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DeepSeek V3.2 vs GPT-5.1-Codex-Mini

Updated October 21, 2026. 22 benchmarks have a result for both. Coding is ranked on the Vibe Coding Index; every other board is shown as published.

Replace DeepSeek V3.2 Replace GPT-5.1-Codex-Mini
DeepSeek V3.2DeepSeek
Coding
54.4
Overall
21.5
Output $/M
$0.42
19
GPT-5.1-Codex-MiniOpenAI
Coding
6.2
Overall
20.4
Output $/M
$2.00
3
vs boards won of 22 shared

Decision reading

Pick DeepSeek V3.2 for coding: it scores 54.4 on the Vibe Coding Index against 6.2 for GPT-5.1-Codex-Mini.

Pick GPT-5.1-Codex-Mini when the context window is larger, 400K against 164K tokens, or when what matters is Terminal-Bench or Design Arena: ASCII art, where it leads.

Model ADeepSeek V3.2DeepSeek54.4/1002 independent benchmarks$0.99 per solved taskModel BGPT-5.1-Codex-MiniOpenAI6.2/1001 independent benchmarkNo cost per solved task
Shared results
22
DeepSeek V3.2 only
53
GPT-5.1-Codex-Mini only
0
Like-for-like categories
8 of 9

Shared results can support a head-to-head reading. Results only one model has describe coverage, not superiority.

Which one for your work

Each card is decided by one number both models carry. Where only one has it, the card says so and makes no call.

At a glance

Coding index
DeepSeek V3.2 54.4 from 2 benchmarks, GPT-5.1-Codex-Mini 6.2 from 1 benchmark.
Widest category
Agentic work, 27.8 points apart on average over 1 shared benchmark.
Widest single gap
τ²-Bench Telecom: DeepSeek V3.2 90.6% against GPT-5.1-Codex-Mini 62.9%, 27.8 points apart on a 0 to 100 scale.
Output price
DeepSeek V3.2 $0.42 against GPT-5.1-Codex-Mini $2.00 per million output tokens, 4.8x apart.
Context window
DeepSeek V3.2 takes 164K tokens, GPT-5.1-Codex-Mini 400K.

Benchmark by benchmark

First the score: boards each model leads, per category, where both have a result. Then every board, a category to a fold; bars are each result on a 0 to 100 scale, so compare the two in a row, not one row with another.

