DeepSeek V4.1 Flash vs GPT-5.1-Codex
DeepSeek V4.1 Flash leads GPT-5.1-Codex on coding, 62.5 to 15.3 on the Vibe Coding Index, and DeepSeek V4.1 Flash costs 11.9x less per output token ($0.84 vs $10.00 per million). Updated October 22, 2026; 12 benchmarks have a result for both.
vs boards won of 12 shared
DeepSeek V4.1 Flash or GPT-5.1-Codex: which to pick
Pick DeepSeek V4.1 Flash for coding: it scores 62.5 on the Vibe Coding Index against 15.3 for GPT-5.1-Codex.
Pick GPT-5.1-Codex for work measured by ALE-Bench, where it leads.
Model ADeepSeek V4.1 FlashDeepSeek62.5/1005 independent benchmarksNo cost per solved taskModel BGPT-5.1-CodexOpenAI15.3/1002 independent benchmarks$0.892 per solved task
- Shared results
- 12
- DeepSeek V4.1 Flash only
- 89
- GPT-5.1-Codex only
- 14
- Like-for-like categories
- 5 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 V4.1 Flash
DeepSeek V4.1 Flash scores 62.5 against 15.3.
5 and 2 benchmarks behind the scores
Intelligence
AA Intelligence Index
DeepSeek V4.1 Flash
DeepSeek V4.1 Flash leads, 24.7 against 23.7.
Same board, both measured
Web design
Design Arena: websites
DeepSeek V4.1 Flash
DeepSeek V4.1 Flash leads, 1308 against 1161.
Same board, both measured
Long documents
Listed context window
DeepSeek V4.1 Flash
DeepSeek V4.1 Flash takes 1.05M tokens against 400K.
Listed by OpenRouter
Everyday cost
1K input + 500 output tokens
DeepSeek V4.1 Flash
DeepSeek V4.1 Flash $0.0006, GPT-5.1-Codex $0.0063 per turn.
List prices
Cost per solved task
One SWE-bench Verified task, solved
No call
Only GPT-5.1-Codex has the number, $0.892.
Directional only
At a glance
- Coding index
- DeepSeek V4.1 Flash 62.5 from 5 benchmarks, GPT-5.1-Codex 15.3 from 2 benchmarks.
- Widest category
- Coding, 39.8 points apart on average over 4 shared benchmarks.
- Widest single gap
- Vibe Code Bench (Vals AI): DeepSeek V4.1 Flash 84.7% against GPT-5.1-Codex 13.1%, 71.6 points apart on a 0 to 100 scale.
- Output price
- DeepSeek V4.1 Flash $0.84 against GPT-5.1-Codex $10.00 per million output tokens, 11.9x apart.
- Context window
- DeepSeek V4.1 Flash takes 1.05M tokens, GPT-5.1-Codex 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 V4.1 Flash | Bars | GPT-5.1-Codex | Ties |
|---|---|---|---|---|
| Coding | 3 | 1 | ||
| Intelligence | 1 | 0 | ||
| Reasoning | 1 | 0 | ||
| Web design | 5 | 0 | ||
| General | 1 | 0 | ||
| All shared boards | 11 | 1 |
CodingLike-for-likeSix of these boards feed the Vibe Coding Index31
| Benchmark | DeepSeek V4.1 Flash | GPT-5.1-Codex | Leader |
|---|---|---|---|
| SWE-bench Verified | Not measured | 66.0% | Only GPT-5.1-Codex measured |
| LiveBench coding | 90.2% | Not measured | Only DeepSeek V4.1 Flash measured |
| LMArena WebDev | 1618 | 1337 | DeepSeek V4.1 Flash |
| LiveCodeBench (Vals AI) | Not measured | 85.5% | Only GPT-5.1-Codex measured |
| Terminal-Bench 4 (Vals AI) | 19.7% | Not measured | Only DeepSeek V4.1 Flash measured |
| Vibe Code Bench (Vals AI) | 84.7% | 13.1% | DeepSeek V4.1 Flash |
| 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 | 84.9% | Only GPT-5.1-Codex measured |
| SciCode | 51.9% | Not measured | Only DeepSeek V4.1 Flash measured |
| Terminal-Bench Hard (Artificial Analysis run) | Not measured | 34.8% | Only GPT-5.1-Codex measured |
| Terminal-Bench | Not measured | 57.8% | Only GPT-5.1-Codex measured |
| FrontierCode | 43.9% | Not measured | Only DeepSeek V4.1 Flash measured |
| ALE-Bench | 1092.3 | 1244.9 | GPT-5.1-Codex |
| LMArena Text: coding | 1502 | Not measured | Only DeepSeek V4.1 Flash measured |
| LMArena Text: software and IT | 1496 | Not measured | Only DeepSeek V4.1 Flash measured |
| LMArena WebDev: React | 1628 | Not measured | Only DeepSeek V4.1 Flash measured |
| LMArena WebDev: HTML | 1612 | 1346 | DeepSeek V4.1 Flash |
| LMArena WebDev: from an image | 1606 | Not measured | Only DeepSeek V4.1 Flash measured |
| Neither model has a result on the other 14 boards here | |||
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index10
| Benchmark | DeepSeek V4.1 Flash | GPT-5.1-Codex | Leader |
|---|---|---|---|
| AA Intelligence Index | 24.7 | 23.7 | DeepSeek V4.1 Flash |
| Epoch Capabilities Index | 155.9 | Not measured | Only DeepSeek V4.1 Flash measured |
