DeepSeek V4 Flash Vision Exp vs GPT-5.6 Terra
Updated October 21, 2026. 14 benchmarks have a result for both. Coding is ranked on the Vibe Coding Index; every other board is shown as published.
vs boards won of 14 shared
Decision reading
Pick GPT-5.6 Terra for coding: it scores 69.0 on the Vibe Coding Index against 37.6 for DeepSeek V4 Flash Vision Exp.
Pick DeepSeek V4 Flash Vision Exp when output tokens cost 18.6x less, or when what matters is AA Agentic Index or LiveBench research, where it leads.
Model ADeepSeek V4 Flash Vision ExpDeepSeek37.6/1001 independent benchmarkNo cost per solved taskModel BGPT-5.6 TerraOpenAI69.0/1002 independent benchmarks$0.42 per solved task
- Shared results
- 14
- DeepSeek V4 Flash Vision Exp only
- 0
- GPT-5.6 Terra only
- 110
- 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-5.6 Terra
GPT-5.6 Terra scores 69.0 against 37.6.
1 and 2 benchmarks behind the scores
Intelligence
AA Intelligence Index
GPT-5.6 Terra
GPT-5.6 Terra leads, 42.1 against 34.8.
Same board, both measured
Agentic work
AA Agentic Index
DeepSeek V4 Flash Vision Exp
DeepSeek V4 Flash Vision Exp leads, 47.5 against 43.2.
Same board, both measured
Reasoning
GPQA Diamond
No call
Only GPT-5.6 Terra has a GPQA Diamond result, 90.9%.
Directional only
Knowledge
MMLU Pro
No call
Only GPT-5.6 Terra has a MMLU Pro result, 86.7%.
Directional only
Web design
Design Arena: websites
No call
Only GPT-5.6 Terra has a Design Arena: websites result, 1269.
Directional only
Long documents
Listed context window
GPT-5.6 Terra
GPT-5.6 Terra 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 $0.0005, GPT-5.6 Terra $0.0080 per turn.
List prices
Cost per solved task
One SWE-bench Verified task, solved
No call
Only GPT-5.6 Terra has the number, $0.42.
Directional only
At a glance
- Coding index
- DeepSeek V4 Flash Vision Exp 37.6 from 1 benchmark, GPT-5.6 Terra 69.0 from 2 benchmarks.
- Widest category
- Coding, 21.9 points apart on average over 3 shared benchmarks.
- Widest single gap
- LiveBench coding: DeepSeek V4 Flash Vision Exp 37.6% against GPT-5.6 Terra 86.2%, 48.6 points apart on a 0 to 100 scale.
- Output price
- DeepSeek V4 Flash Vision Exp $0.6468 against GPT-5.6 Terra $12.00 per million output tokens, 18.6x apart.
