DeepSeek V4 Pro 0813 vs GPT-5.6 Sol
GPT-5.6 Sol leads DeepSeek V4 Pro 0813 on coding, 73.5 to 56.1 on the Vibe Coding Index, and DeepSeek V4 Pro 0813 costs 10.1x less per output token ($1.98 vs $20.00 per million). Updated October 22, 2026; 75 benchmarks have a result for both.
DeepSeek V4 Pro 0813 or GPT-5.6 Sol: which to pick
Pick GPT-5.6 Sol for coding: it scores 73.5 on the Vibe Coding Index against 56.1 for DeepSeek V4 Pro 0813.
Pick DeepSeek V4 Pro 0813 for output tokens 10.1x cheaper ($1.98 vs $20.00 per million) and a lower cost per solved task ($0.10 against $1.20).
- Shared results
- 75
- DeepSeek V4 Pro 0813 only
- 3
- GPT-5.6 Sol only
- 64
- Like-for-like categories
- 7 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.
Coding
Vibe Coding Index, six public coding benchmarks
GPT-5.6 Sol
GPT-5.6 Sol scores 73.5 against 56.1.
5 and 6 benchmarks behind the scores
Intelligence
AA Intelligence Index
GPT-5.6 Sol
GPT-5.6 Sol leads, 47.0 against 36.0.
Same board, both measured
Agentic work
AA Agentic Index
GPT-5.6 Sol
GPT-5.6 Sol leads, 50.2 against 41.3.
Same board, both measured
Reasoning
GPQA Diamond
GPT-5.6 Sol
GPT-5.6 Sol leads, 95.2% against 92.4%.
Same board, both measured
Knowledge
MMLU Pro
GPT-5.6 Sol
GPT-5.6 Sol leads, 89.1% against 87.0%.
Same board, both measured
Web design
Design Arena: websites
No call
Only GPT-5.6 Sol has a Design Arena: websites result, 1321.
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
GPT-5.6 Sol
GPT-5.6 Sol takes 1.05M tokens against 1.05M.
Listed by OpenRouter
Everyday cost
1K input + 500 output tokens
DeepSeek V4 Pro 0813
DeepSeek V4 Pro 0813 $0.0016, GPT-5.6 Sol $0.014 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-5.6 Sol $1.20.
Published attempt cost and pass rate
At a glance
- Coding index
- DeepSeek V4 Pro 0813 56.1 from 5 benchmarks, GPT-5.6 Sol 73.5 from 6 benchmarks.
- Widest category
- Math, 21.5 points apart on average over 6 shared benchmarks.
- Widest single gap
- FrontierMath, tier 4: DeepSeek V4 Pro 0813 26.8% against GPT-5.6 Sol 82.9%, 56.1 points apart on a 0 to 100 scale.
- Output price
- DeepSeek V4 Pro 0813 $1.98 against GPT-5.6 Sol $20.00 per million output tokens, 10.1x apart.
- Context window
- DeepSeek V4 Pro 0813 takes 1.05M tokens, GPT-5.6 Sol 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.
