DeepSeek V4 Pro 0813 vs GPT-5
Updated October 21, 2026. 57 benchmarks have a result for both. Coding is ranked on the Vibe Coding Index; every other board is shown as published.
Decision reading
Pick GPT-5 for coding: it scores 72.2 on the Vibe Coding Index against 54.6 for DeepSeek V4 Pro 0813.
Pick DeepSeek V4 Pro 0813 when output tokens cost 5.1x less, or when a solved task costs $0.10 against $0.39.
- Shared results
- 57
- DeepSeek V4 Pro 0813 only
- 21
- GPT-5 only
- 52
- Like-for-like categories
- 6 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.
Coding
Vibe Coding Index, four public coding benchmarks
GPT-5
GPT-5 scores 72.2 against 54.6.
1 and 3 benchmarks behind the scores
Intelligence
AA Intelligence Index
DeepSeek V4 Pro 0813
DeepSeek V4 Pro 0813 leads, 36.0 against 23.0.
Same board, both measured
Agentic work
AA Agentic Index
No call
Only DeepSeek V4 Pro 0813 has a AA Agentic Index result, 41.3.
Directional only
Reasoning
GPQA Diamond
DeepSeek V4 Pro 0813
DeepSeek V4 Pro 0813 leads, 92.4% against 85.6%.
Same board, both measured
Math
AIME
No call
Only GPT-5 has a AIME result, 93.4%.
Directional only
Knowledge
MMLU Pro
DeepSeek V4 Pro 0813
DeepSeek V4 Pro 0813 leads, 87.0% against 86.5%.
Same board, both measured
Web design
Design Arena: websites
No call
Only GPT-5 has a Design Arena: websites result, 1185.
Directional only
General
Vals Index
No call
Only DeepSeek V4 Pro 0813 has a Vals Index result, 53.0%.
Directional only
Long documents
Listed context window
DeepSeek V4 Pro 0813
DeepSeek V4 Pro 0813 takes 1.05M tokens against 400K.
Listed by OpenRouter
Everyday cost
1K input + 500 output tokens
DeepSeek V4 Pro 0813
DeepSeek V4 Pro 0813 $0.0016, GPT-5 $0.0063 per turn.
List prices
Cost per solved task
One SWE-bench Verified task, solved
DeepSeek V4 Pro 0813
DeepSeek V4 Pro 0813 $0.10, GPT-5 $0.39.
Published attempt cost and pass rate
At a glance
- Coding index
- DeepSeek V4 Pro 0813 54.6 from 1 benchmark, GPT-5 72.2 from 3 benchmarks.
- Widest category
- Coding, 20.7 points apart on average over 10 shared benchmarks.
- Widest single gap
- Vibe Code Bench (Vals AI): DeepSeek V4 Pro 0813 82.3% against GPT-5 20.1%, 62.2 points apart on a 0 to 100 scale.
- Output price
- DeepSeek V4 Pro 0813 $1.98 against GPT-5 $10.00 per million output tokens, 5.1x apart.
- Context window
- DeepSeek V4 Pro 0813 takes 1.05M tokens, GPT-5 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.
