Model comparison

DeepSeek-V3.1 vs GPT-5.5 Pro

GPT-5.5 Pro is the stronger model overall, scoring 64.3 to 42.8 on the Noometry Index. DeepSeek-V3.1 costs 159× less per token, which makes it the better buy when GPT-5.5 Pro's lead doesn't matter for your workload.

Last verified . 4 shared benchmarks.

DeepSeek-V3.1 DeepSeek

42.8

Rank #108 Confirmed

GPT-5.5 Pro OpenAI

64.3

Rank #8 Confirmed

Summary

  • They share 4 benchmarks with published results for both. DeepSeek-V3.1 scores higher in 0 categories and GPT-5.5 Pro in 3 categories; 3 gaps are clear of the uncertainty.
  • The widest gap is in reasoning, where GPT-5.5 Pro leads 73.3 to 27.9.
  • The biggest single-benchmark swing is SimpleBench: 40% for DeepSeek-V3.1 and 76.9% for GPT-5.5 Pro.
  • DeepSeek-V3.1 is cheaper at $0.25 / $0.95 per million input/output tokens, against $30 / $180 for GPT-5.5 Pro.
  • GPT-5.5 Pro accepts more context: 1.05M tokens versus 164K.
  • DeepSeek-V3.1 has downloadable open weights; the other is API-only.

Side by side

DeepSeek-V3.1 and GPT-5.5 Pro specifications
DeepSeek-V3.1GPT-5.5 Pro
ProviderDeepSeekOpenAI
Noometry Index42.864.3
Released2025-08-212026-04-23
WeightsOpenProprietary
Context window164K1.05M
Max output8K128K
Input $ / M tokens$0.25$30
Output $ / M tokens$0.95$180
Results tracked2714

Sponsored placements are available on pages like this one. Advertise on Noometry

Category by category

Coding Not comparable

DeepSeek-V3.1: 40.3 (#144), GPT-5.5 Pro: —

Coding benchmarks
BenchmarkDeepSeek-V3.1GPT-5.5 Pro
WeirdML38.4%—
LMArena Coding1417—

Reasoning GPT-5.5 Pro leads

DeepSeek-V3.1: 27.9 (#110), GPT-5.5 Pro: 73.3 (#10)

Reasoning benchmarks
BenchmarkDeepSeek-V3.1GPT-5.5 Pro
SimpleBench40%76.9%
DTBench82.7%96%
LMCA24.3%53.9%
Epoch Capabilities Index139.92162.07
ARC-AGI-2—84.6%
Kagi LLM Benchmark53.2%—
ARC-AGI-1—96.5%
CritPt—30.6%
Chess Puzzles—64%
LMArena Hard Prompts1417—
ForecastBench58—

Math GPT-5.5 Pro leads

DeepSeek-V3.1: 38.9 (#122), GPT-5.5 Pro: 84.0 (#10)

Math benchmarks
BenchmarkDeepSeek-V3.1GPT-5.5 Pro
FrontierMath (Tiers 1-3)—87.7%
FrontierMath Tier 4—78%
OTIS Mock AIME 2024-2025—100%
LMArena Math1420—
FrontierMath (Feb 2025 set)—52.4%
FrontierMath Tier 4 (v1)—39.6%

Knowledge GPT-5.5 Pro leads

DeepSeek-V3.1: 43.7 (#90), GPT-5.5 Pro: 64.1 (#19)

Knowledge benchmarks
BenchmarkDeepSeek-V3.1GPT-5.5 Pro
GPQA Diamond—93.9%
Vectara Hallucination Rate5.5%—
LMArena Expert1405—

Multilingual Not comparable

DeepSeek-V3.1: 51.6 (#106), GPT-5.5 Pro: —

Multilingual benchmarks
BenchmarkDeepSeek-V3.1GPT-5.5 Pro
LMArena Non-English1400—
LMArena Chinese1469—
LMArena French1447—
LMArena German1411—
LMArena Japanese1378—
LMArena Korean1337—
LMArena Russian1405—
LMArena Spanish1431—

Instruction Following Not comparable

DeepSeek-V3.1: 73.9 (#110), GPT-5.5 Pro: —

Instruction Following benchmarks
BenchmarkDeepSeek-V3.1GPT-5.5 Pro
LMArena Instruction Following1400—

Long Context Not comparable

DeepSeek-V3.1: 36.3 (#232), GPT-5.5 Pro: —

Long Context benchmarks
BenchmarkDeepSeek-V3.1GPT-5.5 Pro
Fiction.LiveBench52.8%—
LMArena Longer Query1422—

Writing & Preference Not comparable

DeepSeek-V3.1: 60.3 (#98), GPT-5.5 Pro: —

Writing & Preference benchmarks
BenchmarkDeepSeek-V3.1GPT-5.5 Pro
LMArena Text1420—
LMArena Creative Writing1401—
EQ-Bench Creative Writing1436—
LMArena Multi-Turn1408—

Frequently asked questions

Is DeepSeek-V3.1 better than GPT-5.5 Pro?

GPT-5.5 Pro is the stronger model overall, scoring 64.3 to 42.8 on the Noometry Index. DeepSeek-V3.1 costs 159× less per token, which makes it the better buy when GPT-5.5 Pro's lead doesn't matter for your workload.

Which is cheaper, DeepSeek-V3.1 or GPT-5.5 Pro?

DeepSeek-V3.1 is cheaper. It lists at $0.25 per million input tokens and $0.95 per million output tokens; GPT-5.5 Pro lists at $30 and $180.

Which has the bigger context window?

GPT-5.5 Pro does, with 1.05M tokens against 164K.

How many benchmarks do DeepSeek-V3.1 and GPT-5.5 Pro share?

4 benchmarks have published results for both models. DeepSeek-V3.1 has 27 scored results on Noometry and GPT-5.5 Pro has 14.

Related comparisons

Go deeper