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DeepSeek V3.2 vs GPT-4.1 Nano

DeepSeek V3.2 leads GPT-4.1 Nano on the Artificial Analysis Intelligence Index, 21.5 to 7.8, and GPT-4.1 Nano costs 2.2x less per output token ($0.40 vs $0.88 per million). Updated October 22, 2026; 56 benchmarks have a result for both.

Replace DeepSeek V3.2 Replace GPT-4.1 Nano
DeepSeek V3.2DeepSeek
Coding
30.0
Overall
37.9
Output $/M
$0.88
56
GPT-4.1 NanoOpenAI
Coding
No data
Overall
24.7
Output $/M
$0.40
0
vs boards won of 56 shared

DeepSeek V3.2 or GPT-4.1 Nano: which to pick

Only DeepSeek V3.2 has a coding score, 30.0 on the Vibe Coding Index; GPT-4.1 Nano has none, so the two cannot be ranked on coding.

Pick GPT-4.1 Nano for output tokens 2.2x cheaper ($0.40 vs $0.88 per million) and a larger context window (1.05M against 164K tokens).

Model ADeepSeek V3.2DeepSeek30.0/1003 independent benchmarks$0.99 per solved taskModel BGPT-4.1 NanoOpenAINot benchmarkedNo coding benchmarkNo cost per solved task
Shared results
56
DeepSeek V3.2 only
19
GPT-4.1 Nano only
15
Like-for-like categories
8 of 9

Only benchmarks that tested both models count toward a pick; a result only one model has is shown but not compared.

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 30.0 from 3 benchmarks, GPT-4.1 Nano not benchmarked.
Widest category
Agentic work, 73.4 points apart on average over 1 shared benchmark.
Widest single gap
τ²-Bench Telecom: DeepSeek V3.2 90.6% against GPT-4.1 Nano 17.3%, 73.4 points apart on a 0 to 100 scale.
Output price
DeepSeek V3.2 $0.88 against GPT-4.1 Nano $0.40 per million output tokens, 2.2x apart.
Context window
DeepSeek V3.2 takes 164K tokens, GPT-4.1 Nano 1.05M.