| Category | DeepSeek V4 Pro 0813 | Bars | GPT-5 | Ties |
|---|---|---|---|---|
| Coding | 10 | 0 | ||
| Intelligence | 2 | 0 | ||
| Reasoning | 11 | 0 | ||
| Math | 6 | 0 | ||
| Knowledge | 7 | 3 | ||
| General | 17 | 1 | ||
| All shared boards | 53 | 4 |
CodingLike-for-likeFour of these boards feed the Vibe Coding Index100
| Benchmark | DeepSeek V4 Pro 0813 | GPT-5 | Leader |
|---|---|---|---|
| Aider polyglot | Not measured | 88.0% | Only GPT-5 measured |
| SWE-bench Verified | Not measured | 74.4% | Only GPT-5 measured |
| LMArena WebDev | 1582 | 1418 | DeepSeek V4 Pro 0813 |
| AA Coding Index | 68.8 | 37.8 | DeepSeek V4 Pro 0813 |
| LiveCodeBench (Vals AI) | 87.5% | 85.9% | DeepSeek V4 Pro 0813 |
| SWE-bench Verified (Vals AI) | 96.4% | 69.0% | DeepSeek V4 Pro 0813 |
| Terminal-Bench 4 (Vals AI) | 14.1% | Not measured | Only DeepSeek V4 Pro 0813 measured |
| Vibe Code Bench (Vals AI) | 82.3% | 20.1% | DeepSeek V4 Pro 0813 |
| Code migration (Vals AI) | 41.5% | Not measured | Only DeepSeek V4 Pro 0813 measured |
| ProgramBench (Vals AI) | 0.0% | Not measured | Only DeepSeek V4 Pro 0813 measured |
| IOI (Vals AI) | 51.6% | Not measured | Only DeepSeek V4 Pro 0813 measured |
| Terminal-Bench 2.1 (Vals AI) | 54.7% | Not measured | Only DeepSeek V4 Pro 0813 measured |
| Vibe Code Bench 1-100 (Vals AI) | 17.5% | Not measured | Only DeepSeek V4 Pro 0813 measured |
| SkillsBench (Vals AI) | 53.8% | Not measured | Only DeepSeek V4 Pro 0813 measured |
| CyberBench (Vals AI) | 72.9% | Not measured | Only DeepSeek V4 Pro 0813 measured |
| LiveCodeBench (Artificial Analysis run) | Not measured | 84.6% | Only GPT-5 measured |
| SciCode | 51.0% | Not measured | Only DeepSeek V4 Pro 0813 measured |
| Terminal-Bench Hard (Artificial Analysis run) | Not measured | 37.9% | Only GPT-5 measured |
| Terminal-Bench | Not measured | 49.6% | Only GPT-5 measured |
| FrontierCode | 28.5% | Not measured | Only DeepSeek V4 Pro 0813 measured |
| GSO-Bench | Not measured | 6.9% | Only GPT-5 measured |
| WeirdML | 66.2% | 60.7% | DeepSeek V4 Pro 0813 |
| ALE-Bench | 1403.2 | 807.6 | DeepSeek V4 Pro 0813 |
| LMArena Text: coding | 1469 | 1436 | DeepSeek V4 Pro 0813 |
| LMArena Text: software and IT | 1462 | 1420 | DeepSeek V4 Pro 0813 |
| LMArena WebDev: React | 1588 | Not measured | Only DeepSeek V4 Pro 0813 measured |
| LMArena WebDev: HTML | 1566 | 1427 | DeepSeek V4 Pro 0813 |
| Neither model has a result on the other 11 boards here | |||
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index20
| Benchmark | DeepSeek V4 Pro 0813 | GPT-5 | Leader |
|---|---|---|---|
| AA Intelligence Index | 36.0 | 23.0 | DeepSeek V4 Pro 0813 |
| Epoch Capabilities Index | 155.6 | 150.0 | DeepSeek V4 Pro 0813 |
Agentic workDirectional onlyPublic boards, shown as published, kept out of the index15 boards, none shared
| Benchmark | DeepSeek V4 Pro 0813 | GPT-5 | Leader |
|---|---|---|---|
| AA Agentic Index | 41.3 | Not measured | Only DeepSeek V4 Pro 0813 measured |
| SREBench (Vals AI) | 1.9% | Not measured | Only DeepSeek V4 Pro 0813 measured |
| Finance Agent (Vals AI) | 50.4% | Not measured | Only DeepSeek V4 Pro 0813 measured |
