DeepSeek V3.1 vs GPT-6 Sol
GPT-6 Sol leads DeepSeek V3.1 on the Artificial Analysis Intelligence Index, 47.6 to 13.7, and DeepSeek V3.1 costs 6.7x less per output token ($1.50 vs $10.00 per million). Updated October 21, 2026; 10 benchmarks have a result for both.
DeepSeek V3.1 or GPT-6 Sol: which to pick
Only GPT-6 Sol has a coding score, 76.0 on the Vibe Coding Index; DeepSeek V3.1 has none, so the two cannot be ranked on coding.
Pick DeepSeek V3.1 for output tokens 6.7x cheaper ($1.50 vs $10.00 per million).
- Shared results
- 10
- DeepSeek V3.1 only
- 1
- GPT-6 Sol only
- 91
- Like-for-like categories
- 3 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
No call
Only GPT-6 Sol has a coding score, so no call is made.
One side not measured
Intelligence
AA Intelligence Index
GPT-6 Sol
GPT-6 Sol leads, 47.6 against 13.7.
Same board, both measured
Web design
Design Arena: websites
GPT-6 Sol
GPT-6 Sol leads, 1292 against 1123.
Same board, both measured
Long documents
Listed context window
GPT-6 Sol
GPT-6 Sol takes 1.05M tokens against 164K.
Listed by OpenRouter
Everyday cost
1K input + 500 output tokens
DeepSeek V3.1
DeepSeek V3.1 $0.0013, GPT-6 Sol $0.0070 per turn.
List prices
At a glance
- Coding index
- DeepSeek V3.1 not benchmarked, GPT-6 Sol 76.0 from 5 benchmarks.
- Widest category
- Intelligence, 33.9 points apart on average over 1 shared benchmark.
- Widest single gap
- Design Arena: SVG: DeepSeek V3.1 967 against GPT-6 Sol 1316, 43.6 points apart on a 0 to 100 scale.
- Output price
- DeepSeek V3.1 $1.50 against GPT-6 Sol $10.00 per million output tokens, 6.7x apart.
- Context window
- DeepSeek V3.1 takes 164K tokens, GPT-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 V3.1 | Bars | GPT-6 Sol | Ties |
|---|---|---|---|---|
| Intelligence | 0 | 1 | ||
| Web design | 0 | 7 | ||
| General | 0 | 2 | ||
| All shared boards | 0 | 10 |
CodingDirectional onlySix of these boards feed the Vibe Coding Index17 boards, none shared
| Benchmark | DeepSeek V3.1 | GPT-6 Sol | Leader |
|---|---|---|---|
| LiveBench coding | Not measured | 93.1% | Only GPT-6 Sol measured |
| LMArena WebDev | Not measured | 1683 | Only GPT-6 Sol measured |
| Terminal-Bench 4 (Vals AI) | Not measured | 44.4% | Only GPT-6 Sol measured |
| Vibe Code Bench (Vals AI) | Not measured | 87.8% | Only GPT-6 Sol measured |
| Code migration (Vals AI) | Not measured | 57.2% | Only GPT-6 Sol measured |
| ProgramBench (Vals AI) | Not measured | 2.0% | Only GPT-6 Sol measured |
| IOI (Vals AI) | Not measured | 82.6% | Only GPT-6 Sol measured |
| Terminal-Bench 2.1 (Vals AI) | Not measured | 83.2% | Only GPT-6 Sol measured |
| CyberBench (Vals AI) | Not measured | 78.0% | Only GPT-6 Sol measured |
| SciCode | Not measured | 57.6% | Only GPT-6 Sol measured |
| FrontierCode | Not measured | 49.3% | Only GPT-6 Sol measured |
| ALE-Bench | Not measured | 2462.0 | Only GPT-6 Sol measured |
| LMArena Text: coding | Not measured | 1448 | Only GPT-6 Sol measured |
| LMArena Text: software and IT | Not measured | 1433 | Only GPT-6 Sol measured |
| LMArena WebDev: React | Not measured | 1685 | Only GPT-6 Sol measured |
| LMArena WebDev: HTML | Not measured | 1685 | Only GPT-6 Sol measured |