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-4.1 NanoTies
Coding60
Intelligence20
Agentic work10
Reasoning80
Math60
Knowledge100
Web design60
General170
All shared boards560
CodingLike-for-likeSix of these boards feed the Vibe Coding Index60
Coding benchmarks for DeepSeek V3.2 and GPT-4.1 Nano
BenchmarkDeepSeek V3.2GPT-4.1 NanoLeader
Aider polyglotNot measured8.9%Only GPT-4.1 Nano measured
SWE-bench Verified70.0%Not measuredOnly DeepSeek V3.2 measured
SWE-bench Multilingual59.0%Not measuredOnly DeepSeek V3.2 measured
LMArena WebDev1362Not measuredOnly DeepSeek V3.2 measured
AA Coding Index44.211.1DeepSeek V3.2
LiveCodeBench (Vals AI)80.7%42.7%DeepSeek V3.2
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%32.6%DeepSeek V3.2
Terminal-Bench Hard (Artificial Analysis run)35.6%3.8%DeepSeek V3.2
Terminal-Bench39.6%Not measuredOnly DeepSeek V3.2 measured
WeirdMLNot measured19.0%Only GPT-4.1 Nano measured
LMArena Text: coding14531306DeepSeek V3.2
LMArena Text: software and IT14491305DeepSeek V3.2
LMArena WebDev: React1350Not measuredOnly DeepSeek V3.2 measured
LMArena WebDev: HTML1371Not measuredOnly DeepSeek V3.2 measured
Neither model has a result on the other 23 boards here
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index20
Intelligence benchmarks for DeepSeek V3.2 and GPT-4.1 Nano
BenchmarkDeepSeek V3.2GPT-4.1 NanoLeader
AA Intelligence Index21.57.8DeepSeek V3.2
Epoch Capabilities Index146.1129.5DeepSeek V3.2
Agentic workLike-for-likePublic boards, shown as published, kept out of the index10
Agentic work benchmarks for DeepSeek V3.2 and GPT-4.1 Nano
BenchmarkDeepSeek V3.2GPT-4.1 NanoLeader
τ²-Bench Telecom90.6%17.3%DeepSeek V3.2
APEX-Agents21.3%Not measuredOnly DeepSeek V3.2 measured
Vending-Bench 2$1,034Not measuredOnly DeepSeek V3.2 measured
Berkeley Function Calling Leaderboard (BFCL)Not measured33.1%Only GPT-4.1 Nano measured
Neither model has a result on the other 37 boards here
ReasoningLike-for-likePublic boards, shown as published, kept out of the index80
Reasoning benchmarks for DeepSeek V3.2 and GPT-4.1 Nano
BenchmarkDeepSeek V3.2GPT-4.1 NanoLeader
GPQA Diamond80.3%50.8%DeepSeek V3.2
MMMU Pro (Vals AI)Not measured55.0%Only GPT-4.1 Nano measured
GPQA Diamond (Artificial Analysis run)84.0%51.2%DeepSeek V3.2
Humanity's Last Exam (Artificial Analysis run)24.6%3.8%DeepSeek V3.2
GPQA Diamond (Epoch AI run)Not measured48.9%Only GPT-4.1 Nano measured
ARC-AGI57.0%0.0%DeepSeek V3.2
ARC-AGI-24.0%0.0%DeepSeek V3.2
Chess puzzlesNot measured0.0%Only GPT-4.1 Nano measured
LMArena Text: hard prompts14341286DeepSeek V3.2
LMArena Text: expert14361271DeepSeek V3.2
LMArena Text: hard prompts in English14461293DeepSeek V3.2
Kagi LLM BenchmarkNot measured33.3%Only GPT-4.1 Nano measured
Neither model has a result on the other 10 boards here
MathLike-for-likePublic boards, shown as published, kept out of the index60
Math benchmarks for DeepSeek V3.2 and GPT-4.1 Nano
BenchmarkDeepSeek V3.2GPT-4.1 NanoLeader
AIME84.6%26.5%DeepSeek V3.2
MATH 500 (Vals AI)Not measured80.2%Only GPT-4.1 Nano measured
MGSM (Vals AI)86.0%69.3%DeepSeek V3.2
AA Math Index92.024.0DeepSeek V3.2
AIME 2025 (Artificial Analysis run)92.0%24.0%DeepSeek V3.2
OTIS Mock AIMENot measured28.9%Only GPT-4.1 Nano measured
MATH level 5Not measured70.0%Only GPT-4.1 Nano measured
LMArena Text: math14351274DeepSeek V3.2
LMArena Text: mathematical work14401274DeepSeek V3.2
Neither model has a result on the other 4 boards here
KnowledgeLike-for-likePublic boards, shown as published, kept out of the index100
Knowledge benchmarks for DeepSeek V3.2 and GPT-4.1 Nano
BenchmarkDeepSeek V3.2GPT-4.1 NanoLeader
MMLU Pro84.9%63.5%DeepSeek V3.2
LegalBench (Vals AI)76.1%61.1%DeepSeek V3.2
CaseLaw (Vals AI)55.4%Not measuredOnly DeepSeek V3.2 measured
CorpFin (Vals AI)51.0%42.1%DeepSeek V3.2
TaxEval (Vals AI)68.2%60.8%DeepSeek V3.2
MortgageTax (Vals AI)Not measured52.8%Only GPT-4.1 Nano measured
MedQA (Vals AI)93.9%68.2%DeepSeek V3.2
MMLU Pro (Artificial Analysis run)86.2%65.7%DeepSeek V3.2
SimpleQA VerifiedNot measured6.0%Only GPT-4.1 Nano measured
LMArena Text: science14461297DeepSeek V3.2
LMArena Text: medicine and healthcare14401276DeepSeek V3.2
LMArena Text: legal and government14251300DeepSeek V3.2
LMArena Text: business and finance14101267DeepSeek V3.2
Neither model has a result on the other 5 boards here
Web designLike-for-likePublic boards, shown as published, kept out of the index60
Web design benchmarks for DeepSeek V3.2 and GPT-4.1 Nano
BenchmarkDeepSeek V3.2GPT-4.1 NanoLeader
Design Arena: websites1175972DeepSeek V3.2
Design Arena: UI components1146913DeepSeek V3.2
Design Arena: game dev1131970DeepSeek V3.2
Design Arena: data viz1158891DeepSeek V3.2
Design Arena: 3D1132924DeepSeek V3.2
Design Arena: all code categories1163962DeepSeek V3.2
Design Arena: SVG1032Not measuredOnly DeepSeek V3.2 measured
Design Arena: ASCII art1083Not measuredOnly DeepSeek V3.2 measured
Neither model has a result on the other 1 board here
GeneralLike-for-likePublic boards, shown as published, kept out of the index170
General benchmarks for DeepSeek V3.2 and GPT-4.1 Nano
BenchmarkDeepSeek V3.2GPT-4.1 NanoLeader
IFBench60.7%32.0%DeepSeek V3.2
Long context reasoning (AA-LCR)73.3%20.3%DeepSeek V3.2
DTBench85.6%52.5%DeepSeek V3.2
LMCA28.8%5.5%DeepSeek V3.2
Fiction.LiveBenchNot measured25.0%Only GPT-4.1 Nano measured
CL-bench12.4%Not measuredOnly DeepSeek V3.2 measured
CL-bench Life7.4%Not measuredOnly DeepSeek V3.2 measured
LMArena Text14251285DeepSeek V3.2
LMArena Text: instruction following14131266DeepSeek V3.2
LMArena Text: creative writing14001260DeepSeek V3.2
LMArena VisionNot measured1063Only GPT-4.1 Nano measured
LMArena Text: English14391303DeepSeek V3.2
LMArena Text: non-English14091260DeepSeek V3.2
LMArena Text: Chinese14551270DeepSeek V3.2
LMArena Text: German14131288DeepSeek V3.2
LMArena Text: Japanese13741198DeepSeek V3.2
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: Russian14241261DeepSeek V3.2
LMArena Text: Polish1419Not measuredOnly DeepSeek V3.2 measured
LMArena Text: multi-turn14271277DeepSeek V3.2
LMArena Text: longer queries14281283DeepSeek V3.2
LMArena Text: writing and language14071261DeepSeek V3.2
LMArena Text: entertainment and media13951243DeepSeek V3.2
LMArena Vision: EnglishNot measured1101Only GPT-4.1 Nano measured
Neither model has a result on the other 20 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-4.1 Nano
BenchmarkDeepSeek V3.2GPT-4.1 NanoLeader
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$0.0007Fits in one request
GPT-4.1 Nano$0.0003Fits in one request

