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DeepSeek V4 Pro 0813 vs GPT-5.5

Updated October 21, 2026. 71 benchmarks have a result for both. Coding is ranked on the Vibe Coding Index; every other board is shown as published.

Replace DeepSeek V4 Pro 0813 Replace GPT-5.5
DeepSeek V4 Pro 0813DeepSeek
Coding
54.6
Overall
36.0
Output $/M
$1.98
11
GPT-5.5OpenAI
Coding
67.8
Overall
38.4
Output $/M
$30.00
59
vs boards won of 71 shared, 1 tied

Decision reading

Pick GPT-5.5 for coding: it scores 67.8 on the Vibe Coding Index against 54.6 for DeepSeek V4 Pro 0813.

Pick DeepSeek V4 Pro 0813 when output tokens cost 15.2x less, or when a solved task costs $0.10 against $1.65.

Model ADeepSeek V4 Pro 0813DeepSeek54.6/1001 independent benchmark$0.10 per solved taskModel BGPT-5.5OpenAI67.8/1002 independent benchmarks$1.65 per solved task
Shared results
71
DeepSeek V4 Pro 0813 only
7
GPT-5.5 only
61
Like-for-like categories
7 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 V4 Pro 0813 54.6 from 1 benchmark, GPT-5.5 67.8 from 2 benchmarks.
Widest category
Math, 16.2 points apart on average over 6 shared benchmarks.
Widest single gap
FrontierMath, tier 4: DeepSeek V4 Pro 0813 26.8% against GPT-5.5 72.5%, 45.7 points apart on a 0 to 100 scale.
Output price
DeepSeek V4 Pro 0813 $1.98 against GPT-5.5 $30.00 per million output tokens, 15.2x apart.
Context window
DeepSeek V4 Pro 0813 takes 1.05M tokens, GPT-5.5 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 V4 Pro 0813BarsGPT-5.5Ties
Coding611
Intelligence02
Agentic work34
Reasoning110
Math141 tie
Knowledge010
General018
All shared boards11591 tie
CodingLike-for-likeFour of these boards feed the Vibe Coding Index611
Coding benchmarks for DeepSeek V4 Pro 0813 and GPT-5.5
BenchmarkDeepSeek V4 Pro 0813GPT-5.5Leader
LiveBench codingNot measured85.1%Only GPT-5.5 measured
LMArena WebDev15821513DeepSeek V4 Pro 0813
AA Coding Index68.874.9GPT-5.5
LiveCodeBench (Vals AI)87.5%85.3%DeepSeek V4 Pro 0813
SWE-bench Verified (Vals AI)96.4%82.6%DeepSeek V4 Pro 0813
Terminal-Bench 4 (Vals AI)14.1%Not measuredOnly DeepSeek V4 Pro 0813 measured
Vibe Code Bench (Vals AI)82.3%69.8%DeepSeek V4 Pro 0813
Code migration (Vals AI)41.5%45.2%GPT-5.5
ProgramBench (Vals AI)0.0%0.5%GPT-5.5
IOI (Vals AI)51.6%Not measuredOnly DeepSeek V4 Pro 0813 measured
Terminal-Bench 2.1 (Vals AI)54.7%76.4%GPT-5.5
Vibe Code Bench 1-100 (Vals AI)17.5%Not measuredOnly DeepSeek V4 Pro 0813 measured
SkillsBench (Vals AI)53.8%62.5%GPT-5.5
CyberBench (Vals AI)72.9%Not measuredOnly DeepSeek V4 Pro 0813 measured
SciCode51.0%56.1%GPT-5.5
Terminal-Bench Hard (Artificial Analysis run)Not measured60.6%Only GPT-5.5 measured
Terminal-BenchNot measured84.7%Only GPT-5.5 measured
FrontierCode28.5%43.0%GPT-5.5
GSO-BenchNot measured40.2%Only GPT-5.5 measured
WeirdML66.2%84.9%GPT-5.5
MirrorCodeNot measured10.0%Only GPT-5.5 measured
ALE-Bench1403.21943.0GPT-5.5
LMArena Text: coding14691494GPT-5.5
LMArena Text: software and IT14621493GPT-5.5
LMArena WebDev: React15881506DeepSeek V4 Pro 0813
LMArena WebDev: HTML15661543DeepSeek V4 Pro 0813
LMArena WebDev: from an imageNot measured1532Only GPT-5.5 measured
Neither model has a result on the other 11 boards here
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index02
Intelligence benchmarks for DeepSeek V4 Pro 0813 and GPT-5.5
BenchmarkDeepSeek V4 Pro 0813GPT-5.5Leader
AA Intelligence Index36.038.4GPT-5.5
Epoch Capabilities Index155.6159.7GPT-5.5
Agentic workLike-for-likePublic boards, shown as published, kept out of the index34
Agentic work benchmarks for DeepSeek V4 Pro 0813 and GPT-5.5
