DeepSeek V4.1 Flash vs GPT-4.1 Nano
DeepSeek V4.1 Flash leads GPT-4.1 Nano on the Artificial Analysis Intelligence Index, 24.7 to 7.8, and GPT-4.1 Nano costs 2.1x less per output token ($0.40 vs $0.84 per million). Updated October 22, 2026; 45 benchmarks have a result for both.
vs boards won of 45 shared
DeepSeek V4.1 Flash or GPT-4.1 Nano: which to pick
Only DeepSeek V4.1 Flash has a coding score, 62.5 on the Vibe Coding Index; GPT-4.1 Nano has none, so the two cannot be ranked on coding.
Pick GPT-4.1 Nano for output tokens 2.1x cheaper ($0.40 vs $0.84 per million).
Model ADeepSeek V4.1 FlashDeepSeek62.5/1005 independent benchmarksNo cost per solved taskModel BGPT-4.1 NanoOpenAINot benchmarkedNo coding benchmarkNo cost per solved task
- Shared results
- 45
- DeepSeek V4.1 Flash only
- 56
- GPT-4.1 Nano only
- 26
- 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
No call
Only DeepSeek V4.1 Flash has a coding score, so no call is made.
One side not measured
Intelligence
AA Intelligence Index
DeepSeek V4.1 Flash
DeepSeek V4.1 Flash leads, 24.7 against 7.8.
Same board, both measured
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
DeepSeek V4.1 Flash
DeepSeek V4.1 Flash leads, 1308 against 972.
Same board, both measured
Long documents
Listed context window
DeepSeek V4.1 Flash
DeepSeek V4.1 Flash takes 1.05M tokens against 1.05M.
Listed by OpenRouter
Everyday cost
1K input + 500 output tokens
GPT-4.1 Nano
DeepSeek V4.1 Flash $0.0006, GPT-4.1 Nano $0.0003 per turn.
List prices
At a glance
- Coding index
- DeepSeek V4.1 Flash 62.5 from 5 benchmarks, GPT-4.1 Nano not benchmarked.
- Widest category
- Reasoning, 49.4 points apart on average over 8 shared benchmarks.
- Widest single gap
- ARC-AGI: DeepSeek V4.1 Flash 94.5% against GPT-4.1 Nano 0.0%, 94.5 points apart on a 0 to 100 scale.
- Output price
- DeepSeek V4.1 Flash $0.84 against GPT-4.1 Nano $0.40 per million output tokens, 2.1x apart.
- Context window
- DeepSeek V4.1 Flash 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 V4.1 Flash | Bars | GPT-4.1 Nano | Ties |
|---|---|---|---|---|
| Coding | 2 | 0 | ||
| Intelligence | 2 | 0 | ||
| Reasoning | 8 | 0 | ||
| Math | 3 | 0 | ||
| Knowledge | 6 | 0 | ||
| Web design | 6 | 0 | ||
| General | 18 | 0 | ||
| All shared boards | 45 | 0 |
CodingLike-for-likeSix of these boards feed the Vibe Coding Index20
| Benchmark | DeepSeek V4.1 Flash | GPT-4.1 Nano | Leader |
|---|---|---|---|
| Aider polyglot | Not measured | 8.9% | Only GPT-4.1 Nano measured |
| LiveBench coding | 90.2% | Not measured | Only DeepSeek V4.1 Flash measured |
| LMArena WebDev | 1618 | Not measured | Only DeepSeek V4.1 Flash measured |
| AA Coding Index | Not measured | 11.1 | Only GPT-4.1 Nano measured |
| LiveCodeBench (Vals AI) | Not measured | 42.7% | Only GPT-4.1 Nano measured |
| Terminal-Bench 4 (Vals AI) | 19.7% | Not measured | Only DeepSeek V4.1 Flash measured |
| Vibe Code Bench (Vals AI) | 84.7% | Not measured | Only DeepSeek V4.1 Flash measured |