| LMArena WebDev: from an image | Not measured | 1660 | Only GPT-6 Sol measured |
| Neither model has a result on the other 22 boards here | |||
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index01
| Benchmark | DeepSeek V3.1 | GPT-6 Sol | Leader |
|---|---|---|---|
| AA Intelligence Index | 13.7 | 47.6 | GPT-6 Sol |
| Epoch Capabilities Index | Not measured | 163.7 | Only GPT-6 Sol measured |
Agentic workDirectional onlyPublic boards, shown as published, kept out of the index17 boards, none shared
| Benchmark | DeepSeek V3.1 | GPT-6 Sol | Leader |
|---|---|---|---|
| Design Arena: agents building web apps | Not measured | 1231 | Only GPT-6 Sol measured |
| Design Arena: agents building full-stack apps | Not measured | 1238 | Only GPT-6 Sol measured |
| Design Arena: agents building mobile apps | Not measured | 1214 | Only GPT-6 Sol measured |
| LiveBench research | Not measured | 69.3% | Only GPT-6 Sol measured |
| LiveBench browser | Not measured | 92.0% | Only GPT-6 Sol measured |
| LiveBench long agentic | Not measured | 66.9% | Only GPT-6 Sol measured |
| SREBench (Vals AI) | Not measured | 30.5% | Only GPT-6 Sol measured |
| Finance Agent (Vals AI) | Not measured | 49.0% | Only GPT-6 Sol measured |
| Tax Agent Bench (Vals AI) | Not measured | 15.0% | Only GPT-6 Sol measured |
| Legal Research Bench (Vals AI) | Not measured | 28.9% | Only GPT-6 Sol measured |
| Excel Modeling Benchmark (Vals AI) | Not measured | 71.5% | Only GPT-6 Sol measured |
| BioMysteryBench (Vals AI) | Not measured | 74.8% | Only GPT-6 Sol measured |
| Terminal-Bench-Science (Vals AI) | Not measured | 30.0% | Only GPT-6 Sol measured |
| Vals Science Index | Not measured | 45.0% | Only GPT-6 Sol measured |
| APEX-Agents | Not measured | 54.3% | Only GPT-6 Sol measured |
| SpireClimb | Not measured | 7.5% | Only GPT-6 Sol measured |
| Vending-Bench 2 | Not measured | $14,428 | Only GPT-6 Sol measured |
| Neither model has a result on the other 24 boards here | |||
ReasoningDirectional onlyPublic boards, shown as published, kept out of the index15 boards, none shared
| Benchmark | DeepSeek V3.1 | GPT-6 Sol | Leader |
|---|---|---|---|
| LiveBench reasoning | Not measured | 88.7% | Only GPT-6 Sol measured |
| MysteryMechanism (Vals AI) | Not measured | 30.2% | Only GPT-6 Sol measured |
| Humanity's Last Exam (Artificial Analysis run) | Not measured | 47.9% | Only GPT-6 Sol measured |
| GPQA Diamond (Epoch AI run) | Not measured | 94.3% | Only GPT-6 Sol measured |
| ARC-AGI | Not measured | 95.5% | Only GPT-6 Sol measured |
| ARC-AGI-2 | Not measured | 89.6% | Only GPT-6 Sol measured |
| Chess puzzles | Not measured | 56.0% | Only GPT-6 Sol measured |
| Mystery game puzzles | Not measured | 56.0% | Only GPT-6 Sol measured |
| EBR-bench | Not measured | 53.3% | Only GPT-6 Sol measured |
| LMArena Text: hard prompts | Not measured | 1422 | Only GPT-6 Sol measured |
| LMArena Text: expert | Not measured | 1437 | Only GPT-6 Sol measured |
| LMArena Text: hard prompts in English | Not measured | 1420 | Only GPT-6 Sol measured |
| LMArena Vision: diagrams | Not measured | 1270 | Only GPT-6 Sol measured |
| LMArena Vision: homework | Not measured | 1286 | Only GPT-6 Sol measured |