- Context window
- DeepSeek V4 Flash Vision Exp takes 1.05M tokens, GPT-5.6 Terra 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 Terra | Ties |
|---|---|---|---|---|
| Coding | 0 | 3 | ||
| Intelligence | 0 | 1 | ||
| Agentic work | 2 | 2 | ||
| Reasoning | 0 | 3 | ||
| Web design | 0 | 1 | ||
| General | 1 | 1 | ||
| All shared boards | 3 | 11 |
CodingLike-for-likeFour of these boards feed the Vibe Coding Index03
| Benchmark | DeepSeek V4 Flash Vision Exp | GPT-5.6 Terra | Leader |
|---|---|---|---|
| LiveBench coding | 37.6% | 86.2% | GPT-5.6 Terra |
| LMArena WebDev | Not measured | 1522 | Only GPT-5.6 Terra measured |
| AA Coding Index | 65.0 | 76.7 | GPT-5.6 Terra |
| LiveCodeBench (Vals AI) | Not measured | 85.9% | Only GPT-5.6 Terra measured |
| SWE-bench Verified (Vals AI) | Not measured | 95.4% | Only GPT-5.6 Terra measured |
| Terminal-Bench 4 (Vals AI) | Not measured | 22.7% | Only GPT-5.6 Terra measured |
| Vibe Code Bench (Vals AI) | Not measured | 74.6% | Only GPT-5.6 Terra measured |
| Code migration (Vals AI) | Not measured | 47.8% | Only GPT-5.6 Terra measured |
| ProgramBench (Vals AI) | Not measured | 0.5% | Only GPT-5.6 Terra measured |
| IOI (Vals AI) | Not measured | 87.6% | Only GPT-5.6 Terra measured |
| Terminal-Bench 2.1 (Vals AI) | Not measured | 77.5% | Only GPT-5.6 Terra measured |
| Vibe Code Bench 1-100 (Vals AI) | Not measured | 14.8% | Only GPT-5.6 Terra measured |
| SkillsBench (Vals AI) | Not measured | 58.9% | Only GPT-5.6 Terra measured |
| CyberBench (Vals AI) | Not measured | 72.1% | Only GPT-5.6 Terra measured |
| SciCode | 49.7% | 55.0% | GPT-5.6 Terra |
| Terminal-Bench Hard (Artificial Analysis run) | Not measured | 62.9% | Only GPT-5.6 Terra measured |
| FrontierCode | Not measured | 41.3% | Only GPT-5.6 Terra measured |
| WeirdML | Not measured | 78.3% | Only GPT-5.6 Terra measured |
| ALE-Bench | Not measured | 1951.4 | Only GPT-5.6 Terra measured |
| LMArena Text: coding | Not measured | 1485 | Only GPT-5.6 Terra measured |
| LMArena Text: software and IT | Not measured | 1482 | Only GPT-5.6 Terra measured |
| LMArena WebDev: React | Not measured | 1513 | Only GPT-5.6 Terra measured |
| LMArena WebDev: HTML | Not measured | 1526 | Only GPT-5.6 Terra measured |
| LMArena WebDev: from an image | Not measured | 1541 | Only GPT-5.6 Terra measured |
| Neither model has a result on the other 14 boards here | |||
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index01
| Benchmark | DeepSeek V4 Flash Vision Exp | GPT-5.6 Terra | Leader |
|---|---|---|---|
| AA Intelligence Index | 34.8 | 42.1 | GPT-5.6 Terra |
| Epoch Capabilities Index | Not measured | 160.1 | Only GPT-5.6 Terra measured |
Agentic workLike-for-likePublic boards, shown as published, kept out of the index22
| Benchmark | DeepSeek V4 Flash Vision Exp | GPT-5.6 Terra | Leader |
|---|---|---|---|
| AA Agentic Index | 47.5 | 43.2 | DeepSeek V4 Flash Vision Exp |
| Design Arena: agents building web apps | Not measured | 1120 | Only GPT-5.6 Terra measured |
| Design Arena: agents building full-stack apps | Not measured | 1061 | Only GPT-5.6 Terra measured |
| Design Arena: agents building mobile apps | Not measured | 1112 | Only GPT-5.6 Terra measured |
| Design Arena: agents building Android apps | Not measured | 1066 | Only GPT-5.6 Terra measured |