| Code migration (Vals AI) | 45.6% | Not measured | Only DeepSeek V4.1 Flash measured |
| ProgramBench (Vals AI) | 0.5% | Not measured | Only DeepSeek V4.1 Flash measured |
| IOI (Vals AI) | 40.3% | Not measured | Only DeepSeek V4.1 Flash measured |
| Terminal-Bench 2.1 (Vals AI) | 74.5% | Not measured | Only DeepSeek V4.1 Flash measured |
| SWE-bench Multimodal (Vals AI) | 46.5% | Not measured | Only DeepSeek V4.1 Flash measured |
| Vibe Code Bench 1-100 (Vals AI) | 16.4% | Not measured | Only DeepSeek V4.1 Flash measured |
| SkillsBench (Vals AI) | 69.8% | Not measured | Only DeepSeek V4.1 Flash measured |
| CyberBench (Vals AI) | 73.7% | Not measured | Only DeepSeek V4.1 Flash measured |
| LiveCodeBench (Artificial Analysis run) | Not measured | 32.6% | Only GPT-4.1 Nano measured |
| SciCode | 51.9% | Not measured | Only DeepSeek V4.1 Flash measured |
| Terminal-Bench Hard (Artificial Analysis run) | Not measured | 3.8% | Only GPT-4.1 Nano measured |
| FrontierCode | 43.9% | Not measured | Only DeepSeek V4.1 Flash measured |
| WeirdML | Not measured | 19.0% | Only GPT-4.1 Nano measured |
| ALE-Bench | 1092.3 | Not measured | Only DeepSeek V4.1 Flash measured |
| LMArena Text: coding | 1502 | 1306 | DeepSeek V4.1 Flash |
| LMArena Text: software and IT | 1496 | 1305 | DeepSeek V4.1 Flash |
| LMArena WebDev: React | 1628 | Not measured | Only DeepSeek V4.1 Flash measured |
| LMArena WebDev: HTML | 1612 | Not measured | Only DeepSeek V4.1 Flash measured |
| LMArena WebDev: from an image | 1606 | Not measured | Only DeepSeek V4.1 Flash measured |
| Neither model has a result on the other 13 boards here | |||
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index20
| Benchmark | DeepSeek V4.1 Flash | GPT-4.1 Nano | Leader |
|---|---|---|---|
| AA Intelligence Index | 24.7 | 7.8 | DeepSeek V4.1 Flash |
| Epoch Capabilities Index | 155.9 | 129.5 | DeepSeek V4.1 Flash |
Agentic workDirectional onlyPublic boards, shown as published, kept out of the index14 boards, none shared
| Benchmark | DeepSeek V4.1 Flash | GPT-4.1 Nano | Leader |
|---|---|---|---|
| LiveBench research | 86.8% | Not measured | Only DeepSeek V4.1 Flash measured |
| LiveBench browser | 84.0% | Not measured | Only DeepSeek V4.1 Flash measured |
| LiveBench long agentic | 40.1% | Not measured | Only DeepSeek V4.1 Flash measured |
| SREBench (Vals AI) | 0.8% | Not measured | Only DeepSeek V4.1 Flash measured |
| Finance Agent (Vals AI) | 53.5% | Not measured | Only DeepSeek V4.1 Flash measured |
| Tax Agent Bench (Vals AI) | 26.6% | Not measured | Only DeepSeek V4.1 Flash measured |
| Legal Research Bench (Vals AI) | 41.4% | Not measured | Only DeepSeek V4.1 Flash measured |
| Excel Modeling Benchmark (Vals AI) | 57.2% | Not measured | Only DeepSeek V4.1 Flash measured |
| BioMysteryBench (Vals AI) | 67.8% | Not measured | Only DeepSeek V4.1 Flash measured |
| Terminal-Bench-Science (Vals AI) | 0.0% | Not measured | Only DeepSeek V4.1 Flash measured |