Boards won, where both have a result
CategoryDeepSeek V3.2BarsGPT-5.1-Codex-MiniTies
Coding41
Intelligence10
Agentic work10
Reasoning20
Math20
Knowledge10
Web design71
General11
All shared boards193
CodingLike-for-likeFour of these boards feed the Vibe Coding Index41
Coding benchmarks for DeepSeek V3.2 and GPT-5.1-Codex-Mini
BenchmarkDeepSeek V3.2GPT-5.1-Codex-MiniLeader
SWE-bench Verified70.0%Not measuredOnly DeepSeek V3.2 measured
SWE-bench Multilingual59.0%Not measuredOnly DeepSeek V3.2 measured
LMArena WebDev13621244DeepSeek V3.2
AA Coding Index44.2Not measuredOnly DeepSeek V3.2 measured
LiveCodeBench (Vals AI)80.7%Not measuredOnly DeepSeek V3.2 measured
SWE-bench Verified (Vals AI)67.6%Not measuredOnly DeepSeek V3.2 measured
Vibe Code Bench (Vals AI)5.1%Not measuredOnly DeepSeek V3.2 measured
LiveCodeBench (Artificial Analysis run)86.2%83.6%DeepSeek V3.2
Terminal-Bench Hard (Artificial Analysis run)35.6%33.3%DeepSeek V3.2
Terminal-Bench39.6%61.6%GPT-5.1-Codex-Mini
LMArena Text: coding1453Not measuredOnly DeepSeek V3.2 measured
LMArena Text: software and IT1449Not measuredOnly DeepSeek V3.2 measured
LMArena WebDev: React1350Not measuredOnly DeepSeek V3.2 measured
LMArena WebDev: HTML13711253DeepSeek V3.2
Neither model has a result on the other 24 boards here
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index10
Intelligence benchmarks for DeepSeek V3.2 and GPT-5.1-Codex-Mini
BenchmarkDeepSeek V3.2GPT-5.1-Codex-MiniLeader
AA Intelligence Index21.520.4DeepSeek V3.2
Epoch Capabilities Index146.1Not measuredOnly DeepSeek V3.2 measured
Agentic workLike-for-likePublic boards, shown as published, kept out of the index10
Agentic work benchmarks for DeepSeek V3.2 and GPT-5.1-Codex-Mini
BenchmarkDeepSeek V3.2GPT-5.1-Codex-MiniLeader
τ²-Bench Telecom90.6%62.9%DeepSeek V3.2
APEX-Agents21.3%Not measuredOnly DeepSeek V3.2 measured
Vending-Bench 2$1,034Not measuredOnly DeepSeek V3.2 measured
Neither model has a result on the other 36 boards here
ReasoningLike-for-likePublic boards, shown as published, kept out of the index20
Reasoning benchmarks for DeepSeek V3.2 and GPT-5.1-Codex-Mini
BenchmarkDeepSeek V3.2GPT-5.1-Codex-MiniLeader
GPQA Diamond80.3%Not measuredOnly DeepSeek V3.2 measured
GPQA Diamond (Artificial Analysis run)84.0%81.3%DeepSeek V3.2
Humanity's Last Exam (Artificial Analysis run)24.6%18.5%DeepSeek V3.2
ARC-AGI57.0%Not measuredOnly DeepSeek V3.2 measured
ARC-AGI-24.0%Not measuredOnly DeepSeek V3.2 measured
LMArena Text: hard prompts1434Not measuredOnly DeepSeek V3.2 measured
LMArena Text: expert1436Not measuredOnly DeepSeek V3.2 measured
LMArena Text: hard prompts in English1446Not measuredOnly DeepSeek V3.2 measured
Neither model has a result on the other 13 boards here
MathLike-for-likePublic boards, shown as published, kept out of the index20
Math benchmarks for DeepSeek V3.2 and GPT-5.1-Codex-Mini
BenchmarkDeepSeek V3.2GPT-5.1-Codex-MiniLeader
AIME84.6%Not measuredOnly DeepSeek V3.2 measured
MGSM (Vals AI)86.0%Not measuredOnly DeepSeek V3.2 measured
AA Math Index92.091.7DeepSeek V3.2
AIME 2025 (Artificial Analysis run)92.0%91.7%DeepSeek V3.2
LMArena Text: math1435Not measuredOnly DeepSeek V3.2 measured
LMArena Text: mathematical work1440Not measuredOnly DeepSeek V3.2 measured
Neither model has a result on the other 7 boards here
KnowledgeLike-for-likePublic boards, shown as published, kept out of the index10
Knowledge benchmarks for DeepSeek V3.2 and GPT-5.1-Codex-Mini
BenchmarkDeepSeek V3.2GPT-5.1-Codex-MiniLeader
MMLU Pro84.9%Not measuredOnly DeepSeek V3.2 measured
LegalBench (Vals AI)76.1%Not measuredOnly DeepSeek V3.2 measured
CaseLaw (Vals AI)55.4%Not measuredOnly DeepSeek V3.2 measured
CorpFin (Vals AI)51.0%Not measuredOnly DeepSeek V3.2 measured
TaxEval (Vals AI)68.2%Not measuredOnly DeepSeek V3.2 measured
MedQA (Vals AI)93.9%Not measuredOnly DeepSeek V3.2 measured
MMLU Pro (Artificial Analysis run)86.2%82.0%DeepSeek V3.2
LMArena Text: science1446Not measuredOnly DeepSeek V3.2 measured
LMArena Text: medicine and healthcare1440Not measuredOnly DeepSeek V3.2 measured
LMArena Text: legal and government1425Not measuredOnly DeepSeek V3.2 measured
LMArena Text: business and finance1410Not measuredOnly DeepSeek V3.2 measured
Neither model has a result on the other 6 boards here
Web designLike-for-likePublic boards, shown as published, kept out of the index71
Web design benchmarks for DeepSeek V3.2 and GPT-5.1-Codex-Mini
BenchmarkDeepSeek V3.2GPT-5.1-Codex-MiniLeader
Design Arena: websites11751111DeepSeek V3.2
Design Arena: UI components11491081DeepSeek V3.2
Design Arena: game dev11321093DeepSeek V3.2
Design Arena: data viz11581097DeepSeek V3.2
Design Arena: 3D1133988DeepSeek V3.2
Design Arena: all code categories11641094DeepSeek V3.2
Design Arena: SVG1032977DeepSeek V3.2
Design Arena: ASCII art10821104GPT-5.1-Codex-Mini
Neither model has a result on the other 1 board here
GeneralLike-for-likePublic boards, shown as published, kept out of the index11
General benchmarks for DeepSeek V3.2 and GPT-5.1-Codex-Mini
BenchmarkDeepSeek V3.2GPT-5.1-Codex-MiniLeader
IFBench60.7%67.9%GPT-5.1-Codex-Mini
Long context reasoning (AA-LCR)73.3%66.7%DeepSeek V3.2
DTBench85.6%Not measuredOnly DeepSeek V3.2 measured
LMCA28.8%Not measuredOnly DeepSeek V3.2 measured
CL-bench12.4%Not measuredOnly DeepSeek V3.2 measured
CL-bench Life7.4%Not measuredOnly DeepSeek V3.2 measured
LMArena Text1425Not measuredOnly DeepSeek V3.2 measured
LMArena Text: instruction following1413Not measuredOnly DeepSeek V3.2 measured
LMArena Text: creative writing1400Not measuredOnly DeepSeek V3.2 measured
LMArena Text: English1439Not measuredOnly DeepSeek V3.2 measured
LMArena Text: non-English1409Not measuredOnly DeepSeek V3.2 measured
LMArena Text: Chinese1455Not measuredOnly DeepSeek V3.2 measured
LMArena Text: German1413Not measuredOnly DeepSeek V3.2 measured
LMArena Text: Japanese1374Not measuredOnly DeepSeek V3.2 measured
LMArena Text: Korean1370Not measuredOnly DeepSeek V3.2 measured
LMArena Text: French1429Not measuredOnly DeepSeek V3.2 measured
LMArena Text: Spanish1424Not measuredOnly DeepSeek V3.2 measured
LMArena Text: Russian1424Not measuredOnly DeepSeek V3.2 measured
LMArena Text: Polish1419Not measuredOnly DeepSeek V3.2 measured
LMArena Text: multi-turn1427Not measuredOnly DeepSeek V3.2 measured
LMArena Text: longer queries1428Not measuredOnly DeepSeek V3.2 measured
LMArena Text: writing and language1407Not measuredOnly DeepSeek V3.2 measured
LMArena Text: entertainment and media1395Not measuredOnly DeepSeek V3.2 measured
Neither model has a result on the other 23 boards here
Image generationNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
Image generation benchmarks for DeepSeek V3.2 and GPT-5.1-Codex-Mini
BenchmarkDeepSeek V3.2GPT-5.1-Codex-MiniLeader
Neither model has a result on 5 boards here