| Design Arena: agents building games | Not measured | 1082 | Only GPT-5.6 Terra measured |
| Design Arena: HTML slides | Not measured | 1108 | Only GPT-5.6 Terra measured |
| Design Arena: PowerPoint slides | Not measured | 1130 | Only GPT-5.6 Terra measured |
| LiveBench research | 69.2% | 60.4% | DeepSeek V4 Flash Vision Exp |
| LiveBench browser | 64.0% | 84.0% | GPT-5.6 Terra |
| LiveBench long agentic | 39.0% | 48.4% | GPT-5.6 Terra |
| SREBench (Vals AI) | Not measured | 9.5% | Only GPT-5.6 Terra measured |
| Finance Agent (Vals AI) | Not measured | 54.4% | Only GPT-5.6 Terra measured |
| Tax Agent Bench (Vals AI) | Not measured | 30.0% | Only GPT-5.6 Terra measured |
| Legal Research Bench (Vals AI) | Not measured | 41.4% | Only GPT-5.6 Terra measured |
| Excel Modeling Benchmark (Vals AI) | Not measured | 66.2% | Only GPT-5.6 Terra measured |
| Terminal-Bench-Science (Vals AI) | Not measured | 10.0% | Only GPT-5.6 Terra measured |
| τ²-Bench Telecom | Not measured | 86.3% | Only GPT-5.6 Terra measured |
| APEX-Agents | Not measured | 58.2% | Only GPT-5.6 Terra measured |
| BALROG | Not measured | 53.2% | Only GPT-5.6 Terra measured |
| Vending-Bench 2 | Not measured | $7,343 | Only GPT-5.6 Terra measured |
| Neither model has a result on the other 18 boards here | |||
ReasoningLike-for-likePublic boards, shown as published, kept out of the index03
| Benchmark | DeepSeek V4 Flash Vision Exp | GPT-5.6 Terra | Leader |
|---|---|---|---|
| GPQA Diamond | Not measured | 90.9% | Only GPT-5.6 Terra measured |
| LiveBench reasoning | 85.4% | 90.6% | GPT-5.6 Terra |
| MMMU Pro (Vals AI) | Not measured | 86.5% | Only GPT-5.6 Terra measured |
| GPQA Diamond (Artificial Analysis run) | 91.3% | 92.5% | GPT-5.6 Terra |
| Humanity's Last Exam (Artificial Analysis run) | 34.5% | 42.9% | GPT-5.6 Terra |
| GPQA Diamond (Epoch AI run) | Not measured | 93.3% | Only GPT-5.6 Terra measured |
| ARC-AGI | Not measured | 96.5% | Only GPT-5.6 Terra measured |
| ARC-AGI-2 | Not measured | 83.9% | Only GPT-5.6 Terra measured |
| SimpleBench | Not measured | 48.9% | Only GPT-5.6 Terra measured |
| Chess puzzles | Not measured | 47.0% | Only GPT-5.6 Terra measured |
| Mystery game puzzles | Not measured | 35.0% | Only GPT-5.6 Terra measured |
| LMArena Text: hard prompts | Not measured | 1469 | Only GPT-5.6 Terra measured |
| LMArena Text: expert | Not measured | 1496 | Only GPT-5.6 Terra measured |
| LMArena Text: hard prompts in English | Not measured | 1465 | Only GPT-5.6 Terra measured |
| LMArena Vision: diagrams | Not measured | 1295 | Only GPT-5.6 Terra measured |
| LMArena Vision: homework | Not measured | 1312 | Only GPT-5.6 Terra measured |
| Neither model has a result on the other 5 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 Terra | Leader |
|---|---|---|---|
| OTIS Mock AIME | Not measured | 99.7% | Only GPT-5.6 Terra measured |
| FrontierMath, tiers 1 to 3 | Not measured | 86.0% | Only GPT-5.6 Terra measured |
| FrontierMath, tier 4 | Not measured | 70.7% | Only GPT-5.6 Terra measured |
| ProofBench | Not measured | 74.0% | Only GPT-5.6 Terra measured |
| LMArena Text: math | Not measured | 1465 | Only GPT-5.6 Terra measured |
| LMArena Text: mathematical work | Not measured | 1478 | Only GPT-5.6 Terra measured |
| Neither model has a result on the other 7 boards here | |||