| Vals Science Index | 29.6% | Not measured | Only DeepSeek V4.1 Flash measured |
| τ²-Bench Telecom | Not measured | 17.3% | Only GPT-4.1 Nano measured |
| APEX-Agents | 39.5% | Not measured | Only DeepSeek V4.1 Flash measured |
| Berkeley Function Calling Leaderboard (BFCL) | Not measured | 33.1% | Only GPT-4.1 Nano measured |
| Neither model has a result on the other 27 boards here | |||
ReasoningLike-for-likePublic boards, shown as published, kept out of the index80
| Benchmark | DeepSeek V4.1 Flash | GPT-4.1 Nano | Leader |
|---|---|---|---|
| GPQA Diamond | Not measured | 50.8% | Only GPT-4.1 Nano measured |
| LiveBench reasoning | 86.7% | Not measured | Only DeepSeek V4.1 Flash measured |
| MysteryMechanism (Vals AI) | 21.2% | Not measured | Only DeepSeek V4.1 Flash measured |
| MMMU Pro (Vals AI) | Not measured | 55.0% | Only GPT-4.1 Nano measured |
| GPQA Diamond (Artificial Analysis run) | Not measured | 51.2% | Only GPT-4.1 Nano measured |
| Humanity's Last Exam (Artificial Analysis run) | 39.2% | 3.8% | DeepSeek V4.1 Flash |
| GPQA Diamond (Epoch AI run) | 89.8% | 48.9% | DeepSeek V4.1 Flash |
| ARC-AGI | 94.5% | 0.0% | DeepSeek V4.1 Flash |
| ARC-AGI-2 | 72.9% | 0.0% | DeepSeek V4.1 Flash |
| Chess puzzles | 48.0% | 0.0% | DeepSeek V4.1 Flash |
| Mystery game puzzles | 43.0% | Not measured | Only DeepSeek V4.1 Flash measured |
| LMArena Text: hard prompts | 1483 | 1286 | DeepSeek V4.1 Flash |
| LMArena Text: expert | 1501 | 1271 | DeepSeek V4.1 Flash |
| LMArena Text: hard prompts in English | 1488 | 1293 | DeepSeek V4.1 Flash |
| LMArena Vision: diagrams | 1297 | Not measured | Only DeepSeek V4.1 Flash measured |
| LMArena Vision: homework | 1307 | Not measured | Only DeepSeek V4.1 Flash measured |
| Kagi LLM Benchmark | Not measured | 33.3% | Only GPT-4.1 Nano measured |
| Neither model has a result on the other 5 boards here | |||
MathLike-for-likePublic boards, shown as published, kept out of the index30
| Benchmark | DeepSeek V4.1 Flash | 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 | 98.3% | 28.9% | DeepSeek V4.1 Flash |
| FrontierMath, tiers 1 to 3 | 67.4% | Not measured | Only DeepSeek V4.1 Flash measured |
| FrontierMath, tier 4 | 26.8% | Not measured | Only DeepSeek V4.1 Flash measured |
| ProofBench | 54.0% | Not measured | Only DeepSeek V4.1 Flash measured |
| MATH level 5 | Not measured | 70.0% | Only GPT-4.1 Nano measured |
| LMArena Text: math | 1478 | 1274 | DeepSeek V4.1 Flash |
| LMArena Text: mathematical work | 1485 | 1274 | DeepSeek V4.1 Flash |
| Neither model has a result on the other 1 board here | |||
KnowledgeLike-for-likePublic boards, shown as published, kept out of the index60
| Benchmark | DeepSeek V4.1 Flash | GPT-4.1 Nano | Leader |
|---|---|---|---|
| MMLU Pro | Not measured | 63.5% | Only GPT-4.1 Nano measured |
| LegalBench (Vals AI) | 83.3% | 61.1% | DeepSeek V4.1 Flash |
| 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 |
| MedCode (Vals AI) | 41.2% | Not measured | Only DeepSeek V4.1 Flash measured |
