DeepSeek V4 Flash Vision Exp vs GPT-5.6 Sol
GPT-5.6 Sol leads DeepSeek V4 Flash Vision Exp on the Artificial Analysis Intelligence Index, 47.0 to 34.8, and DeepSeek V4 Flash Vision Exp costs 15.2x less per output token ($1.32 vs $20.00 per million). Updated October 22, 2026; 14 benchmarks have a result for both.
vs boards won of 14 shared
DeepSeek V4 Flash Vision Exp or GPT-5.6 Sol: which to pick
Only GPT-5.6 Sol has a coding score, 73.5 on the Vibe Coding Index; DeepSeek V4 Flash Vision Exp has none, so the two cannot be ranked on coding.
Pick DeepSeek V4 Flash Vision Exp for output tokens 15.2x cheaper ($1.32 vs $20.00 per million) and work measured by LiveBench research, where it leads.
Model ADeepSeek V4 Flash Vision ExpDeepSeekNot benchmarked1 independent benchmarkNo cost per solved taskModel BGPT-5.6 SolOpenAI73.5/1006 independent benchmarks$1.20 per solved task
- Shared results
- 14
- DeepSeek V4 Flash Vision Exp only
- 0
- GPT-5.6 Sol only
- 125
- Like-for-like categories
- 6 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-5.6 Sol has a coding score, so no call is made.
One side not measured
Intelligence
AA Intelligence Index
GPT-5.6 Sol
GPT-5.6 Sol leads, 47.0 against 34.8.
Same board, both measured
Agentic work
AA Agentic Index
GPT-5.6 Sol
GPT-5.6 Sol leads, 50.2 against 47.5.
Same board, both measured
Reasoning
GPQA Diamond
No call
Only GPT-5.6 Sol has a GPQA Diamond result, 95.2%.
Directional only
Knowledge
MMLU Pro
No call
Only GPT-5.6 Sol has a MMLU Pro result, 89.1%.
Directional only
Web design
Design Arena: websites
No call
Only GPT-5.6 Sol has a Design Arena: websites result, 1321.
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 Flash Vision Exp
DeepSeek V4 Flash Vision Exp $0.0011, GPT-5.6 Sol $0.014 per turn.
List prices
Cost per solved task
One SWE-bench Verified task, solved
No call
Only GPT-5.6 Sol has the number, $1.20.
Directional only
At a glance
- Coding index
- DeepSeek V4 Flash Vision Exp not benchmarked, GPT-5.6 Sol 73.5 from 6 benchmarks.
- Widest category
- Coding, 24.2 points apart on average over 3 shared benchmarks.
- Widest single gap
- LiveBench coding: DeepSeek V4 Flash Vision Exp 37.6% against GPT-5.6 Sol 89.7%, 52.1 points apart on a 0 to 100 scale.
- Output price
- DeepSeek V4 Flash Vision Exp $1.32 against GPT-5.6 Sol $20.00 per million output tokens, 15.2x apart.
- Context window
- DeepSeek V4 Flash Vision Exp 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 Flash Vision Exp | Bars | GPT-5.6 Sol | Ties |
|---|---|---|---|---|
| Coding | 0 | 3 | ||
| Intelligence | 0 | 1 | ||
| Agentic work | 1 | 3 | ||
| Reasoning | 0 | 3 | ||
| Web design | 0 | 1 | ||
| General | 0 | 2 | ||
| All shared boards | 1 | 13 |
CodingLike-for-likeSix of these boards feed the Vibe Coding Index03
| Benchmark | DeepSeek V4 Flash Vision Exp | GPT-5.6 Sol | Leader |
|---|---|---|---|
| LiveBench coding | 37.6% | 89.7% | GPT-5.6 Sol |
| LMArena WebDev | Not measured | 1616 | Only GPT-5.6 Sol measured |
| AA Coding Index | 65.0 | 77.4 | GPT-5.6 Sol |
| LiveCodeBench (Vals AI) | Not measured | 82.6% | Only GPT-5.6 Sol measured |
| SWE-bench Verified (Vals AI) | Not measured | 96.2% | Only GPT-5.6 Sol measured |
| Terminal-Bench 4 (Vals AI) | Not measured | 37.9% | Only GPT-5.6 Sol measured |
| Vibe Code Bench (Vals AI) | Not measured | 80.5% | Only GPT-5.6 Sol measured |
| Code migration (Vals AI) | Not measured | 52.9% | Only GPT-5.6 Sol measured |
