DeepSeek V4 Flash 0731 vs GPT-5.4 Nano
DeepSeek V4 Flash 0731 leads GPT-5.4 Nano on coding, 51.8 to 44.8 on the Vibe Coding Index, and DeepSeek V4 Flash 0731 costs 3.2x less per output token ($0.396 vs $1.25 per million). Updated October 22, 2026; 38 benchmarks have a result for both.
DeepSeek V4 Flash 0731 or GPT-5.4 Nano: which to pick
Pick DeepSeek V4 Flash 0731 for coding: it scores 51.8 on the Vibe Coding Index against 44.8 for GPT-5.4 Nano.
Pick GPT-5.4 Nano for work measured by Chess puzzles or LegalBench (Vals AI), where it leads.
- Shared results
- 38
- DeepSeek V4 Flash 0731 only
- 17
- GPT-5.4 Nano only
- 47
- 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
DeepSeek V4 Flash 0731
DeepSeek V4 Flash 0731 scores 51.8 against 44.8.
4 and 2 benchmarks behind the scores
Intelligence
AA Intelligence Index
DeepSeek V4 Flash 0731
DeepSeek V4 Flash 0731 leads, 34.3 against 20.7.
Same board, both measured
Agentic work
AA Agentic Index
DeepSeek V4 Flash 0731
DeepSeek V4 Flash 0731 leads, 41.0 against 16.0.
Same board, both measured
Reasoning
GPQA Diamond
DeepSeek V4 Flash 0731
DeepSeek V4 Flash 0731 leads, 89.9% against 77.5%.
Same board, both measured
Math
AIME
No call
Only GPT-5.4 Nano has a AIME result, 88.8%.
Directional only
Knowledge
MMLU Pro
DeepSeek V4 Flash 0731
DeepSeek V4 Flash 0731 leads, 86.2% against 77.2%.
Same board, both measured
Web design
Design Arena: websites
No call
Only DeepSeek V4 Flash 0731 has a Design Arena: websites result, 1237.
Directional only
Long documents
Listed context window
DeepSeek V4 Flash 0731
DeepSeek V4 Flash 0731 takes 1.05M tokens against 400K.
Listed by OpenRouter
Everyday cost
1K input + 500 output tokens
DeepSeek V4 Flash 0731
DeepSeek V4 Flash 0731 $0.0003, GPT-5.4 Nano $0.0008 per turn.
List prices
Cost per solved task
One SWE-bench Verified task, solved
DeepSeek V4 Flash 0731
DeepSeek V4 Flash 0731 $0.01, GPT-5.4 Nano $0.14.
Published attempt cost and pass rate
At a glance
- Coding index
- DeepSeek V4 Flash 0731 51.8 from 4 benchmarks, GPT-5.4 Nano 44.8 from 2 benchmarks.
- Widest category
- Reasoning, 21.9 points apart on average over 8 shared benchmarks.
- Widest single gap
- ARC-AGI-2: DeepSeek V4 Flash 0731 61.4% against GPT-5.4 Nano 5.7%, 55.7 points apart on a 0 to 100 scale.
- Output price
- DeepSeek V4 Flash 0731 $0.396 against GPT-5.4 Nano $1.25 per million output tokens, 3.2x apart.
- Context window
- DeepSeek V4 Flash 0731 takes 1.05M tokens, GPT-5.4 Nano 400K.