| Category | DeepSeek V4 Pro 0813 | Bars | GPT-5.6 Sol | Ties |
|---|---|---|---|---|
| Coding | 3 | 18 | ||
| Intelligence | 0 | 2 | ||
| Agentic work | 0 | 7 | ||
| Reasoning | 0 | 11 | ||
| Math | 0 | 6 | ||
| Knowledge | 3 | 7 | ||
| General | 1 | 17 | ||
| All shared boards | 7 | 68 |
CodingLike-for-likeSix of these boards feed the Vibe Coding Index318
| Benchmark | DeepSeek V4 Pro 0813 | GPT-5.6 Sol | Leader |
|---|---|---|---|
| LiveBench coding | Not measured | 89.7% | Only GPT-5.6 Sol measured |
| LMArena WebDev | 1582 | 1616 | GPT-5.6 Sol |
| AA Coding Index | 68.8 | 77.4 | GPT-5.6 Sol |
| LiveCodeBench (Vals AI) | 87.5% | 82.6% | DeepSeek V4 Pro 0813 |
| SWE-bench Verified (Vals AI) | 96.4% | 96.2% | DeepSeek V4 Pro 0813 |
| Terminal-Bench 4 (Vals AI) | 14.1% | 37.9% | GPT-5.6 Sol |
| Vibe Code Bench (Vals AI) | 82.3% | 80.5% | DeepSeek V4 Pro 0813 |
| Code migration (Vals AI) | 41.5% | 52.9% | GPT-5.6 Sol |
| ProgramBench (Vals AI) | 0.0% | 1.5% | GPT-5.6 Sol |
| IOI (Vals AI) | 51.6% | 91.2% | GPT-5.6 Sol |
| Terminal-Bench 2.1 (Vals AI) | 54.7% | 85.8% | GPT-5.6 Sol |
| Vibe Code Bench 1-100 (Vals AI) | 17.5% | 20.0% | GPT-5.6 Sol |
| SkillsBench (Vals AI) | 53.8% | 54.1% | GPT-5.6 Sol |
| CyberBench (Vals AI) | 72.9% | 76.3% | GPT-5.6 Sol |
| SciCode | 51.0% | 57.8% | GPT-5.6 Sol |
| Terminal-Bench Hard (Artificial Analysis run) | Not measured | 65.9% | Only GPT-5.6 Sol measured |
| FrontierCode | 28.5% | 47.5% | GPT-5.6 Sol |
| FrontierSWE | Not measured | 32.2% | Only GPT-5.6 Sol measured |
| GSO-Bench | Not measured | 76.5% | Only GPT-5.6 Sol measured |
| WeirdML | 66.2% | 88.8% | GPT-5.6 Sol |
| MirrorCode | Not measured | 20.0% | Only GPT-5.6 Sol measured |
| ALE-Bench | 1403.2 | 2176.9 | GPT-5.6 Sol |
| LMArena Text: coding | 1469 | 1496 | GPT-5.6 Sol |
| LMArena Text: software and IT | 1462 | 1489 | GPT-5.6 Sol |
| LMArena WebDev: React | 1588 | 1620 | GPT-5.6 Sol |
| LMArena WebDev: HTML | 1566 | 1618 | GPT-5.6 Sol |
| LMArena WebDev: from an image | Not measured | 1609 | Only GPT-5.6 Sol measured |
| SciCode | Not measured | 10.8% | Only GPT-5.6 Sol measured |
| Neither model has a result on the other 11 boards here | |||
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index02
| Benchmark | DeepSeek V4 Pro 0813 | GPT-5.6 Sol | Leader |
|---|---|---|---|
| AA Intelligence Index | 36.0 | 47.0 | GPT-5.6 Sol |
| Epoch Capabilities Index | 155.6 | 162.8 | GPT-5.6 Sol |
Agentic workLike-for-likePublic boards, shown as published, kept out of the index07
| Benchmark | DeepSeek V4 Pro 0813 | GPT-5.6 Sol | Leader |
|---|---|---|---|
| AA Agentic Index | 41.3 | 50.2 | GPT-5.6 Sol |
| Design Arena: agents building web apps | Not measured | 1245 | Only GPT-5.6 Sol measured |
| Design Arena: agents building full-stack apps | Not measured | 1261 | Only GPT-5.6 Sol measured |
| Design Arena: agents building mobile apps | Not measured | 1248 | Only GPT-5.6 Sol measured |
| Design Arena: agents building Android apps | Not measured | 1240 | Only GPT-5.6 Sol measured |
| Design Arena: agents building Godot games | Not measured | 1260 | Only GPT-5.6 Sol measured |
| Design Arena: agents building games | Not measured | 1266 | Only GPT-5.6 Sol measured |
| Design Arena: HTML slides | Not measured | 1236 | Only GPT-5.6 Sol measured |