| ProgramBench (Vals AI) | Not measured | 1.5% | Only GPT-5.6 Sol measured |
| IOI (Vals AI) | Not measured | 91.2% | Only GPT-5.6 Sol measured |
| Terminal-Bench 2.1 (Vals AI) | Not measured | 85.8% | Only GPT-5.6 Sol measured |
| Vibe Code Bench 1-100 (Vals AI) | Not measured | 20.0% | Only GPT-5.6 Sol measured |
| SkillsBench (Vals AI) | Not measured | 54.1% | Only GPT-5.6 Sol measured |
| CyberBench (Vals AI) | Not measured | 76.3% | Only GPT-5.6 Sol measured |
| SciCode | 49.7% | 57.8% | GPT-5.6 Sol |
| Terminal-Bench Hard (Artificial Analysis run) | Not measured | 65.9% | Only GPT-5.6 Sol measured |
| FrontierCode | Not measured | 47.5% | Only GPT-5.6 Sol measured |
| FrontierSWE | Not measured | 32.2% | Only GPT-5.6 Sol measured |
| GSO-Bench | Not measured | 76.5% | Only GPT-5.6 Sol measured |
| WeirdML | Not measured | 88.8% | Only GPT-5.6 Sol measured |
| MirrorCode | Not measured | 20.0% | Only GPT-5.6 Sol measured |
| ALE-Bench | Not measured | 2176.9 | Only GPT-5.6 Sol measured |
| LMArena Text: coding | Not measured | 1496 | Only GPT-5.6 Sol measured |
| LMArena Text: software and IT | Not measured | 1489 | Only GPT-5.6 Sol measured |
| LMArena WebDev: React | Not measured | 1620 | Only GPT-5.6 Sol measured |
| LMArena WebDev: HTML | Not measured | 1618 | Only GPT-5.6 Sol measured |
| 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 index01
| Benchmark | DeepSeek V4 Flash Vision Exp | GPT-5.6 Sol | Leader |
|---|---|---|---|
| AA Intelligence Index | 34.8 | 47.0 | GPT-5.6 Sol |
| Epoch Capabilities Index | Not measured | 162.8 | Only GPT-5.6 Sol measured |
Agentic workLike-for-likePublic boards, shown as published, kept out of the index13
| Benchmark | DeepSeek V4 Flash Vision Exp | GPT-5.6 Sol | Leader |
|---|---|---|---|
| AA Agentic Index | 47.5 | 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 | 69.2% | 54.5% | DeepSeek V4 Flash Vision Exp |
| LiveBench browser | 64.0% | 88.0% | GPT-5.6 Sol |
| LiveBench long agentic | 39.0% | 48.5% | GPT-5.6 Sol |
| SREBench (Vals AI) | Not measured | 30.5% | Only GPT-5.6 Sol measured |
| Finance Agent (Vals AI) | Not measured | 53.8% | Only GPT-5.6 Sol measured |
| Tax Agent Bench (Vals AI) | Not measured | 31.1% | Only GPT-5.6 Sol measured |
| Legal Research Bench (Vals AI) | Not measured | 48.1% | Only GPT-5.6 Sol measured |
| Excel Modeling Benchmark (Vals AI) | Not measured | 72.3% | Only GPT-5.6 Sol measured |
| BioMysteryBench (Vals AI) | Not measured | 71.1% | Only GPT-5.6 Sol measured |
| Terminal-Bench-Science (Vals AI) | Not measured | 20.0% | Only GPT-5.6 Sol measured |
| 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 |
| 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 13 boards here | |||
ReasoningLike-for-likePublic boards, shown as published, kept out of the index03
| Benchmark | DeepSeek V4 Flash Vision Exp | GPT-5.6 Sol | Leader |
|---|---|---|---|
| GPQA Diamond | Not measured | 95.2% | Only GPT-5.6 Sol measured |
| LiveBench reasoning | 85.4% | 91.7% | GPT-5.6 Sol |
| 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) | 91.3% | 94.1% | GPT-5.6 Sol |
| Humanity's Last Exam (Artificial Analysis run) | 34.5% | 49.5% | GPT-5.6 Sol |
| GPQA Diamond (Epoch AI run) | Not measured | 93.5% | Only GPT-5.6 Sol measured |
| ARC-AGI | Not measured | 97.5% | Only GPT-5.6 Sol measured |
| ARC-AGI-2 | Not measured | 92.5% | Only GPT-5.6 Sol measured |