GPT-4.1 Nano costs less

Repository review

50K input + 3K output tokens

DeepSeek V3.2$0.017Fits in one request
GPT-4.1 Nano$0.0062Fits in one request

GPT-4.1 Nano costs less

Agent loop

200K input + 10K output tokens

DeepSeek V3.2$0.067Exceeds the context window
GPT-4.1 Nano$0.024Fits in one request

GPT-4.1 Nano 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-4.1 Nano
SpecificationDeepSeek V3.2OpenAI GPT-4.1 Nano
MakerDeepSeekOpenAI
WeightsOpen weightsNo public weights listed
ReleasedDecember 1, 2025April 14, 2025
Context window164K1.05M
Input $/Mtok$0.29$0.10
Output $/Mtok$0.88$0.40
Coding index30.0Not benchmarked
Independent measurements behind it30
Cost per solved task$0.99Not computable
SourceOpenRouter listingOpenRouter listing

Questions

Is DeepSeek V3.2 better than GPT-4.1 Nano for coding?

Only DeepSeek V3.2 has a coding score, 30.0 on the Vibe Coding Index; GPT-4.1 Nano has none, so the two cannot be ranked on coding. Pick GPT-4.1 Nano for output tokens 2.2x cheaper ($0.40 vs $0.88 per million) and a larger context window (1.05M against 164K tokens).

Which is cheaper, DeepSeek V3.2 or GPT-4.1 Nano?

DeepSeek V3.2 costs $0.29 per million input tokens and $0.88 per million output tokens; GPT-4.1 Nano costs $0.10 and $0.40. Cost per solved task is known for DeepSeek V3.2 only.

Which has the bigger context window, DeepSeek V3.2 or GPT-4.1 Nano?

GPT-4.1 Nano, with 1.05M tokens against 164K.

How many benchmarks is the DeepSeek V3.2 vs GPT-4.1 Nano comparison based on?

56 benchmarks have a result for both models as of October 22, 2026. DeepSeek V3.2's coding index rests on 3 independent benchmarks and GPT-4.1 Nano's on 0. Where only one model has a result, the page says so instead of naming a winner.

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