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 0731 | Bars | GPT-5.4 Nano | Ties |
|---|---|---|---|---|
| Coding | 9 | 0 | ||
| Intelligence | 2 | 0 | ||
| Agentic work | 5 | 0 | ||
| Reasoning | 7 | 1 | ||
| Math | 4 | 0 | ||
| Knowledge | 5 | 1 | ||
| General | 4 | 0 | ||
| All shared boards | 36 | 2 |
CodingLike-for-likeSix of these boards feed the Vibe Coding Index90
| Benchmark | DeepSeek V4 Flash 0731 | GPT-5.4 Nano | Leader |
|---|---|---|---|
| AA Coding Index | 69.1 | 56.1 | DeepSeek V4 Flash 0731 |
| LiveCodeBench (Vals AI) | 87.3% | 84.0% | DeepSeek V4 Flash 0731 |
| SWE-bench Verified (Vals AI) | 88.8% | 69.8% | DeepSeek V4 Flash 0731 |
| Terminal-Bench 4 (Vals AI) | 18.7% | Not measured | Only DeepSeek V4 Flash 0731 measured |
| Vibe Code Bench (Vals AI) | 74.7% | 26.1% | DeepSeek V4 Flash 0731 |
| Code migration (Vals AI) | 38.6% | 14.5% | DeepSeek V4 Flash 0731 |
| ProgramBench (Vals AI) | 0.0% | Not measured | Only DeepSeek V4 Flash 0731 measured |
| IOI (Vals AI) | 32.7% | Not measured | Only DeepSeek V4 Flash 0731 measured |
| Terminal-Bench 2.1 (Vals AI) | 67.0% | 41.6% | DeepSeek V4 Flash 0731 |
| SkillsBench (Vals AI) | 50.7% | Not measured | Only DeepSeek V4 Flash 0731 measured |
| CyberBench (Vals AI) | 72.1% | Not measured | Only DeepSeek V4 Flash 0731 measured |
| SciCode | 50.3% | 47.2% | DeepSeek V4 Flash 0731 |
| Terminal-Bench Hard (Artificial Analysis run) | Not measured | 42.4% | Only GPT-5.4 Nano measured |
| FrontierCode | 18.8% | Not measured | Only DeepSeek V4 Flash 0731 measured |
| WeirdML | 63.0% | 49.2% | DeepSeek V4 Flash 0731 |
| ALE-Bench | 1306.1 | 1004.5 | DeepSeek V4 Flash 0731 |
| LMArena Text: coding | Not measured | 1404 | Only GPT-5.4 Nano measured |
| LMArena Text: software and IT | Not measured | 1402 | Only GPT-5.4 Nano measured |
| Neither model has a result on the other 21 boards here | |||
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index20
| Benchmark | DeepSeek V4 Flash 0731 | GPT-5.4 Nano | Leader |
|---|---|---|---|
| AA Intelligence Index | 34.3 | 20.7 | DeepSeek V4 Flash 0731 |
| Epoch Capabilities Index | 154.8 | 146.0 | DeepSeek V4 Flash 0731 |
Agentic workLike-for-likePublic boards, shown as published, kept out of the index50
| Benchmark | DeepSeek V4 Flash 0731 | GPT-5.4 Nano | Leader |
|---|---|---|---|
| AA Agentic Index | 41.0 | 16.0 | DeepSeek V4 Flash 0731 |
| Finance Agent (Vals AI) | 49.5% | 38.2% | DeepSeek V4 Flash 0731 |
| Tax Agent Bench (Vals AI) | 28.1% | 5.0% | DeepSeek V4 Flash 0731 |
| Legal Research Bench (Vals AI) | 30.3% | 6.3% | DeepSeek V4 Flash 0731 |
| Excel Modeling Benchmark (Vals AI) | 57.0% | 44.8% | DeepSeek V4 Flash 0731 |
| BioMysteryBench (Vals AI) | 64.4% | Not measured | Only DeepSeek V4 Flash 0731 measured |
| Terminal-Bench-Science (Vals AI) | 4.3% | Not measured | Only DeepSeek V4 Flash 0731 measured |
| τ²-Bench Telecom | Not measured | 76.0% | Only GPT-5.4 Nano measured |
| Neither model has a result on the other 33 boards here | |||
ReasoningLike-for-likePublic boards, shown as published, kept out of the index71
| Benchmark | DeepSeek V4 Flash 0731 | GPT-5.4 Nano | Leader |
|---|---|---|---|
| GPQA Diamond | 89.9% | 77.5% | DeepSeek V4 Flash 0731 |
| MMMU Pro (Vals AI) | Not measured | 73.6% | Only GPT-5.4 Nano measured |
| GPQA Diamond (Artificial Analysis run) | 90.8% | 81.7% | DeepSeek V4 Flash 0731 |
| Humanity's Last Exam (Artificial Analysis run) | 38.6% | 28.3% | DeepSeek V4 Flash 0731 |
| GPQA Diamond (Epoch AI run) | 91.0% | 78.5% | DeepSeek V4 Flash 0731 |
| ARC-AGI | 89.0% | 51.5% | DeepSeek V4 Flash 0731 |
| ARC-AGI-2 | 61.4% | 5.7% | DeepSeek V4 Flash 0731 |
| SimpleBench | 61.1% | Not measured | Only DeepSeek V4 Flash 0731 measured |
| Chess puzzles | 32.0% | 45.0% | GPT-5.4 Nano |
| Mystery game puzzles | 34.0% | 9.0% | DeepSeek V4 Flash 0731 |