| MMLU Pro (Artificial Analysis run) | Not measured | 65.7% | Only GPT-4.1 Nano measured |
| SimpleQA Verified | 42.9% | 6.0% | DeepSeek V4.1 Flash |
| LMArena Text: science | 1469 | 1297 | DeepSeek V4.1 Flash |
| LMArena Text: medicine and healthcare | 1484 | 1276 | DeepSeek V4.1 Flash |
| LMArena Text: legal and government | 1443 | 1300 | DeepSeek V4.1 Flash |
| LMArena Text: business and finance | 1461 | 1267 | DeepSeek V4.1 Flash |
| Neither model has a result on the other 5 boards here | |||
Web designLike-for-likePublic boards, shown as published, kept out of the index60
| Benchmark | DeepSeek V4.1 Flash | GPT-4.1 Nano | Leader |
|---|---|---|---|
| Design Arena: websites | 1308 | 972 | DeepSeek V4.1 Flash |
| Design Arena: UI components | 1312 | 913 | DeepSeek V4.1 Flash |
| Design Arena: game dev | 1330 | 970 | DeepSeek V4.1 Flash |
| Design Arena: data viz | 1291 | 891 | DeepSeek V4.1 Flash |
| Design Arena: 3D | 1355 | 924 | DeepSeek V4.1 Flash |
| Design Arena: all code categories | 1320 | 962 | DeepSeek V4.1 Flash |
| Design Arena: SVG | 1245 | Not measured | Only DeepSeek V4.1 Flash measured |
| Design Arena: ASCII art | 1265 | Not measured | Only DeepSeek V4.1 Flash measured |
| LiveBench design | 79.2% | Not measured | Only DeepSeek V4.1 Flash measured |
GeneralLike-for-likePublic boards, shown as published, kept out of the index180
| Benchmark | DeepSeek V4.1 Flash | GPT-4.1 Nano | Leader |
|---|---|---|---|
| LiveBench data analysis | 79.3% | Not measured | Only DeepSeek V4.1 Flash measured |
| Public Benefits Bench (Vals AI) | 64.3% | Not measured | Only DeepSeek V4.1 Flash measured |
| SAGE (Vals AI) | 47.9% | Not measured | Only DeepSeek V4.1 Flash measured |
| MedScribe (Vals AI) | 85.5% | Not measured | Only DeepSeek V4.1 Flash measured |
| IFBench | Not measured | 32.0% | Only GPT-4.1 Nano measured |
| Long context reasoning (AA-LCR) | 84.0% | 20.3% | DeepSeek V4.1 Flash |
| DTBench | 89.9% | 52.5% | DeepSeek V4.1 Flash |
| LMCA | 47.0% | 5.5% | DeepSeek V4.1 Flash |
| Fiction.LiveBench | Not measured | 25.0% | Only GPT-4.1 Nano measured |
| Surface Evolver Bench | 46.3% | Not measured | Only DeepSeek V4.1 Flash measured |
| Furniture assembly | 34.2% | Not measured | Only DeepSeek V4.1 Flash measured |
| LMArena Text | 1464 | 1285 | DeepSeek V4.1 Flash |
| LMArena Text: instruction following | 1473 | 1266 | DeepSeek V4.1 Flash |
| LMArena Text: creative writing | 1437 | 1260 | DeepSeek V4.1 Flash |
| LMArena Vision | 1278 | 1063 | DeepSeek V4.1 Flash |
| LMArena Text: English | 1473 | 1303 | DeepSeek V4.1 Flash |
| LMArena Text: non-English | 1449 | 1260 | DeepSeek V4.1 Flash |
| LMArena Text: Chinese | 1501 | 1270 | DeepSeek V4.1 Flash |
| LMArena Text: German | 1470 | 1288 | DeepSeek V4.1 Flash |
| LMArena Text: Japanese | 1432 | 1198 | DeepSeek V4.1 Flash |
| LMArena Text: Korean | 1436 | Not measured | Only DeepSeek V4.1 Flash measured |
| LMArena Text: French | 1465 | Not measured | Only DeepSeek V4.1 Flash measured |