| Tax Agent Bench (Vals AI) | 26.8% | Not measured | Only DeepSeek V4 Pro 0813 measured |
| Legal Research Bench (Vals AI) | 40.9% | Not measured | Only DeepSeek V4 Pro 0813 measured |
| Harvey's Legal Agent Benchmark (Vals AI) | 10.8% | Not measured | Only DeepSeek V4 Pro 0813 measured |
| Excel Modeling Benchmark (Vals AI) | 52.8% | Not measured | Only DeepSeek V4 Pro 0813 measured |
| Terminal-Bench-Science (Vals AI) | 4.3% | Not measured | Only DeepSeek V4 Pro 0813 measured |
| τ²-Bench Telecom | Not measured | 86.5% | Only GPT-5 measured |
| APEX-Agents | 47.3% | Not measured | Only DeepSeek V4 Pro 0813 measured |
| METR time horizons | Not measured | 69.6% | Only GPT-5 measured |
| Remote Labor Index | Not measured | 1.7% | Only GPT-5 measured |
| GDPval | Not measured | 34.8% | Only GPT-5 measured |
| BALROG | Not measured | 32.8% | Only GPT-5 measured |
| DeepResearch Bench | Not measured | 49.6% | Only GPT-5 measured |
| Neither model has a result on the other 24 boards here | |||
ReasoningLike-for-likePublic boards, shown as published, kept out of the index110
| Benchmark | DeepSeek V4 Pro 0813 | GPT-5 | Leader |
|---|---|---|---|
| GPQA Diamond | 92.4% | 85.6% | DeepSeek V4 Pro 0813 |
| MMMU Pro (Vals AI) | Not measured | 81.5% | Only GPT-5 measured |
| GPQA Diamond (Artificial Analysis run) | 92.8% | 85.4% | DeepSeek V4 Pro 0813 |
| Humanity's Last Exam (Artificial Analysis run) | 41.0% | 28.5% | DeepSeek V4 Pro 0813 |
| GPQA Diamond (Epoch AI run) | 91.7% | 86.2% | DeepSeek V4 Pro 0813 |
| ARC-AGI | 90.5% | 65.7% | DeepSeek V4 Pro 0813 |
| ARC-AGI-2 | 61.3% | 9.9% | DeepSeek V4 Pro 0813 |
| SimpleBench | Not measured | 56.7% | Only GPT-5 measured |
| Chess puzzles | 46.0% | 36.0% | DeepSeek V4 Pro 0813 |
| Mystery game puzzles | 43.0% | 23.0% | DeepSeek V4 Pro 0813 |
| EBR-bench | Not measured | 12.7% | Only GPT-5 measured |
| VPCT | Not measured | 66.0% | Only GPT-5 measured |
| LMArena Text: hard prompts | 1458 | 1415 | DeepSeek V4 Pro 0813 |
| LMArena Text: expert | 1459 | 1419 | DeepSeek V4 Pro 0813 |
| LMArena Text: hard prompts in English | 1463 | 1419 | DeepSeek V4 Pro 0813 |
| LMArena Vision: diagrams | Not measured | 1252 | Only GPT-5 measured |
| LMArena Vision: homework | Not measured | 1278 | Only GPT-5 measured |
| Neither model has a result on the other 4 boards here | |||
MathLike-for-likePublic boards, shown as published, kept out of the index60
| Benchmark | DeepSeek V4 Pro 0813 | GPT-5 | Leader |
|---|---|---|---|
| AIME | Not measured | 93.4% | Only GPT-5 measured |
| MATH 500 (Vals AI) | Not measured | 96.0% | Only GPT-5 measured |
| MGSM (Vals AI) | Not measured | 92.8% | Only GPT-5 measured |
| AA Math Index | Not measured | 94.3 | Only GPT-5 measured |
| AIME 2025 (Artificial Analysis run) | Not measured | 94.3% | Only GPT-5 measured |
| OTIS Mock AIME | 98.6% | 91.4% | DeepSeek V4 Pro 0813 |
| FrontierMath, tiers 1 to 3 | 64.6% | 55.4% | DeepSeek V4 Pro 0813 |
| FrontierMath, tier 4 | 26.8% | 22.0% | DeepSeek V4 Pro 0813 |
| ProofBench | 50.0% | 18.0% | DeepSeek V4 Pro 0813 |
| MATH level 5 | Not measured | 98.1% | Only GPT-5 measured |
| LMArena Text: math | 1441 | 1407 | DeepSeek V4 Pro 0813 |