| Design Arena: PowerPoint slides | Not measured | 1215 | Only GPT-5.6 Sol measured |
| LiveBench research | Not measured | 54.5% | Only GPT-5.6 Sol measured |
| LiveBench browser | Not measured | 88.0% | Only GPT-5.6 Sol measured |
| LiveBench long agentic | Not measured | 48.5% | Only GPT-5.6 Sol measured |
| SREBench (Vals AI) | 1.9% | 30.5% | GPT-5.6 Sol |
| Finance Agent (Vals AI) | 50.4% | 53.8% | GPT-5.6 Sol |
| Tax Agent Bench (Vals AI) | 26.8% | 31.1% | GPT-5.6 Sol |
| Legal Research Bench (Vals AI) | 40.9% | 48.1% | GPT-5.6 Sol |
| Harvey's Legal Agent Benchmark (Vals AI) | 10.8% | Not measured | Only DeepSeek V4 Pro 0813 measured |
| Excel Modeling Benchmark (Vals AI) | 52.8% | 72.3% | GPT-5.6 Sol |
| BioMysteryBench (Vals AI) | Not measured | 71.1% | Only GPT-5.6 Sol measured |
| Terminal-Bench-Science (Vals AI) | 4.3% | 20.0% | GPT-5.6 Sol |
| Vals Science Index | Not measured | 41.5% | Only GPT-5.6 Sol measured |
| Time Horizon Index (Vals AI) | Not measured | 23.8% | Only GPT-5.6 Sol measured |
| CUA-bench (Vals AI) | Not measured | 8.3% | Only GPT-5.6 Sol measured |
| τ²-Bench Telecom | Not measured | 85.1% | Only GPT-5.6 Sol measured |
| APEX-Agents | 47.3% | Not measured | Only DeepSeek V4 Pro 0813 measured |
| OSWorld 2.0 | Not measured | 27.3% | Only GPT-5.6 Sol measured |
| BALROG | Not measured | 60.0% | Only GPT-5.6 Sol measured |
| PostTrainBench | Not measured | 36.2% | Only GPT-5.6 Sol measured |
| Vending-Bench 2 | Not measured | $9,619 | Only GPT-5.6 Sol measured |
| LMArena Search | Not measured | 1261 | Only GPT-5.6 Sol measured |
| Neither model has a result on the other 11 boards here | |||
ReasoningLike-for-likePublic boards, shown as published, kept out of the index011
| Benchmark | DeepSeek V4 Pro 0813 | GPT-5.6 Sol | Leader |
|---|---|---|---|
| GPQA Diamond | 92.4% | 95.2% | GPT-5.6 Sol |
| LiveBench reasoning | Not measured | 91.7% | Only GPT-5.6 Sol measured |
| MysteryMechanism (Vals AI) | Not measured | 33.3% | Only GPT-5.6 Sol measured |
| MMMU Pro (Vals AI) | Not measured | 88.8% | Only GPT-5.6 Sol measured |
| GPQA Diamond (Artificial Analysis run) | 92.8% | 94.1% | GPT-5.6 Sol |
| Humanity's Last Exam (Artificial Analysis run) | 41.0% | 49.5% | GPT-5.6 Sol |
| GPQA Diamond (Epoch AI run) | 91.7% | 93.5% | GPT-5.6 Sol |
| ARC-AGI | 90.5% | 97.5% | GPT-5.6 Sol |
| ARC-AGI-2 | 61.3% | 92.5% | GPT-5.6 Sol |
| SimpleBench | Not measured | 64.8% | Only GPT-5.6 Sol measured |
| Chess puzzles | 46.0% | 59.0% | GPT-5.6 Sol |
| Mystery game puzzles | 43.0% | 58.0% | GPT-5.6 Sol |
| EBR-bench | Not measured | 44.8% | Only GPT-5.6 Sol measured |
| LMArena Text: hard prompts | 1458 | 1483 | GPT-5.6 Sol |
| LMArena Text: expert | 1459 | 1517 | GPT-5.6 Sol |
| LMArena Text: hard prompts in English | 1463 | 1477 | GPT-5.6 Sol |
| LMArena Vision: diagrams | Not measured | 1305 | Only GPT-5.6 Sol measured |
| LMArena Vision: homework | Not measured | 1305 | Only GPT-5.6 Sol measured |
| Kagi LLM Benchmark | Not measured | 67.0% | Only GPT-5.6 Sol measured |
| Neither model has a result on the other 3 boards here | |||
MathLike-for-likePublic boards, shown as published, kept out of the index06
| Benchmark | DeepSeek V4 Pro 0813 | GPT-5.6 Sol | Leader |