| LMArena Text: hard prompts | Not measured | 1381 | Only GPT-5.4 Nano measured |
| LMArena Text: expert | Not measured | 1396 | Only GPT-5.4 Nano measured |
| LMArena Text: hard prompts in English | Not measured | 1387 | Only GPT-5.4 Nano measured |
| LMArena Vision: diagrams | Not measured | 1210 | Only GPT-5.4 Nano measured |
| LMArena Vision: homework | Not measured | 1225 | Only GPT-5.4 Nano measured |
| Kagi LLM Benchmark | Not measured | 39.7% | Only GPT-5.4 Nano measured |
| Neither model has a result on the other 6 boards here | |||
MathLike-for-likePublic boards, shown as published, kept out of the index40
| Benchmark | DeepSeek V4 Flash 0731 | GPT-5.4 Nano | Leader |
|---|---|---|---|
| AIME | Not measured | 88.8% | Only GPT-5.4 Nano measured |
| OTIS Mock AIME | 94.4% | 87.8% | DeepSeek V4 Flash 0731 |
| FrontierMath, tiers 1 to 3 | 57.5% | 44.9% | DeepSeek V4 Flash 0731 |
| FrontierMath, tier 4 | 24.4% | 12.2% | DeepSeek V4 Flash 0731 |
| ProofBench | 56.0% | 5.0% | DeepSeek V4 Flash 0731 |
| LMArena Text: math | Not measured | 1405 | Only GPT-5.4 Nano measured |
| LMArena Text: mathematical work | Not measured | 1409 | Only GPT-5.4 Nano measured |
| Neither model has a result on the other 6 boards here | |||
KnowledgeLike-for-likePublic boards, shown as published, kept out of the index51
| Benchmark | DeepSeek V4 Flash 0731 | GPT-5.4 Nano | Leader |
|---|---|---|---|
| MMLU Pro | 86.2% | 77.2% | DeepSeek V4 Flash 0731 |
| LegalBench (Vals AI) | 77.7% | 77.9% | GPT-5.4 Nano |
| CaseLaw (Vals AI) | Not measured | 51.9% | Only GPT-5.4 Nano measured |
| CorpFin (Vals AI) | 61.9% | 61.2% | DeepSeek V4 Flash 0731 |
| TaxEval (Vals AI) | 70.7% | 67.4% | DeepSeek V4 Flash 0731 |
| MortgageTax (Vals AI) | Not measured | 59.1% | Only GPT-5.4 Nano measured |
| MedCode (Vals AI) | 41.4% | 41.0% | DeepSeek V4 Flash 0731 |
| SimpleQA Verified | 33.6% | 11.7% | DeepSeek V4 Flash 0731 |
| LMArena Text: science | Not measured | 1374 | Only GPT-5.4 Nano measured |
| LMArena Text: medicine and healthcare | Not measured | 1369 | Only GPT-5.4 Nano measured |
| LMArena Text: legal and government | Not measured | 1368 | Only GPT-5.4 Nano measured |
| LMArena Text: business and finance | Not measured | 1366 | Only GPT-5.4 Nano measured |
| Neither model has a result on the other 6 boards here | |||
Web designDirectional onlyPublic boards, shown as published, kept out of the index8 boards, none shared
| Benchmark | DeepSeek V4 Flash 0731 | GPT-5.4 Nano | Leader |
|---|---|---|---|
| Design Arena: websites | 1237 | Not measured | Only DeepSeek V4 Flash 0731 measured |
| Design Arena: UI components | 1233 | Not measured | Only DeepSeek V4 Flash 0731 measured |
| Design Arena: game dev | 1207 | Not measured | Only DeepSeek V4 Flash 0731 measured |
| Design Arena: data viz | 1180 | Not measured | Only DeepSeek V4 Flash 0731 measured |
| Design Arena: 3D | 1208 | Not measured | Only DeepSeek V4 Flash 0731 measured |
| Design Arena: all code categories | 1229 | Not measured | Only DeepSeek V4 Flash 0731 measured |
| Design Arena: SVG | 1184 | Not measured | Only DeepSeek V4 Flash 0731 measured |
| Design Arena: ASCII art | 1090 | Not measured | Only DeepSeek V4 Flash 0731 measured |
| Neither model has a result on the other 1 board here | |||
GeneralLike-for-likePublic boards, shown as published, kept out of the index40
| Benchmark | DeepSeek V4 Flash 0731 | GPT-5.4 Nano | Leader |
|---|---|---|---|
| SAGE (Vals AI) | Not measured | 38.1% | Only GPT-5.4 Nano measured |
| MedScribe (Vals AI) | 80.4% | 77.1% | DeepSeek V4 Flash 0731 |
| Vals Multimodal Index | Not measured | 47.6% | Only GPT-5.4 Nano measured |
| IFBench | Not measured | 75.9% | Only GPT-5.4 Nano measured |
| Long context reasoning (AA-LCR) | 79.7% | 76.7% | DeepSeek V4 Flash 0731 |
| DTBench | 90.9% | 80.3% | DeepSeek V4 Flash 0731 |
| LMCA | 41.7% | 36.9% | DeepSeek V4 Flash 0731 |
