DeepSeek V4 Flash Vision Exp vs GPT-4.1 Nano
Updated October 21, 2026. 5 benchmarks have a result for both. Coding is ranked on the Vibe Coding Index; every other board is shown as published.
Decision reading
Pick DeepSeek V4 Flash Vision Exp for coding: it scores 37.6 on the Vibe Coding Index against 8.9 for GPT-4.1 Nano.
Pick GPT-4.1 Nano when output tokens cost 1.6x less.
- Shared results
- 5
- DeepSeek V4 Flash Vision Exp only
- 9
- GPT-4.1 Nano only
- 64
- Like-for-like categories
- 4 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
DeepSeek V4 Flash Vision Exp
DeepSeek V4 Flash Vision Exp scores 37.6 against 8.9.
One benchmark behind each score
Intelligence
AA Intelligence Index
DeepSeek V4 Flash Vision Exp
DeepSeek V4 Flash Vision Exp leads, 34.8 against 7.8.
Same board, both measured
Agentic work
AA Agentic Index
No call
Only DeepSeek V4 Flash Vision Exp has a AA Agentic Index result, 47.5.
Directional only
Reasoning
GPQA Diamond
No call
Only GPT-4.1 Nano has a GPQA Diamond result, 50.8%.
Directional only
Math
AIME
No call
Only GPT-4.1 Nano has a AIME result, 26.5%.
Directional only
Knowledge
MMLU Pro
No call
Only GPT-4.1 Nano has a MMLU Pro result, 63.5%.
Directional only
Web design
Design Arena: websites
No call
Only GPT-4.1 Nano has a Design Arena: websites result, 973.
Directional only
Long documents
Listed context window
DeepSeek V4 Flash Vision Exp
DeepSeek V4 Flash Vision Exp takes 1.05M tokens against 1.05M.
Listed by OpenRouter
Everyday cost
1K input + 500 output tokens
GPT-4.1 Nano
DeepSeek V4 Flash Vision Exp $0.0005, GPT-4.1 Nano $0.0003 per turn.
List prices
At a glance
- Coding index
- DeepSeek V4 Flash Vision Exp 37.6 from 1 benchmark, GPT-4.1 Nano 8.9 from 1 benchmark.
- Widest category
- General, 61.0 points apart on average over 1 shared benchmark.
- Widest single gap
- Long context reasoning (AA-LCR): DeepSeek V4 Flash Vision Exp 81.3% against GPT-4.1 Nano 20.3%, 61.0 points apart on a 0 to 100 scale.
- Output price
- DeepSeek V4 Flash Vision Exp $0.6468 against GPT-4.1 Nano $0.40 per million output tokens, 1.6x apart.
- Context window
- DeepSeek V4 Flash Vision Exp takes 1.05M tokens, GPT-4.1 Nano 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-4.1 Nano | Ties |
|---|---|---|---|---|
| Coding | 1 | 0 | ||
| Intelligence | 1 | 0 | ||
| Reasoning | 2 | 0 | ||
| General | 1 | 0 | ||
| All shared boards | 5 | 0 |
CodingLike-for-likeFour of these boards feed the Vibe Coding Index10
| Benchmark | DeepSeek V4 Flash Vision Exp | GPT-4.1 Nano | Leader |
|---|---|---|---|
| Aider polyglot | Not measured | 8.9% | Only GPT-4.1 Nano measured |
| LiveBench coding | 37.6% | Not measured | Only DeepSeek V4 Flash Vision Exp measured |
| AA Coding Index | 65.0 | 11.1 | DeepSeek V4 Flash Vision Exp |
| LiveCodeBench (Vals AI) | Not measured | 42.7% | Only GPT-4.1 Nano measured |
| LiveCodeBench (Artificial Analysis run) | Not measured | 32.6% | Only GPT-4.1 Nano measured |
| SciCode | 49.7% | Not measured | Only DeepSeek V4 Flash Vision Exp measured |
| Terminal-Bench Hard (Artificial Analysis run) | Not measured | 3.8% | Only GPT-4.1 Nano measured |
| WeirdML | Not measured | 19.0% | Only GPT-4.1 Nano measured |
| LMArena Text: coding | Not measured | 1306 | Only GPT-4.1 Nano measured |
| LMArena Text: software and IT | Not measured | 1305 | Only GPT-4.1 Nano measured |
| Neither model has a result on the other 28 boards here | |||
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index10
| Benchmark | DeepSeek V4 Flash Vision Exp | GPT-4.1 Nano | Leader |
|---|---|---|---|
| AA Intelligence Index | 34.8 | 7.8 | DeepSeek V4 Flash Vision Exp |
| Epoch Capabilities Index | Not measured | 129.5 | Only GPT-4.1 Nano measured |
Agentic workDirectional onlyPublic boards, shown as published, kept out of the index5 boards, none shared
| Benchmark | DeepSeek V4 Flash Vision Exp | GPT-4.1 Nano | Leader |
|---|---|---|---|
| AA Agentic Index | 47.5 | Not measured | Only DeepSeek V4 Flash Vision Exp measured |
| LiveBench research | 69.2% | Not measured | Only DeepSeek V4 Flash Vision Exp measured |
