M tokens$0.95$10
Results tracked276

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Category by category

Coding GPT-5.1-Codex leads

DeepSeek-V3.1: 39.8 (#140), GPT-5.1-Codex: 41.7 (#107)

Coding benchmarks
BenchmarkDeepSeek-V3.1GPT-5.1-Codex
SWE-bench Verified (bash only)—66%
LMArena WebDev—1337
WeirdML38.4%—
LMArena Coding1417—
ALE-Bench—1,245

Agentic & Tool Use Not comparable

DeepSeek-V3.1: —, GPT-5.1-Codex: 37.8 (#32)

Agentic & Tool Use benchmarks
BenchmarkDeepSeek-V3.1GPT-5.1-Codex
Terminal-Bench—60.4%
METR Time Horizons—70.8%

Reasoning Not comparable

DeepSeek-V3.1: 27.3 (#109), GPT-5.1-Codex: —

Reasoning benchmarks
BenchmarkDeepSeek-V3.1GPT-5.1-Codex
SimpleBench40%—
Kagi LLM Benchmark53.2%—
LMArena Hard Prompts1417—
DTBench82.7%—
LMCA24.3%—
Epoch Capabilities Index139.92—
ForecastBench58—

Math DeepSeek-V3.1 leads

DeepSeek-V3.1: 36.1 (#125), GPT-5.1-Codex: 29.3 (#218)

Math benchmarks
BenchmarkDeepSeek-V3.1GPT-5.1-Codex
ProofBench—9%
LMArena Math1420—

Knowledge Not comparable

DeepSeek-V3.1: 43.0 (#86), GPT-5.1-Codex: —

Knowledge benchmarks
BenchmarkDeepSeek-V3.1GPT-5.1-Codex
Vectara Hallucination Rate5.5%—
LMArena Expert1403—

Multilingual Not comparable

DeepSeek-V3.1: 51.8 (#100), GPT-5.1-Codex: —

Multilingual benchmarks
BenchmarkDeepSeek-V3.1GPT-5.1-Codex
LMArena Non-English1400—
LMArena Chinese1470—
LMArena French1447—
LMArena German1412—
LMArena Japanese1374—
LMArena Korean1337—
LMArena Russian1405—
LMArena Spanish1429—

Instruction Following Not comparable

DeepSeek-V3.1: 74.1 (#105), GPT-5.1-Codex: —

Instruction Following benchmarks
BenchmarkDeepSeek-V3.1GPT-5.1-Codex
LMArena Instruction Following1400—

Long Context Not comparable

DeepSeek-V3.1: 36.3 (#227), GPT-5.1-Codex: —

Long Context benchmarks
BenchmarkDeepSeek-V3.1GPT-5.1-Codex
Fiction.LiveBench52.8%—
LMArena Longer Query1422—

Writing & Preference Not comparable

DeepSeek-V3.1: 60.5 (#93), GPT-5.1-Codex: —

Writing & Preference benchmarks
BenchmarkDeepSeek-V3.1GPT-5.1-Codex
LMArena Text1420—
LMArena Creative Writing1401—
EQ-Bench Creative Writing1436—
LMArena Multi-Turn1408—

Frequently asked questions

Is DeepSeek-V3.1 better than GPT-5.1-Codex?

DeepSeek-V3.1 is the stronger model overall, scoring 42.2 to 38.2 on the Noometry Index.

Which is cheaper, DeepSeek-V3.1 or GPT-5.1-Codex?

DeepSeek-V3.1 is cheaper. It lists at $0.25 per million input tokens and $0.95 per million output tokens; GPT-5.1-Codex lists at $1.25 and $10.

Is DeepSeek-V3.1 or GPT-5.1-Codex better for coding?

GPT-5.1-Codex scores higher on coding benchmarks: 41.7 versus 39.8 in the Noometry coding category.

Which has the bigger context window?

GPT-5.1-Codex does, with 400K tokens against 164K.

How many benchmarks do DeepSeek-V3.1 and GPT-5.1-Codex share?

0 benchmarks have published results for both models. DeepSeek-V3.1 has 27 scored results on Noometry and GPT-5.1-Codex has 6.

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