| LMArena Text | Not measured | 1372 | Only GPT-5.4 Nano measured |
| LMArena Text: instruction following | Not measured | 1362 | Only GPT-5.4 Nano measured |
| LMArena Text: creative writing | Not measured | 1315 | Only GPT-5.4 Nano measured |
| LMArena Vision | Not measured | 1196 | Only GPT-5.4 Nano measured |
| LMArena Text: English | Not measured | 1381 | Only GPT-5.4 Nano measured |
| LMArena Text: non-English | Not measured | 1359 | Only GPT-5.4 Nano measured |
| LMArena Text: Chinese | Not measured | 1391 | Only GPT-5.4 Nano measured |
| LMArena Text: German | Not measured | 1368 | Only GPT-5.4 Nano measured |
| LMArena Text: Japanese | Not measured | 1343 | Only GPT-5.4 Nano measured |
| LMArena Text: Korean | Not measured | 1321 | Only GPT-5.4 Nano measured |
| LMArena Text: French | Not measured | 1395 | Only GPT-5.4 Nano measured |
| LMArena Text: Spanish | Not measured | 1371 | Only GPT-5.4 Nano measured |
| LMArena Text: Russian | Not measured | 1363 | Only GPT-5.4 Nano measured |
| LMArena Text: Polish | Not measured | 1366 | Only GPT-5.4 Nano measured |
| LMArena Text: multi-turn | Not measured | 1382 | Only GPT-5.4 Nano measured |
| LMArena Text: longer queries | Not measured | 1365 | Only GPT-5.4 Nano measured |
| LMArena Text: writing and language | Not measured | 1338 | Only GPT-5.4 Nano measured |
| LMArena Text: entertainment and media | Not measured | 1325 | Only GPT-5.4 Nano measured |
| LMArena Vision: English | Not measured | 1202 | Only GPT-5.4 Nano measured |
| LMArena Vision: Chinese | Not measured | 1232 | Only GPT-5.4 Nano measured |
| LMArena Vision: reading text | Not measured | 1204 | Only GPT-5.4 Nano measured |
| LMArena Vision: humor | Not measured | 1161 | Only GPT-5.4 Nano measured |
| LMArena Vision: recognizing things | Not measured | 1141 | Only GPT-5.4 Nano measured |
| LMArena Vision: creative writing | Not measured | 1159 | Only GPT-5.4 Nano measured |
| Neither model has a result on the other 15 boards here | |||
Image generationNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
| Benchmark | DeepSeek V4 Flash 0731 | GPT-5.4 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 Flash 0731 costs less
Repository review
50K input + 3K output tokens
DeepSeek V4 Flash 0731 costs less
Agent loop
200K input + 10K output tokens
DeepSeek V4 Flash 0731 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 0731 | OpenAI GPT-5.4 Nano |
|---|---|---|
| Maker | DeepSeek | OpenAI |
| Weights | Open weights | No public weights listed |
| Released | July 31, 2026 | March 17, 2026 |
| Context window | 1.05M | 400K |
| Input $/Mtok | $0.14 | $0.20 |
| Output $/Mtok | $0.396 | $1.25 |
| Coding index | 51.8 | 44.8 |
| Independent measurements behind it | 4 | 2 |
| Cost per solved task | $0.01 | $0.14 |
| Source | OpenRouter listing | OpenRouter listing |
Questions
Is DeepSeek V4 Flash 0731 better than GPT-5.4 Nano for coding?
Pick DeepSeek V4 Flash 0731 for coding: it scores 51.8 on the Vibe Coding Index against 44.8 for GPT-5.4 Nano. Pick GPT-5.4 Nano for work measured by Chess puzzles or LegalBench (Vals AI), where it leads.
Which is cheaper, DeepSeek V4 Flash 0731 or GPT-5.4 Nano?
DeepSeek V4 Flash 0731 costs $0.14 per million input tokens and $0.396 per million output tokens; GPT-5.4 Nano costs $0.20 and $1.25. Per solved SWE-bench Verified task, DeepSeek V4 Flash 0731 costs $0.01 and GPT-5.4 Nano $0.14.
Which has the bigger context window, DeepSeek V4 Flash 0731 or GPT-5.4 Nano?
DeepSeek V4 Flash 0731, with 1.05M tokens against 400K.
How many benchmarks is the DeepSeek V4 Flash 0731 vs GPT-5.4 Nano comparison based on?
38 benchmarks have a result for both models as of October 22, 2026. DeepSeek V4 Flash 0731's coding index rests on 4 independent benchmarks and GPT-5.4 Nano's on 2. Where only one model has a result, the page says so instead of naming a winner.