|---|---|---|---|
| OTIS Mock AIME | 98.6% | 100.0% | GPT-5.6 Sol |
| FrontierMath, tiers 1 to 3 | 64.6% | 89.1% | GPT-5.6 Sol |
| FrontierMath, tier 4 | 26.8% | 82.9% | GPT-5.6 Sol |
| ProofBench | 50.0% | 83.0% | GPT-5.6 Sol |
| LMArena Text: math | 1441 | 1473 | GPT-5.6 Sol |
| LMArena Text: mathematical work | 1443 | 1496 | GPT-5.6 Sol |
| Neither model has a result on the other 7 boards here | |||
KnowledgeLike-for-likePublic boards, shown as published, kept out of the index37
| Benchmark | DeepSeek V4 Pro 0813 | GPT-5.6 Sol | Leader |
|---|---|---|---|
| MMLU Pro | 87.0% | 89.1% | GPT-5.6 Sol |
| LegalBench (Vals AI) | 82.4% | 87.0% | GPT-5.6 Sol |
| CorpFin (Vals AI) | 65.4% | 64.4% | DeepSeek V4 Pro 0813 |
| TaxEval (Vals AI) | 73.1% | 74.8% | GPT-5.6 Sol |
| MortgageTax (Vals AI) | Not measured | 67.3% | Only GPT-5.6 Sol measured |
| MedCode (Vals AI) | 42.5% | 44.0% | GPT-5.6 Sol |
| SimpleQA Verified | 52.9% | 69.7% | GPT-5.6 Sol |
| LMArena Text: science | 1457 | 1455 | DeepSeek V4 Pro 0813 |
| LMArena Text: medicine and healthcare | 1446 | 1431 | DeepSeek V4 Pro 0813 |
| LMArena Text: legal and government | 1459 | 1476 | GPT-5.6 Sol |
| LMArena Text: business and finance | 1442 | 1457 | GPT-5.6 Sol |
| FACTS Benchmark Suite | Not measured | 52.4% | Only GPT-5.6 Sol measured |
| Neither model has a result on the other 6 boards here | |||
Web designDirectional onlyPublic boards, shown as published, kept out of the index9 boards, none shared
| Benchmark | DeepSeek V4 Pro 0813 | GPT-5.6 Sol | Leader |
|---|---|---|---|
| Design Arena: websites | Not measured | 1321 | Only GPT-5.6 Sol measured |
| Design Arena: UI components | Not measured | 1335 | Only GPT-5.6 Sol measured |
| Design Arena: game dev | Not measured | 1367 | Only GPT-5.6 Sol measured |
| Design Arena: data viz | Not measured | 1322 | Only GPT-5.6 Sol measured |
| Design Arena: 3D | Not measured | 1384 | Only GPT-5.6 Sol measured |
| Design Arena: all code categories | Not measured | 1341 | Only GPT-5.6 Sol measured |
| Design Arena: SVG | Not measured | 1314 | Only GPT-5.6 Sol measured |
| Design Arena: ASCII art | Not measured | 1304 | Only GPT-5.6 Sol measured |
| LiveBench design | Not measured | 81.6% | Only GPT-5.6 Sol measured |
GeneralLike-for-likePublic boards, shown as published, kept out of the index117
| Benchmark | DeepSeek V4 Pro 0813 | GPT-5.6 Sol | Leader |
|---|---|---|---|
| Vals Index | 53.0% | Not measured | Only DeepSeek V4 Pro 0813 measured |
| LiveBench data analysis | Not measured | 79.8% | Only GPT-5.6 Sol measured |
| Public Benefits Bench (Vals AI) | Not measured | 66.5% | Only GPT-5.6 Sol measured |
| SAGE (Vals AI) | Not measured | 52.6% | Only GPT-5.6 Sol measured |
| MedScribe (Vals AI) | 80.2% | 85.2% | GPT-5.6 Sol |
| Vals Multimodal Index | Not measured | 72.6% | Only GPT-5.6 Sol measured |
| IFBench | Not measured | 72.7% | Only GPT-5.6 Sol measured |
| Long context reasoning (AA-LCR) | 80.3% | 84.0% | GPT-5.6 Sol |
| DTBench | 93.9% | 95.7% | GPT-5.6 Sol |
| LMCA | 45.5% | 58.5% | GPT-5.6 Sol |
| Surface Evolver Bench | Not measured | 93.1% | Only GPT-5.6 Sol measured |
| Furniture assembly | Not measured | 56.7% | Only GPT-5.6 Sol measured |
| LMArena Text | 1446 | 1457 | GPT-5.6 Sol |