| LiveBench browser | 64.0% | Not measured | Only DeepSeek V4 Flash Vision Exp measured |
| LiveBench long agentic | 39.0% | Not measured | Only DeepSeek V4 Flash Vision Exp measured |
| τ²-Bench Telecom | Not measured | 17.3% | Only GPT-4.1 Nano measured |
| Neither model has a result on the other 34 boards here | |||
ReasoningLike-for-likePublic boards, shown as published, kept out of the index20
| Benchmark | DeepSeek V4 Flash Vision Exp | GPT-4.1 Nano | Leader |
|---|---|---|---|
| GPQA Diamond | Not measured | 50.8% | Only GPT-4.1 Nano measured |
| LiveBench reasoning | 85.4% | Not measured | Only DeepSeek V4 Flash Vision Exp measured |
| MMMU Pro (Vals AI) | Not measured | 55.0% | Only GPT-4.1 Nano measured |
| GPQA Diamond (Artificial Analysis run) | 91.3% | 51.2% | DeepSeek V4 Flash Vision Exp |
| Humanity's Last Exam (Artificial Analysis run) | 34.5% | 3.8% | DeepSeek V4 Flash Vision Exp |
| GPQA Diamond (Epoch AI run) | Not measured | 48.9% | Only GPT-4.1 Nano measured |
| ARC-AGI | Not measured | 0.0% | Only GPT-4.1 Nano measured |
| ARC-AGI-2 | Not measured | 0.0% | Only GPT-4.1 Nano measured |
| Chess puzzles | Not measured | 0.0% | Only GPT-4.1 Nano measured |
| LMArena Text: hard prompts | Not measured | 1286 | Only GPT-4.1 Nano measured |
| LMArena Text: expert | Not measured | 1271 | Only GPT-4.1 Nano measured |
| LMArena Text: hard prompts in English | Not measured | 1293 | Only GPT-4.1 Nano measured |
| Neither model has a result on the other 9 boards here | |||
MathDirectional onlyPublic boards, shown as published, kept out of the index9 boards, none shared
| Benchmark | DeepSeek V4 Flash Vision Exp | GPT-4.1 Nano | Leader |
|---|---|---|---|
| AIME | Not measured | 26.5% | Only GPT-4.1 Nano measured |
| MATH 500 (Vals AI) | Not measured | 80.2% | Only GPT-4.1 Nano measured |
| MGSM (Vals AI) | Not measured | 69.3% | Only GPT-4.1 Nano measured |
| AA Math Index | Not measured | 24.0 | Only GPT-4.1 Nano measured |
| AIME 2025 (Artificial Analysis run) | Not measured | 24.0% | Only GPT-4.1 Nano measured |
| OTIS Mock AIME | Not measured | 28.9% | Only GPT-4.1 Nano measured |
| MATH level 5 | Not measured | 70.0% | Only GPT-4.1 Nano measured |
| LMArena Text: math | Not measured | 1274 | Only GPT-4.1 Nano measured |
| LMArena Text: mathematical work | Not measured | 1274 | Only GPT-4.1 Nano measured |
| Neither model has a result on the other 4 boards here | |||
KnowledgeDirectional onlyPublic boards, shown as published, kept out of the index12 boards, none shared
| Benchmark | DeepSeek V4 Flash Vision Exp | GPT-4.1 Nano | Leader |
|---|---|---|---|
| MMLU Pro | Not measured | 63.5% | Only GPT-4.1 Nano measured |
| LegalBench (Vals AI) | Not measured | 61.1% | Only GPT-4.1 Nano measured |
| CorpFin (Vals AI) | Not measured | 42.1% | Only GPT-4.1 Nano measured |
| TaxEval (Vals AI) | Not measured | 60.8% | Only GPT-4.1 Nano measured |
| MortgageTax (Vals AI) | Not measured | 52.8% | Only GPT-4.1 Nano measured |
| MedQA (Vals AI) | Not measured | 68.2% | Only GPT-4.1 Nano measured |
| MMLU Pro (Artificial Analysis run) | Not measured | 65.7% | Only GPT-4.1 Nano measured |
| SimpleQA Verified | Not measured | 6.0% | Only GPT-4.1 Nano measured |
| LMArena Text: science | Not measured | 1297 | Only GPT-4.1 Nano measured |
| LMArena Text: medicine and healthcare | Not measured | 1276 | Only GPT-4.1 Nano measured |
| LMArena Text: legal and government | Not measured | 1300 | Only GPT-4.1 Nano measured |
| LMArena Text: business and finance | Not measured | 1267 | Only GPT-4.1 Nano measured |
| Neither model has a result on the other 5 boards here | |||
Web designDirectional onlyPublic boards, shown as published, kept out of the index7 boards, none shared
| Benchmark | DeepSeek V4 Flash Vision Exp | GPT-4.1 Nano | Leader |
|---|---|---|---|
| Design Arena: websites | Not measured | 973 | Only GPT-4.1 Nano measured |
| Design Arena: UI components | Not measured | 916 | Only GPT-4.1 Nano measured |