| LMArena Text: mathematical work | 1443 | 1405 | DeepSeek V4 Pro 0813 |
| Neither model has a result on the other 1 board here | |||
KnowledgeLike-for-likePublic boards, shown as published, kept out of the index73
| Benchmark | DeepSeek V4 Pro 0813 | GPT-5 | Leader |
|---|---|---|---|
| MMLU Pro | 87.0% | 86.5% | DeepSeek V4 Pro 0813 |
| LegalBench (Vals AI) | 82.4% | 86.0% | GPT-5 |
| CaseLaw (Vals AI) | Not measured | 66.5% | Only GPT-5 measured |
| CorpFin (Vals AI) | 65.4% | 61.1% | DeepSeek V4 Pro 0813 |
| TaxEval (Vals AI) | 73.1% | 73.4% | GPT-5 |
| MortgageTax (Vals AI) | Not measured | 65.5% | Only GPT-5 measured |
| MedQA (Vals AI) | Not measured | 96.3% | Only GPT-5 measured |
| MedCode (Vals AI) | 42.5% | 49.6% | GPT-5 |
| MMLU Pro (Artificial Analysis run) | Not measured | 87.1% | Only GPT-5 measured |
| SimpleQA Verified | 52.9% | 50.1% | DeepSeek V4 Pro 0813 |
| GeoBench | Not measured | 81.0% | Only GPT-5 measured |
| LMArena Text: science | 1457 | 1416 | DeepSeek V4 Pro 0813 |
| LMArena Text: medicine and healthcare | 1446 | 1413 | DeepSeek V4 Pro 0813 |
| LMArena Text: legal and government | 1459 | 1431 | DeepSeek V4 Pro 0813 |
| LMArena Text: business and finance | 1442 | 1400 | DeepSeek V4 Pro 0813 |
| Neither model has a result on the other 2 boards here | |||
Web designDirectional onlyPublic boards, shown as published, kept out of the index8 boards, none shared
| Benchmark | DeepSeek V4 Pro 0813 | GPT-5 | Leader |
|---|---|---|---|
| Design Arena: websites | Not measured | 1185 | Only GPT-5 measured |
| Design Arena: UI components | Not measured | 1179 | Only GPT-5 measured |
| Design Arena: game dev | Not measured | 1185 | Only GPT-5 measured |
| Design Arena: data viz | Not measured | 1221 | Only GPT-5 measured |
| Design Arena: 3D | Not measured | 1056 | Only GPT-5 measured |
| Design Arena: all code categories | Not measured | 1168 | Only GPT-5 measured |
| Design Arena: SVG | Not measured | 1188 | Only GPT-5 measured |
| Design Arena: ASCII art | Not measured | 1140 | Only GPT-5 measured |
| Neither model has a result on the other 1 board here | |||
GeneralLike-for-likePublic boards, shown as published, kept out of the index171
| Benchmark | DeepSeek V4 Pro 0813 | GPT-5 | Leader |
|---|---|---|---|
| Vals Index | 53.0% | Not measured | Only DeepSeek V4 Pro 0813 measured |
| SAGE (Vals AI) | Not measured | 43.7% | Only GPT-5 measured |
| MedScribe (Vals AI) | 80.2% | 83.7% | GPT-5 |
| IFBench | Not measured | 73.1% | Only GPT-5 measured |
| Long context reasoning (AA-LCR) | 80.3% | 78.2% | DeepSeek V4 Pro 0813 |
| DTBench | 93.9% | 90.7% | DeepSeek V4 Pro 0813 |
| LMCA | 45.5% | 40.0% | DeepSeek V4 Pro 0813 |
| Fiction.LiveBench | Not measured | 97.2% | Only GPT-5 measured |
| Creative writing (Lech Mazur) | Not measured | 86.0% | Only GPT-5 measured |
| LMArena Text | 1446 | 1406 | DeepSeek V4 Pro 0813 |
| LMArena Text: instruction following | 1448 | 1388 | DeepSeek V4 Pro 0813 |
| LMArena Text: creative writing | 1439 | 1365 | DeepSeek V4 Pro 0813 |
| LMArena Vision | Not measured | 1232 | Only GPT-5 measured |
| LMArena Text: English | 1457 | 1409 | DeepSeek V4 Pro 0813 |
| LMArena Text: non-English | 1431 | 1397 | DeepSeek V4 Pro 0813 |