| LMArena Text: instruction following | 1448 | 1483 | GPT-5.6 Sol |
| LMArena Text: creative writing | 1439 | 1449 | GPT-5.6 Sol |
| LMArena Vision | Not measured | 1281 | Only GPT-5.6 Sol measured |
| LMArena Text: English | 1457 | 1457 | GPT-5.6 Sol |
| LMArena Text: non-English | 1431 | 1451 | GPT-5.6 Sol |
| LMArena Text: Chinese | 1481 | 1525 | GPT-5.6 Sol |
| LMArena Text: German | Not measured | 1476 | Only GPT-5.6 Sol measured |
| LMArena Text: Japanese | Not measured | 1472 | Only GPT-5.6 Sol measured |
| LMArena Text: Korean | 1449 | 1442 | DeepSeek V4 Pro 0813 |
| LMArena Text: French | 1446 | 1472 | GPT-5.6 Sol |
| LMArena Text: Spanish | 1435 | 1443 | GPT-5.6 Sol |
| LMArena Text: Russian | 1448 | 1471 | GPT-5.6 Sol |
| LMArena Text: Polish | Not measured | 1459 | Only GPT-5.6 Sol measured |
| LMArena Text: multi-turn | 1454 | 1461 | GPT-5.6 Sol |
| LMArena Text: longer queries | 1458 | 1481 | GPT-5.6 Sol |
| LMArena Text: writing and language | 1443 | 1462 | GPT-5.6 Sol |
| LMArena Text: entertainment and media | 1424 | 1450 | GPT-5.6 Sol |
| LMArena Vision: English | Not measured | 1280 | Only GPT-5.6 Sol measured |
| LMArena Vision: Chinese | Not measured | 1313 | Only GPT-5.6 Sol measured |
| LMArena Vision: reading text | Not measured | 1290 | Only GPT-5.6 Sol measured |
| LMArena Vision: humor | Not measured | 1246 | Only GPT-5.6 Sol measured |
| LMArena Vision: creative writing | Not measured | 1283 | Only GPT-5.6 Sol measured |
| LMArena Document | Not measured | 1483 | Only GPT-5.6 Sol measured |
| Neither model has a result on the other 10 boards here | |||
Image generationNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
| Benchmark | DeepSeek V4 Pro 0813 | GPT-5.6 Sol | 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-5.6 Sol |
|---|---|---|
| Maker | DeepSeek | OpenAI |
| Weights | Open weights | No public weights listed |
| Released | August 12, 2026 | July 9, 2026 |
| Context window | 1.05M | 1.05M |
| Input $/Mtok | $0.66 | $4.00 |
| Output $/Mtok | $1.98 | $20.00 |
| Coding index | 56.1 | 73.5 |
| Independent measurements behind it | 5 | 6 |
| Cost per solved task | $0.10 | $1.20 |
| Source | OpenRouter listing | OpenRouter listing |
Questions
Is DeepSeek V4 Pro 0813 better than GPT-5.6 Sol for coding?
Pick GPT-5.6 Sol for coding: it scores 73.5 on the Vibe Coding Index against 56.1 for DeepSeek V4 Pro 0813. Pick DeepSeek V4 Pro 0813 for output tokens 10.1x cheaper ($1.98 vs $20.00 per million) and a lower cost per solved task ($0.10 against $1.20).
Which is cheaper, DeepSeek V4 Pro 0813 or GPT-5.6 Sol?
DeepSeek V4 Pro 0813 costs $0.66 per million input tokens and $1.98 per million output tokens; GPT-5.6 Sol costs $4.00 and $20.00. Per solved SWE-bench Verified task, DeepSeek V4 Pro 0813 costs $0.10 and GPT-5.6 Sol $1.20.
Which has the bigger context window, DeepSeek V4 Pro 0813 or GPT-5.6 Sol?
GPT-5.6 Sol, with 1.05M tokens against 1.05M.
How many benchmarks is the DeepSeek V4 Pro 0813 vs GPT-5.6 Sol comparison based on?
75 benchmarks have a result for both models as of October 22, 2026. DeepSeek V4 Pro 0813's coding index rests on 5 independent benchmarks and GPT-5.6 Sol's on 6. Where only one model has a result, the page says so instead of naming a winner.