| SimpleBench | Not measured | 64.8% | Only GPT-5.6 Sol measured |
| Chess puzzles | Not measured | 59.0% | Only GPT-5.6 Sol measured |
| Mystery game puzzles | Not measured | 58.0% | Only GPT-5.6 Sol measured |
| EBR-bench | Not measured | 44.8% | Only GPT-5.6 Sol measured |
| LMArena Text: hard prompts | Not measured | 1483 | Only GPT-5.6 Sol measured |
| LMArena Text: expert | Not measured | 1517 | Only GPT-5.6 Sol measured |
| LMArena Text: hard prompts in English | Not measured | 1477 | Only GPT-5.6 Sol measured |
| 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 | |||
MathDirectional onlyPublic boards, shown as published, kept out of the index6 boards, none shared
| Benchmark | DeepSeek V4 Flash Vision Exp | GPT-5.6 Sol | Leader |
|---|---|---|---|
| OTIS Mock AIME | Not measured | 100.0% | Only GPT-5.6 Sol measured |
| FrontierMath, tiers 1 to 3 | Not measured | 89.1% | Only GPT-5.6 Sol measured |
| FrontierMath, tier 4 | Not measured | 82.9% | Only GPT-5.6 Sol measured |
| ProofBench | Not measured | 83.0% | Only GPT-5.6 Sol measured |
| LMArena Text: math | Not measured | 1473 | Only GPT-5.6 Sol measured |
| LMArena Text: mathematical work | Not measured | 1496 | Only GPT-5.6 Sol measured |
| Neither model has a result on the other 7 boards here | |||
KnowledgeDirectional onlyPublic boards, shown as published, kept out of the index12 boards, none shared
| Benchmark | DeepSeek V4 Flash Vision Exp | GPT-5.6 Sol | Leader |
|---|---|---|---|
| MMLU Pro | Not measured | 89.1% | Only GPT-5.6 Sol measured |
| LegalBench (Vals AI) | Not measured | 87.0% | Only GPT-5.6 Sol measured |
| CorpFin (Vals AI) | Not measured | 64.4% | Only GPT-5.6 Sol measured |
| TaxEval (Vals AI) | Not measured | 74.8% | Only GPT-5.6 Sol measured |
| MortgageTax (Vals AI) | Not measured | 67.3% | Only GPT-5.6 Sol measured |
| MedCode (Vals AI) | Not measured | 44.0% | Only GPT-5.6 Sol measured |
| SimpleQA Verified | Not measured | 69.7% | Only GPT-5.6 Sol measured |
| LMArena Text: science | Not measured | 1455 | Only GPT-5.6 Sol measured |
| LMArena Text: medicine and healthcare | Not measured | 1431 | Only GPT-5.6 Sol measured |
| LMArena Text: legal and government | Not measured | 1476 | Only GPT-5.6 Sol measured |
| LMArena Text: business and finance | Not measured | 1457 | Only GPT-5.6 Sol measured |
| 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 designLike-for-likePublic boards, shown as published, kept out of the index01
| Benchmark | DeepSeek V4 Flash Vision Exp | 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 | 70.7% | 81.6% | GPT-5.6 Sol |
GeneralLike-for-likePublic boards, shown as published, kept out of the index02
| Benchmark | DeepSeek V4 Flash Vision Exp | GPT-5.6 Sol | Leader |
|---|---|---|---|
| LiveBench data analysis | 79.5% | 79.8% | GPT-5.6 Sol |
| 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) | Not measured | 85.2% | Only GPT-5.6 Sol measured |
| 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) | 81.3% | 84.0% | GPT-5.6 Sol |
| DTBench | Not measured | 95.7% | Only GPT-5.6 Sol measured |
| LMCA | Not measured | 58.5% | Only GPT-5.6 Sol measured |
| 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 | Not measured | 1457 | Only GPT-5.6 Sol measured |
| LMArena Text: instruction following | Not measured | 1483 | Only GPT-5.6 Sol measured |
| LMArena Text: creative writing | Not measured | 1449 | Only GPT-5.6 Sol measured |