| Kagi LLM Benchmark | 53.2% | Not measured | Only DeepSeek V3.1 measured |
| Neither model has a result on the other 7 boards here | |||
MathDirectional onlyPublic boards, shown as published, kept out of the index6 boards, none shared
| Benchmark | DeepSeek V3.1 | GPT-6 Sol | Leader |
|---|---|---|---|
| OTIS Mock AIME | Not measured | 100.0% | Only GPT-6 Sol measured |
| FrontierMath, tiers 1 to 3 | Not measured | 89.8% | Only GPT-6 Sol measured |
| FrontierMath, tier 4 | Not measured | 90.0% | Only GPT-6 Sol measured |
| ProofBench | Not measured | 83.0% | Only GPT-6 Sol measured |
| LMArena Text: math | Not measured | 1407 | Only GPT-6 Sol measured |
| LMArena Text: mathematical work | Not measured | 1424 | Only GPT-6 Sol measured |
| Neither model has a result on the other 7 boards here | |||
KnowledgeDirectional onlyPublic boards, shown as published, kept out of the index7 boards, none shared
| Benchmark | DeepSeek V3.1 | GPT-6 Sol | Leader |
|---|---|---|---|
| MedCode (Vals AI) | Not measured | 47.1% | Only GPT-6 Sol measured |
| SimpleQA Verified | Not measured | 60.7% | Only GPT-6 Sol measured |
| LMArena Text: science | Not measured | 1389 | Only GPT-6 Sol measured |
| LMArena Text: medicine and healthcare | Not measured | 1366 | Only GPT-6 Sol measured |
| LMArena Text: legal and government | Not measured | 1396 | Only GPT-6 Sol measured |
| LMArena Text: business and finance | Not measured | 1380 | Only GPT-6 Sol measured |
| FACTS Benchmark Suite | Not measured | 72.5% | Only GPT-6 Sol measured |
| Neither model has a result on the other 11 boards here | |||
Web designLike-for-likePublic boards, shown as published, kept out of the index07
| Benchmark | DeepSeek V3.1 | GPT-6 Sol | Leader |
|---|---|---|---|
| Design Arena: websites | 1123 | 1292 | GPT-6 Sol |
| Design Arena: UI components | 1085 | 1292 | GPT-6 Sol |
| Design Arena: game dev | 1084 | 1314 | GPT-6 Sol |
| Design Arena: data viz | 1095 | 1269 | GPT-6 Sol |
| Design Arena: 3D | 1077 | 1318 | GPT-6 Sol |
| Design Arena: all code categories | 1112 | 1301 | GPT-6 Sol |
| Design Arena: SVG | 967 | 1316 | GPT-6 Sol |
| Design Arena: ASCII art | Not measured | 1225 | Only GPT-6 Sol measured |
| LiveBench design | Not measured | 82.2% | Only GPT-6 Sol measured |
GeneralLike-for-likePublic boards, shown as published, kept out of the index02
| Benchmark | DeepSeek V3.1 | GPT-6 Sol | Leader |
|---|---|---|---|
| LiveBench data analysis | Not measured | 81.2% | Only GPT-6 Sol measured |
| Public Benefits Bench (Vals AI) | Not measured | 56.6% | Only GPT-6 Sol measured |
| SAGE (Vals AI) | Not measured | 44.8% | Only GPT-6 Sol measured |
| MedScribe (Vals AI) | Not measured | 82.0% | Only GPT-6 Sol measured |
| Long context reasoning (AA-LCR) | Not measured | 83.7% | Only GPT-6 Sol measured |
| DTBench | 82.7% | 97.3% | GPT-6 Sol |
| LMCA | 24.3% | 59.1% | GPT-6 Sol |
| Furniture assembly | Not measured | 58.3% | Only GPT-6 Sol measured |
| LMArena Text | Not measured | 1398 | Only GPT-6 Sol measured |
| LMArena Text: instruction following | Not measured | 1413 | Only GPT-6 Sol measured |
| LMArena Text: creative writing | Not measured | 1378 | Only GPT-6 Sol measured |