| Design Arena: game dev | Not measured | 971 | Only GPT-4.1 Nano measured |
| Design Arena: data viz | Not measured | 891 | Only GPT-4.1 Nano measured |
| Design Arena: 3D | Not measured | 925 | Only GPT-4.1 Nano measured |
| Design Arena: all code categories | Not measured | 963 | Only GPT-4.1 Nano measured |
| LiveBench design | 70.7% | Not measured | Only DeepSeek V4 Flash Vision Exp measured |
| Neither model has a result on the other 2 boards here | |||
GeneralLike-for-likePublic boards, shown as published, kept out of the index10
| Benchmark | DeepSeek V4 Flash Vision Exp | GPT-4.1 Nano | Leader |
|---|---|---|---|
| LiveBench data analysis | 79.5% | Not measured | Only DeepSeek V4 Flash Vision Exp measured |
| IFBench | Not measured | 32.0% | Only GPT-4.1 Nano measured |
| Long context reasoning (AA-LCR) | 81.3% | 20.3% | DeepSeek V4 Flash Vision Exp |
| DTBench | Not measured | 52.5% | Only GPT-4.1 Nano measured |
| LMCA | Not measured | 5.5% | Only GPT-4.1 Nano measured |
| Fiction.LiveBench | Not measured | 25.0% | Only GPT-4.1 Nano measured |
| LMArena Text | Not measured | 1285 | Only GPT-4.1 Nano measured |
| LMArena Text: instruction following | Not measured | 1266 | Only GPT-4.1 Nano measured |
| LMArena Text: creative writing | Not measured | 1260 | Only GPT-4.1 Nano measured |
| LMArena Vision | Not measured | 1063 | Only GPT-4.1 Nano measured |
| LMArena Text: English | Not measured | 1303 | Only GPT-4.1 Nano measured |
| LMArena Text: non-English | Not measured | 1260 | Only GPT-4.1 Nano measured |
| LMArena Text: Chinese | Not measured | 1270 | Only GPT-4.1 Nano measured |
| LMArena Text: German | Not measured | 1288 | Only GPT-4.1 Nano measured |
| LMArena Text: Japanese | Not measured | 1198 | Only GPT-4.1 Nano measured |
| LMArena Text: Russian | Not measured | 1261 | Only GPT-4.1 Nano measured |
| LMArena Text: multi-turn | Not measured | 1277 | Only GPT-4.1 Nano measured |
| LMArena Text: longer queries | Not measured | 1283 | Only GPT-4.1 Nano measured |
| LMArena Text: writing and language | Not measured | 1261 | Only GPT-4.1 Nano measured |
| LMArena Text: entertainment and media | Not measured | 1243 | Only GPT-4.1 Nano measured |
| LMArena Vision: English | Not measured | 1101 | Only GPT-4.1 Nano measured |
| Neither model has a result on the other 25 boards here | |||
Image generationNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
| Benchmark | DeepSeek V4 Flash Vision Exp | GPT-4.1 Nano | 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
GPT-4.1 Nano costs less
Repository review
50K input + 3K output tokens
GPT-4.1 Nano costs less
Agent loop
200K input + 10K output tokens
GPT-4.1 Nano 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-4.1 Nano |
|---|---|---|
| Maker | DeepSeek | OpenAI |
| Weights | Open weights | No public weights listed |
| Released | August 21, 2026 | April 14, 2025 |
| Context window | 1.05M | 1.05M |
| Input $/Mtok | $0.2156 | $0.10 |
| Output $/Mtok | $0.6468 | $0.40 |
| Coding index | 37.6 | 8.9 |
| Independent measurements behind it | 1 | 1 |
| Cost per solved task | Not computable | Not computable |
| Source | OpenRouter listing | OpenRouter listing |
Questions
Is DeepSeek V4 Flash Vision Exp better than GPT-4.1 Nano for coding?
Pick DeepSeek V4 Flash Vision Exp for coding: it scores 37.6 on the Vibe Coding Index against 8.9 for GPT-4.1 Nano. Pick GPT-4.1 Nano when output tokens cost 1.6x less.
Which is cheaper, DeepSeek V4 Flash Vision Exp or GPT-4.1 Nano?
DeepSeek V4 Flash Vision Exp costs $0.2156 per million input tokens and $0.6468 per million output tokens; GPT-4.1 Nano costs $0.10 and $0.40. Cost per solved task is known for neither of them.
Which has the bigger context window, DeepSeek V4 Flash Vision Exp or GPT-4.1 Nano?
DeepSeek V4 Flash Vision Exp, with 1.05M tokens against 1.05M.
How many benchmarks is the DeepSeek V4 Flash Vision Exp vs GPT-4.1 Nano comparison based on?
5 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-4.1 Nano's on 1. Where only one model has a result, the page says so instead of naming a winner.