BenchmarkDeepSeek V4 Pro 0813GPT-5.5Leader
AA Agentic Index41.336.4DeepSeek V4 Pro 0813
Design Arena: agents building web appsNot measured1117Only GPT-5.5 measured
Design Arena: agents building full-stack appsNot measured1089Only GPT-5.5 measured
Design Arena: agents building mobile appsNot measured1143Only GPT-5.5 measured
Design Arena: agents building Android appsNot measured1169Only GPT-5.5 measured
Design Arena: agents building Godot gamesNot measured1173Only GPT-5.5 measured
Design Arena: agents building gamesNot measured1179Only GPT-5.5 measured
Design Arena: HTML slidesNot measured1067Only GPT-5.5 measured
Design Arena: PowerPoint slidesNot measured1108Only GPT-5.5 measured
LiveBench researchNot measured61.6%Only GPT-5.5 measured
LiveBench browserNot measured48.0%Only GPT-5.5 measured
LiveBench long agenticNot measured44.6%Only GPT-5.5 measured
SREBench (Vals AI)1.9%3.8%GPT-5.5
Finance Agent (Vals AI)50.4%51.8%GPT-5.5
Tax Agent Bench (Vals AI)26.8%21.8%DeepSeek V4 Pro 0813
Legal Research Bench (Vals AI)40.9%40.4%DeepSeek V4 Pro 0813
Harvey's Legal Agent Benchmark (Vals AI)10.8%Not measuredOnly DeepSeek V4 Pro 0813 measured
Excel Modeling Benchmark (Vals AI)52.8%64.5%GPT-5.5
Terminal-Bench-Science (Vals AI)4.3%Not measuredOnly DeepSeek V4 Pro 0813 measured
Time Horizon Index (Vals AI)Not measured8.3%Only GPT-5.5 measured
τ²-Bench TelecomNot measured93.9%Only GPT-5.5 measured
APEX-Agents47.3%55.1%GPT-5.5
Remote Labor IndexNot measured6.3%Only GPT-5.5 measured
OSWorld 2.0Not measured13.0%Only GPT-5.5 measured
DeepResearch BenchNot measured54.0%Only GPT-5.5 measured
PostTrainBenchNot measured27.2%Only GPT-5.5 measured
Vending-Bench 2Not measured$7,524Only GPT-5.5 measured
Neither model has a result on the other 12 boards here
ReasoningLike-for-likePublic boards, shown as published, kept out of the index110
Reasoning benchmarks for DeepSeek V4 Pro 0813 and GPT-5.5
BenchmarkDeepSeek V4 Pro 0813GPT-5.5Leader
GPQA Diamond92.4%93.2%GPT-5.5
LiveBench reasoningNot measured89.7%Only GPT-5.5 measured
MMMU Pro (Vals AI)Not measured88.3%Only GPT-5.5 measured
GPQA Diamond (Artificial Analysis run)92.8%93.5%GPT-5.5
Humanity's Last Exam (Artificial Analysis run)41.0%45.8%GPT-5.5
GPQA Diamond (Epoch AI run)91.7%90.7%DeepSeek V4 Pro 0813
ARC-AGI90.5%95.0%GPT-5.5
ARC-AGI-261.3%85.0%GPT-5.5
SimpleBenchNot measured69.0%Only GPT-5.5 measured
Chess puzzles46.0%63.0%GPT-5.5
Mystery game puzzles43.0%56.0%GPT-5.5
EBR-benchNot measured34.3%Only GPT-5.5 measured
LMArena Text: hard prompts14581489GPT-5.5
LMArena Text: expert14591507GPT-5.5
LMArena Text: hard prompts in English14631483GPT-5.5
LMArena Vision: diagramsNot measured1325Only GPT-5.5 measured
LMArena Vision: homeworkNot measured1332Only GPT-5.5 measured
Neither model has a result on the other 4 boards here
MathLike-for-likePublic boards, shown as published, kept out of the index14
Math benchmarks for DeepSeek V4 Pro 0813 and GPT-5.5
BenchmarkDeepSeek V4 Pro 0813GPT-5.5Leader
OTIS Mock AIME98.6%84.4%DeepSeek V4 Pro 0813
FrontierMath, tiers 1 to 364.6%85.3%GPT-5.5
FrontierMath, tier 426.8%72.5%GPT-5.5
ProofBench50.0%50.0%Tie
LMArena Text: math14411487GPT-5.5
LMArena Text: mathematical work14431496GPT-5.5
Neither model has a result on the other 7 boards here
KnowledgeLike-for-likePublic boards, shown as published, kept out of the index010
Knowledge benchmarks for DeepSeek V4 Pro 0813 and GPT-5.5
BenchmarkDeepSeek V4 Pro 0813GPT-5.5Leader
MMLU Pro87.0%88.1%GPT-5.5
LegalBench (Vals AI)82.4%86.5%GPT-5.5
CaseLaw (Vals AI)Not measured66.2%Only GPT-5.5 measured
CorpFin (Vals AI)65.4%68.4%GPT-5.5
TaxEval (Vals AI)73.1%75.0%GPT-5.5