| LMArena Vision | Not measured | 1240 | Only GPT-6 Sol measured |
| LMArena Text: English | Not measured | 1396 | Only GPT-6 Sol measured |
| LMArena Text: non-English | Not measured | 1388 | Only GPT-6 Sol measured |
| LMArena Text: Chinese | Not measured | 1412 | Only GPT-6 Sol measured |
| LMArena Text: German | Not measured | 1379 | Only GPT-6 Sol measured |
| LMArena Text: Japanese | Not measured | 1377 | Only GPT-6 Sol measured |
| LMArena Text: Korean | Not measured | 1336 | Only GPT-6 Sol measured |
| LMArena Text: French | Not measured | 1399 | Only GPT-6 Sol measured |
| LMArena Text: Spanish | Not measured | 1387 | Only GPT-6 Sol measured |
| LMArena Text: Russian | Not measured | 1402 | Only GPT-6 Sol measured |
| LMArena Text: Polish | Not measured | 1372 | Only GPT-6 Sol measured |
| LMArena Text: multi-turn | Not measured | 1414 | Only GPT-6 Sol measured |
| LMArena Text: longer queries | Not measured | 1416 | Only GPT-6 Sol measured |
| LMArena Text: writing and language | Not measured | 1389 | Only GPT-6 Sol measured |
| LMArena Text: entertainment and media | Not measured | 1373 | Only GPT-6 Sol measured |
| LMArena Vision: English | Not measured | 1229 | Only GPT-6 Sol measured |
| LMArena Vision: reading text | Not measured | 1258 | Only GPT-6 Sol measured |
| LMArena Vision: creative writing | Not measured | 1219 | Only GPT-6 Sol measured |
| Neither model has a result on the other 17 boards here | |||
Image generationNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
| Benchmark | DeepSeek V3.1 | GPT-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 V3.1 costs less
Repository review
50K input + 3K output tokens
DeepSeek V3.1 costs less
Agent loop
200K input + 10K output tokens
DeepSeek V3.1 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 V3.1 | OpenAI GPT-6 Sol |
|---|---|---|
| Maker | DeepSeek | OpenAI |
| Weights | Open weights | No public weights listed |
| Released | August 21, 2025 | September 22, 2026 |
| Context window | 164K | 1.05M |
| Input $/Mtok | $0.55 | $2.00 |
| Output $/Mtok | $1.50 | $10.00 |
| Coding index | Not benchmarked | 76.0 |
| Independent measurements behind it | 0 | 5 |
| Cost per solved task | Not computable | Not computable |
| Source | OpenRouter listing | OpenRouter listing |
Questions
Is DeepSeek V3.1 better than GPT-6 Sol for coding?
Only GPT-6 Sol has a coding score, 76.0 on the Vibe Coding Index; DeepSeek V3.1 has none, so the two cannot be ranked on coding. Pick DeepSeek V3.1 for output tokens 6.7x cheaper ($1.50 vs $10.00 per million).
Which is cheaper, DeepSeek V3.1 or GPT-6 Sol?
DeepSeek V3.1 costs $0.55 per million input tokens and $1.50 per million output tokens; GPT-6 Sol costs $2.00 and $10.00. Cost per solved task is known for neither of them.
Which has the bigger context window, DeepSeek V3.1 or GPT-6 Sol?
GPT-6 Sol, with 1.05M tokens against 164K.
How many benchmarks is the DeepSeek V3.1 vs GPT-6 Sol comparison based on?
10 benchmarks have a result for both models as of October 21, 2026. DeepSeek V3.1's coding index rests on 0 independent benchmarks and GPT-6 Sol's on 5. Where only one model has a result, the page says so instead of naming a winner.