| LMArena Text: Chinese | 1481 | 1422 | DeepSeek V4 Pro 0813 |
| LMArena Text: German | Not measured | 1416 | Only GPT-5 measured |
| LMArena Text: Japanese | Not measured | 1409 | Only GPT-5 measured |
| LMArena Text: Korean | 1449 | 1360 | DeepSeek V4 Pro 0813 |
| LMArena Text: French | 1446 | 1409 | DeepSeek V4 Pro 0813 |
| LMArena Text: Spanish | 1435 | 1399 | DeepSeek V4 Pro 0813 |
| LMArena Text: Russian | 1448 | 1407 | DeepSeek V4 Pro 0813 |
| LMArena Text: Polish | Not measured | 1431 | Only GPT-5 measured |
| LMArena Text: multi-turn | 1454 | 1426 | DeepSeek V4 Pro 0813 |
| LMArena Text: longer queries | 1458 | 1399 | DeepSeek V4 Pro 0813 |
| LMArena Text: writing and language | 1443 | 1384 | DeepSeek V4 Pro 0813 |
| LMArena Text: entertainment and media | 1424 | 1379 | DeepSeek V4 Pro 0813 |
| LMArena Vision: English | Not measured | 1231 | Only GPT-5 measured |
| LMArena Vision: Chinese | Not measured | 1267 | Only GPT-5 measured |
| LMArena Vision: reading text | Not measured | 1246 | Only GPT-5 measured |
| LMArena Vision: humor | Not measured | 1219 | Only GPT-5 measured |
| LMArena Vision: captioning | Not measured | 1212 | Only GPT-5 measured |
| LMArena Vision: recognizing things | Not measured | 1263 | Only GPT-5 measured |
| LMArena Vision: creative writing | Not measured | 1210 | Only GPT-5 measured |
| Neither model has a result on the other 12 boards here | |||
Image generationNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
| Benchmark | DeepSeek V4 Pro 0813 | GPT-5 | Leader |
|---|---|---|---|
| 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 costs less
Repository review
50K input + 3K output tokens
DeepSeek V4 Pro 0813 costs less
Agent loop
200K input + 10K output tokens
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.
| Specification | DeepSeek V4 Pro 0813 | OpenAI GPT-5 |
|---|---|---|
| Maker | DeepSeek | OpenAI |
| Weights | Open weights | No public weights listed |
| Released | August 12, 2026 | August 7, 2025 |
| Context window | 1.05M | 400K |
| Input $/Mtok | $0.66 | $1.25 |
| Output $/Mtok | $1.98 | $10.00 |
| Coding index | 54.6 | 72.2 |
| Independent measurements behind it | 1 | 3 |
| Cost per solved task | $0.10 | $0.39 |
| Source | OpenRouter listing | OpenRouter listing |
Questions
Is DeepSeek V4 Pro 0813 better than GPT-5 for coding?
Pick GPT-5 for coding: it scores 72.2 on the Vibe Coding Index against 54.6 for DeepSeek V4 Pro 0813. Pick DeepSeek V4 Pro 0813 when output tokens cost 5.1x less, or when a solved task costs $0.10 against $0.39.
Which is cheaper, DeepSeek V4 Pro 0813 or GPT-5?
DeepSeek V4 Pro 0813 costs $0.66 per million input tokens and $1.98 per million output tokens; GPT-5 costs $1.25 and $10.00. Per solved SWE-bench Verified task, DeepSeek V4 Pro 0813 costs $0.10 and GPT-5 $0.39.
Which has the bigger context window, DeepSeek V4 Pro 0813 or GPT-5?
DeepSeek V4 Pro 0813, with 1.05M tokens against 400K.
How many benchmarks is the DeepSeek V4 Pro 0813 vs GPT-5 comparison based on?
57 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's on 3. Where only one model has a result, the page says so instead of naming a winner.