MortgageTax (Vals AI)Not measured68.8%Only GPT-5.5 measured
MedCode (Vals AI)42.5%49.1%GPT-5.5
SimpleQA Verified52.9%63.0%GPT-5.5
LMArena Text: science14571485GPT-5.5
LMArena Text: medicine and healthcare14461465GPT-5.5
LMArena Text: legal and government14591491GPT-5.5
LMArena Text: business and finance14421478GPT-5.5
Neither model has a result on the other 5 boards here
Web designDirectional onlyPublic boards, shown as published, kept out of the index9 boards, none shared
Web design benchmarks for DeepSeek V4 Pro 0813 and GPT-5.5
BenchmarkDeepSeek V4 Pro 0813GPT-5.5Leader
Design Arena: websitesNot measured1256Only GPT-5.5 measured
Design Arena: UI componentsNot measured1260Only GPT-5.5 measured
Design Arena: game devNot measured1294Only GPT-5.5 measured
Design Arena: data vizNot measured1265Only GPT-5.5 measured
Design Arena: 3DNot measured1198Only GPT-5.5 measured
Design Arena: all code categoriesNot measured1260Only GPT-5.5 measured
Design Arena: SVGNot measured1234Only GPT-5.5 measured
Design Arena: ASCII artNot measured1254Only GPT-5.5 measured
LiveBench designNot measured70.3%Only GPT-5.5 measured
GeneralLike-for-likePublic boards, shown as published, kept out of the index018
General benchmarks for DeepSeek V4 Pro 0813 and GPT-5.5
BenchmarkDeepSeek V4 Pro 0813GPT-5.5Leader
Vals Index53.0%Not measuredOnly DeepSeek V4 Pro 0813 measured
LiveBench data analysisNot measured81.6%Only GPT-5.5 measured
Public Benefits Bench (Vals AI)Not measured60.9%Only GPT-5.5 measured
SAGE (Vals AI)Not measured51.5%Only GPT-5.5 measured
MedScribe (Vals AI)80.2%86.9%GPT-5.5
Vals Multimodal IndexNot measured68.1%Only GPT-5.5 measured
IFBenchNot measured75.9%Only GPT-5.5 measured
Long context reasoning (AA-LCR)80.3%84.3%GPT-5.5
DTBench93.9%96.0%GPT-5.5
LMCA45.5%54.3%GPT-5.5
Surface Evolver BenchNot measured88.1%Only GPT-5.5 measured
Furniture assemblyNot measured44.2%Only GPT-5.5 measured
ExploitBenchNot measured47.4%Only GPT-5.5 measured
CL-bench LifeNot measured22.2%Only GPT-5.5 measured
LMArena Text14461471GPT-5.5
LMArena Text: instruction following14481478GPT-5.5
LMArena Text: creative writing14391455GPT-5.5
LMArena VisionNot measured1297Only GPT-5.5 measured
LMArena Text: English14571470GPT-5.5
LMArena Text: non-English14311467GPT-5.5
LMArena Text: Chinese14811534GPT-5.5
LMArena Text: GermanNot measured1480Only GPT-5.5 measured
LMArena Text: JapaneseNot measured1499Only GPT-5.5 measured
LMArena Text: Korean14491460GPT-5.5
LMArena Text: French14461485GPT-5.5
LMArena Text: Spanish14351468GPT-5.5
LMArena Text: Russian14481473GPT-5.5
LMArena Text: PolishNot measured1465Only GPT-5.5 measured
LMArena Text: multi-turn14541476GPT-5.5
LMArena Text: longer queries14581484GPT-5.5
LMArena Text: writing and language14431466GPT-5.5
LMArena Text: entertainment and media14241449GPT-5.5
LMArena Vision: EnglishNot measured1292Only GPT-5.5 measured
LMArena Vision: ChineseNot measured1360Only GPT-5.5 measured
LMArena Vision: reading textNot measured1306Only GPT-5.5 measured
LMArena Vision: humorNot measured1293Only GPT-5.5 measured
LMArena Vision: recognizing thingsNot measured1231Only GPT-5.5 measured
LMArena Vision: creative writingNot measured1301Only GPT-5.5 measured
LMArena DocumentNot measured1486Only GPT-5.5 measured
Neither model has a result on the other 7 boards here
Image generationNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
Image generation benchmarks for DeepSeek V4 Pro 0813 and GPT-5.5
BenchmarkDeepSeek V4 Pro 0813GPT-5.5Leader
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 V4 Pro 0813$0.0016Fits in one request
GPT-5.5$0.020Fits in one request