KnowledgeDirectional onlyPublic boards, shown as published, kept out of the index11 boards, none shared
| Benchmark | DeepSeek V4 Flash Vision Exp | GPT-5.6 Terra | Leader |
|---|---|---|---|
| MMLU Pro | Not measured | 86.7% | Only GPT-5.6 Terra measured |
| LegalBench (Vals AI) | Not measured | 85.1% | Only GPT-5.6 Terra measured |
| CorpFin (Vals AI) | Not measured | 65.3% | Only GPT-5.6 Terra measured |
| TaxEval (Vals AI) | Not measured | 76.2% | Only GPT-5.6 Terra measured |
| MortgageTax (Vals AI) | Not measured | 67.3% | Only GPT-5.6 Terra measured |
| MedCode (Vals AI) | Not measured | 43.4% | Only GPT-5.6 Terra measured |
| SimpleQA Verified | Not measured | 43.2% | Only GPT-5.6 Terra measured |
| LMArena Text: science | Not measured | 1452 | Only GPT-5.6 Terra measured |
| LMArena Text: medicine and healthcare | Not measured | 1430 | Only GPT-5.6 Terra measured |
| LMArena Text: legal and government | Not measured | 1461 | Only GPT-5.6 Terra measured |
| LMArena Text: business and finance | Not measured | 1448 | Only GPT-5.6 Terra 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 Terra | Leader |
|---|---|---|---|
| Design Arena: websites | Not measured | 1269 | Only GPT-5.6 Terra measured |
| Design Arena: UI components | Not measured | 1259 | Only GPT-5.6 Terra measured |
| Design Arena: game dev | Not measured | 1230 | Only GPT-5.6 Terra measured |
| Design Arena: data viz | Not measured | 1240 | Only GPT-5.6 Terra measured |
| Design Arena: 3D | Not measured | 1135 | Only GPT-5.6 Terra measured |
| Design Arena: all code categories | Not measured | 1241 | Only GPT-5.6 Terra measured |
| Design Arena: SVG | Not measured | 1220 | Only GPT-5.6 Terra measured |
| Design Arena: ASCII art | Not measured | 1177 | Only GPT-5.6 Terra measured |
| LiveBench design | 70.7% | 76.0% | GPT-5.6 Terra |
GeneralLike-for-likePublic boards, shown as published, kept out of the index11
| Benchmark | DeepSeek V4 Flash Vision Exp | GPT-5.6 Terra | Leader |
|---|---|---|---|
| LiveBench data analysis | 79.5% | 79.3% | DeepSeek V4 Flash Vision Exp |
| Public Benefits Bench (Vals AI) | Not measured | 62.4% | Only GPT-5.6 Terra measured |
| SAGE (Vals AI) | Not measured | 47.0% | Only GPT-5.6 Terra measured |
| MedScribe (Vals AI) | Not measured | 82.9% | Only GPT-5.6 Terra measured |
| Vals Multimodal Index | Not measured | 65.1% | Only GPT-5.6 Terra measured |
| IFBench | Not measured | 71.2% | Only GPT-5.6 Terra measured |
| Long context reasoning (AA-LCR) | 81.3% | 83.0% | GPT-5.6 Terra |
| DTBench | Not measured | 93.3% | Only GPT-5.6 Terra measured |
| LMCA | Not measured | 54.9% | Only GPT-5.6 Terra measured |
| Surface Evolver Bench | Not measured | 83.8% | Only GPT-5.6 Terra measured |
| Furniture assembly | Not measured | 54.2% | Only GPT-5.6 Terra measured |
| LMArena Text | Not measured | 1448 | Only GPT-5.6 Terra measured |
| LMArena Text: instruction following | Not measured | 1456 | Only GPT-5.6 Terra measured |
| LMArena Text: creative writing | Not measured | 1413 | Only GPT-5.6 Terra measured |
| LMArena Vision | Not measured | 1271 | Only GPT-5.6 Terra measured |
| LMArena Text: English | Not measured | 1449 | Only GPT-5.6 Terra measured |
| LMArena Text: non-English | Not measured | 1441 | Only GPT-5.6 Terra measured |
| LMArena Text: Chinese | Not measured | 1514 | Only GPT-5.6 Terra measured |