| LMArena Text: Spanish | 1459 | Not measured | Only DeepSeek V4.1 Flash measured |
| LMArena Text: Russian | 1467 | 1261 | DeepSeek V4.1 Flash |
| LMArena Text: Polish | 1457 | Not measured | Only DeepSeek V4.1 Flash measured |
| LMArena Text: multi-turn | 1461 | 1277 | DeepSeek V4.1 Flash |
| LMArena Text: longer queries | 1473 | 1283 | DeepSeek V4.1 Flash |
| LMArena Text: writing and language | 1450 | 1261 | DeepSeek V4.1 Flash |
| LMArena Text: entertainment and media | 1445 | 1243 | DeepSeek V4.1 Flash |
| LMArena Vision: English | 1288 | 1101 | DeepSeek V4.1 Flash |
| LMArena Vision: Chinese | 1327 | Not measured | Only DeepSeek V4.1 Flash measured |
| LMArena Vision: reading text | 1282 | Not measured | Only DeepSeek V4.1 Flash measured |
| LMArena Vision: humor | 1260 | Not measured | Only DeepSeek V4.1 Flash measured |
| LMArena Vision: creative writing | 1275 | Not measured | Only DeepSeek V4.1 Flash measured |
| Neither model has a result on the other 12 boards here | |||
Image generationNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
| Benchmark | DeepSeek V4.1 Flash | 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
DeepSeek V4.1 Flash$0.0006Fits in one request
GPT-4.1 Nano$0.0003Fits in one request
GPT-4.1 Nano costs less
Repository review
50K input + 3K output tokens
DeepSeek V4.1 Flash$0.014Fits in one request
GPT-4.1 Nano$0.0062Fits in one request
GPT-4.1 Nano costs less
Agent loop
200K input + 10K output tokens
DeepSeek V4.1 Flash$0.053Fits in one request
GPT-4.1 Nano$0.024Fits in one request
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 V4.1 Flash | OpenAI GPT-4.1 Nano |
|---|---|---|
| Maker | DeepSeek | OpenAI |
| Weights | Open weights | No public weights listed |
| Released | September 10, 2026 | April 14, 2025 |
| Context window | 1.05M | 1.05M |
| Input $/Mtok | $0.2225 | $0.10 |
| Output $/Mtok | $0.84 | $0.40 |
| Coding index | 62.5 | Not benchmarked |
| Independent measurements behind it | 5 | 0 |
| Cost per solved task | Not computable | Not computable |
| Source | OpenRouter listing | OpenRouter listing |
Questions
Is DeepSeek V4.1 Flash better than GPT-4.1 Nano for coding?
Only DeepSeek V4.1 Flash has a coding score, 62.5 on the Vibe Coding Index; GPT-4.1 Nano has none, so the two cannot be ranked on coding. Pick GPT-4.1 Nano for output tokens 2.1x cheaper ($0.40 vs $0.84 per million).
Which is cheaper, DeepSeek V4.1 Flash or GPT-4.1 Nano?
DeepSeek V4.1 Flash costs $0.2225 per million input tokens and $0.84 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 V4.1 Flash or GPT-4.1 Nano?
DeepSeek V4.1 Flash, with 1.05M tokens against 1.05M.
How many benchmarks is the DeepSeek V4.1 Flash vs GPT-4.1 Nano comparison based on?
45 benchmarks have a result for both models as of October 22, 2026. DeepSeek V4.1 Flash's coding index rests on 5 independent benchmarks and GPT-4.1 Nano's on 0. Where only one model has a result, the page says so instead of naming a winner.