What each workload costs

Three fixed token mixes at each model's listed price, so per-token rates become a bill.

Chat turn

1K input + 500 output tokens

DeepSeek V3.2$0.0005Fits in one request
GPT-5.1-Codex-Mini$0.0013Fits in one request

DeepSeek V3.2 costs less

Repository review

50K input + 3K output tokens

DeepSeek V3.2$0.015Fits in one request
GPT-5.1-Codex-Mini$0.018Fits in one request

DeepSeek V3.2 costs less

Agent loop

200K input + 10K output tokens

DeepSeek V3.2$0.060Exceeds the context window
GPT-5.1-Codex-Mini$0.070Fits in one request

DeepSeek V3.2 costs less

Listed OpenRouter rates, without cache or batch discounts. A workload that does not fit a model's context window would need splitting.

Specification differences

The leading value in a row is marked; a row with a missing value names no leader. Our two rows are marked in red.

Specifications of DeepSeek V3.2 and GPT-5.1-Codex-Mini
SpecificationDeepSeek V3.2OpenAI GPT-5.1-Codex-Mini
MakerDeepSeekOpenAI
WeightsOpen weightsNo public weights listed
ReleasedDecember 1, 2025November 13, 2025
Context window164K400K
Input $/Mtok$0.28$0.25
Output $/Mtok$0.42$2.00
Coding index54.46.2
Independent measurements behind it21
Cost per solved task$0.99Not computable
SourceOpenRouter listingOpenRouter listing

Questions

Is DeepSeek V3.2 better than GPT-5.1-Codex-Mini for coding?

Pick DeepSeek V3.2 for coding: it scores 54.4 on the Vibe Coding Index against 6.2 for GPT-5.1-Codex-Mini. Pick GPT-5.1-Codex-Mini when the context window is larger, 400K against 164K tokens, or when what matters is Terminal-Bench or Design Arena: ASCII art, where it leads.

Which is cheaper, DeepSeek V3.2 or GPT-5.1-Codex-Mini?

DeepSeek V3.2 costs $0.28 per million input tokens and $0.42 per million output tokens; GPT-5.1-Codex-Mini costs $0.25 and $2.00. Cost per solved task is known for DeepSeek V3.2 only.

Which has the bigger context window, DeepSeek V3.2 or GPT-5.1-Codex-Mini?

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

How many benchmarks is the DeepSeek V3.2 vs GPT-5.1-Codex-Mini comparison based on?

22 benchmarks have a result for both models as of October 21, 2026. DeepSeek V3.2's coding index rests on 2 independent benchmarks and GPT-5.1-Codex-Mini's on 1. Where only one model has a result, the page says so instead of naming a winner.

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