| LMArena Text: German | Not measured | 1460 | Only GPT-5.6 Terra measured |
| LMArena Text: Japanese | Not measured | 1454 | Only GPT-5.6 Terra measured |
| LMArena Text: Korean | Not measured | 1427 | Only GPT-5.6 Terra measured |
| LMArena Text: French | Not measured | 1466 | Only GPT-5.6 Terra measured |
| LMArena Text: Spanish | Not measured | 1451 | Only GPT-5.6 Terra measured |
| LMArena Text: Russian | Not measured | 1452 | Only GPT-5.6 Terra measured |
| LMArena Text: Polish | Not measured | 1446 | Only GPT-5.6 Terra measured |
| LMArena Text: multi-turn | Not measured | 1453 | Only GPT-5.6 Terra measured |
| LMArena Text: longer queries | Not measured | 1454 | Only GPT-5.6 Terra measured |
| LMArena Text: writing and language | Not measured | 1431 | Only GPT-5.6 Terra measured |
| LMArena Text: entertainment and media | Not measured | 1418 | Only GPT-5.6 Terra measured |
| LMArena Vision: English | Not measured | 1272 | Only GPT-5.6 Terra measured |
| LMArena Vision: Chinese | Not measured | 1337 | Only GPT-5.6 Terra measured |
| LMArena Vision: reading text | Not measured | 1278 | Only GPT-5.6 Terra measured |
| LMArena Vision: humor | Not measured | 1236 | Only GPT-5.6 Terra measured |
| LMArena Vision: creative writing | Not measured | 1248 | Only GPT-5.6 Terra measured |
| LMArena Document | Not measured | 1472 | Only GPT-5.6 Terra 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 Terra | 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$0.0005Fits in one request
GPT-5.6 Terra$0.0080Fits in one request
DeepSeek V4 Flash Vision Exp costs less
Repository review
50K input + 3K output tokens
DeepSeek V4 Flash Vision Exp$0.013Fits in one request
GPT-5.6 Terra$0.136Fits in one request
DeepSeek V4 Flash Vision Exp costs less
Agent loop
200K input + 10K output tokens
DeepSeek V4 Flash Vision Exp$0.050Fits in one request
GPT-5.6 Terra$0.520Fits 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 Terra |
|---|---|---|
| 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 | $0.2156 | $2.00 |
| Output $/Mtok | $0.6468 | $12.00 |
| Coding index | 37.6 | 69.0 |
| Independent measurements behind it | 1 | 2 |
| Cost per solved task | Not computable | $0.42 |
| Source | OpenRouter listing | OpenRouter listing |
Questions
Is DeepSeek V4 Flash Vision Exp better than GPT-5.6 Terra for coding?
Pick GPT-5.6 Terra for coding: it scores 69.0 on the Vibe Coding Index against 37.6 for DeepSeek V4 Flash Vision Exp. Pick DeepSeek V4 Flash Vision Exp when output tokens cost 18.6x less, or when what matters is AA Agentic Index or LiveBench research, where it leads.
Which is cheaper, DeepSeek V4 Flash Vision Exp or GPT-5.6 Terra?
DeepSeek V4 Flash Vision Exp costs $0.2156 per million input tokens and $0.6468 per million output tokens; GPT-5.6 Terra costs $2.00 and $12.00. Cost per solved task is known for GPT-5.6 Terra only.
Which has the bigger context window, DeepSeek V4 Flash Vision Exp or GPT-5.6 Terra?
GPT-5.6 Terra, with 1.05M tokens against 1.05M.
How many benchmarks is the DeepSeek V4 Flash Vision Exp vs GPT-5.6 Terra comparison based on?
14 benchmarks have a result for both models as of October 21, 2026. DeepSeek V4 Flash Vision Exp's coding index rests on 1 independent benchmark and GPT-5.6 Terra's on 2. Where only one model has a result, the page says so instead of naming a winner.