DeepSeek V4 Pro 0813 costs less

Repository review

50K input + 3K output tokens

DeepSeek V4 Pro 0813$0.039Fits in one request
GPT-5.5$0.340Fits in one request

DeepSeek V4 Pro 0813 costs less

Agent loop

200K input + 10K output tokens

DeepSeek V4 Pro 0813$0.152Fits in one request
GPT-5.5$1.30Fits in one request

DeepSeek V4 Pro 0813 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 V4 Pro 0813 and GPT-5.5
SpecificationDeepSeek V4 Pro 0813OpenAI GPT-5.5
MakerDeepSeekOpenAI
WeightsOpen weightsNo public weights listed
ReleasedAugust 12, 2026April 24, 2026
Context window1.05M1.05M
Input $/Mtok$0.66$5.00
Output $/Mtok$1.98$30.00
Coding index54.667.8
Independent measurements behind it12
Cost per solved task$0.10$1.65
SourceOpenRouter listingOpenRouter listing

Questions

Is DeepSeek V4 Pro 0813 better than GPT-5.5 for coding?

Pick GPT-5.5 for coding: it scores 67.8 on the Vibe Coding Index against 54.6 for DeepSeek V4 Pro 0813. Pick DeepSeek V4 Pro 0813 when output tokens cost 15.2x less, or when a solved task costs $0.10 against $1.65.

Which is cheaper, DeepSeek V4 Pro 0813 or GPT-5.5?

DeepSeek V4 Pro 0813 costs $0.66 per million input tokens and $1.98 per million output tokens; GPT-5.5 costs $5.00 and $30.00. Per solved SWE-bench Verified task, DeepSeek V4 Pro 0813 costs $0.10 and GPT-5.5 $1.65.

Which has the bigger context window, DeepSeek V4 Pro 0813 or GPT-5.5?

GPT-5.5, with 1.05M tokens against 1.05M.

How many benchmarks is the DeepSeek V4 Pro 0813 vs GPT-5.5 comparison based on?

71 benchmarks have a result for both models as of October 21, 2026. DeepSeek V4 Pro 0813's coding index rests on 1 independent benchmark and GPT-5.5's on 2. Where only one model has a result, the page says so instead of naming a winner.

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