| LMArena Vision | Not measured | 1281 | Only GPT-5.6 Sol measured |
| LMArena Text: English | Not measured | 1457 | Only GPT-5.6 Sol measured |
| LMArena Text: non-English | Not measured | 1451 | Only GPT-5.6 Sol measured |
| LMArena Text: Chinese | Not measured | 1525 | Only GPT-5.6 Sol measured |
| 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 | Not measured | 1442 | Only GPT-5.6 Sol measured |
| LMArena Text: French | Not measured | 1472 | Only GPT-5.6 Sol measured |
| LMArena Text: Spanish | Not measured | 1443 | Only GPT-5.6 Sol measured |
| LMArena Text: Russian | Not measured | 1471 | Only GPT-5.6 Sol measured |
| LMArena Text: Polish | Not measured | 1459 | Only GPT-5.6 Sol measured |
| LMArena Text: multi-turn | Not measured | 1461 | Only GPT-5.6 Sol measured |
| LMArena Text: longer queries | Not measured | 1481 | Only GPT-5.6 Sol measured |
| LMArena Text: writing and language | Not measured | 1462 | Only GPT-5.6 Sol measured |
| LMArena Text: entertainment and media | Not measured | 1450 | Only GPT-5.6 Sol measured |
| 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 11 boards here | |||
Image generationNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
| Benchmark | DeepSeek V4 Flash Vision Exp | 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 Flash Vision Exp$0.0011Fits in one request
GPT-5.6 Sol$0.014Fits in one request
DeepSeek V4 Flash Vision Exp costs less
Repository review
50K input + 3K output tokens
DeepSeek V4 Flash Vision Exp$0.026Fits in one request
GPT-5.6 Sol$0.260Fits in one request
DeepSeek V4 Flash Vision Exp costs less
Agent loop
200K input + 10K output tokens
DeepSeek V4 Flash Vision Exp$0.101Fits in one request
GPT-5.6 Sol$1.00Fits in one request
DeepSeek V4 Flash Vision Exp 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 Flash Vision Exp | OpenAI GPT-5.6 Sol |
|---|---|---|
| Maker | DeepSeek | OpenAI |
| Weights | Open weights | No public weights listed |
| Released | August 21, 2026 | July 9, 2026 |
| Context window | 1.05M | 1.05M |
| Input $/Mtok | $0.44 | $4.00 |
| Output $/Mtok | $1.32 | $20.00 |
| Coding index | Not benchmarked | 73.5 |
| Independent measurements behind it | 1 | 6 |
| Cost per solved task | Not computable | $1.20 |
| Source | OpenRouter listing | OpenRouter listing |
Questions
Is DeepSeek V4 Flash Vision Exp better than GPT-5.6 Sol for coding?
Only GPT-5.6 Sol has a coding score, 73.5 on the Vibe Coding Index; DeepSeek V4 Flash Vision Exp has none, so the two cannot be ranked on coding. Pick DeepSeek V4 Flash Vision Exp for output tokens 15.2x cheaper ($1.32 vs $20.00 per million) and work measured by LiveBench research, where it leads.
Which is cheaper, DeepSeek V4 Flash Vision Exp or GPT-5.6 Sol?
DeepSeek V4 Flash Vision Exp costs $0.44 per million input tokens and $1.32 per million output tokens; GPT-5.6 Sol costs $4.00 and $20.00. Cost per solved task is known for GPT-5.6 Sol only.
Which has the bigger context window, DeepSeek V4 Flash Vision Exp or GPT-5.6 Sol?
GPT-5.6 Sol, with 1.05M tokens against 1.05M.
How many benchmarks is the DeepSeek V4 Flash Vision Exp vs GPT-5.6 Sol comparison based on?
14 benchmarks have a result for both models as of October 22, 2026. DeepSeek V4 Flash Vision Exp's coding index rests on 1 independent benchmark and GPT-5.6 Sol's on 6. Where only one model has a result, the page says so instead of naming a winner.