Agentic workDirectional onlyPublic boards, shown as published, kept out of the index16 boards, none shared
| Benchmark | DeepSeek V4.1 Flash | GPT-5.1-Codex | Leader |
|---|---|---|---|
| Design Arena: agents building web apps | Not measured | 1018 | Only GPT-5.1-Codex measured |
| Design Arena: agents building full-stack apps | Not measured | 1086 | Only GPT-5.1-Codex measured |
| Design Arena: agents building mobile apps | Not measured | 1191 | Only GPT-5.1-Codex measured |
| 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 | 83.0% | Only GPT-5.1-Codex measured |
| APEX-Agents | 39.5% | Not measured | Only DeepSeek V4.1 Flash measured |
| Neither model has a result on the other 25 boards here | |||
ReasoningLike-for-likePublic boards, shown as published, kept out of the index10
| Benchmark | DeepSeek V4.1 Flash | GPT-5.1-Codex | Leader |
|---|---|---|---|
| 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 |
| GPQA Diamond (Artificial Analysis run) | Not measured | 86.0% | Only GPT-5.1-Codex measured |
| Humanity's Last Exam (Artificial Analysis run) | 39.2% | 25.7% | DeepSeek V4.1 Flash |
| GPQA Diamond (Epoch AI run) | 89.8% | Not measured | Only DeepSeek V4.1 Flash measured |
| ARC-AGI | 94.5% | Not measured | Only DeepSeek V4.1 Flash measured |
| ARC-AGI-2 | 72.9% | Not measured | Only DeepSeek V4.1 Flash measured |
| Chess puzzles | 48.0% | Not measured | Only DeepSeek V4.1 Flash measured |
| Mystery game puzzles | 43.0% | Not measured | Only DeepSeek V4.1 Flash measured |
| LMArena Text: hard prompts | 1483 | Not measured | Only DeepSeek V4.1 Flash measured |
| LMArena Text: expert | 1501 | Not measured | Only DeepSeek V4.1 Flash measured |
| LMArena Text: hard prompts in English | 1488 | Not measured | Only DeepSeek V4.1 Flash measured |
| LMArena Vision: diagrams | 1297 | Not measured | Only DeepSeek V4.1 Flash measured |
| LMArena Vision: homework | 1307 | Not measured | Only DeepSeek V4.1 Flash measured |
| Neither model has a result on the other 8 boards here | |||
MathDirectional onlyPublic boards, shown as published, kept out of the index8 boards, none shared
| Benchmark | DeepSeek V4.1 Flash | GPT-5.1-Codex | Leader |
|---|---|---|---|
| AA Math Index | Not measured | 95.7 | Only GPT-5.1-Codex measured |
| AIME 2025 (Artificial Analysis run) | Not measured | 95.7% | Only GPT-5.1-Codex measured |
| OTIS Mock AIME | 98.3% | Not measured | Only DeepSeek V4.1 Flash measured |
| 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 |
| LMArena Text: math | 1478 | Not measured | Only DeepSeek V4.1 Flash measured |
| LMArena Text: mathematical work | 1485 | Not measured | Only DeepSeek V4.1 Flash measured |
| Neither model has a result on the other 5 boards here | |||
KnowledgeDirectional onlyPublic boards, shown as published, kept out of the index8 boards, none shared
| Benchmark | DeepSeek V4.1 Flash | GPT-5.1-Codex | Leader |
|---|---|---|---|
| LegalBench (Vals AI) | 83.3% | Not measured | Only DeepSeek V4.1 Flash measured |
| MedCode (Vals AI) | 41.2% | Not measured | Only DeepSeek V4.1 Flash measured |
| MMLU Pro (Artificial Analysis run) | Not measured | 86.0% | Only GPT-5.1-Codex measured |
| SimpleQA Verified | 42.9% | Not measured | Only DeepSeek V4.1 Flash measured |
| LMArena Text: science | 1469 | Not measured | Only DeepSeek V4.1 Flash measured |
| LMArena Text: medicine and healthcare | 1484 | Not measured | Only DeepSeek V4.1 Flash measured |
| LMArena Text: legal and government | 1443 | Not measured | Only DeepSeek V4.1 Flash measured |
| LMArena Text: business and finance | 1461 | Not measured | Only DeepSeek V4.1 Flash measured |
| Neither model has a result on the other 10 boards here | |||
Web designLike-for-likePublic boards, shown as published, kept out of the index50
| Benchmark | DeepSeek V4.1 Flash | GPT-5.1-Codex | Leader |
|---|---|---|---|
| Design Arena: websites | 1308 | 1161 | DeepSeek V4.1 Flash |
| Design Arena: UI components | 1312 | 1235 | DeepSeek V4.1 Flash |
| Design Arena: game dev | 1330 | 1137 | DeepSeek V4.1 Flash |
| Design Arena: data viz | 1291 | 1213 | DeepSeek V4.1 Flash |
| Design Arena: 3D | 1355 | Not measured | Only DeepSeek V4.1 Flash measured |
| Design Arena: all code categories | 1319 | 1152 | DeepSeek V4.1 Flash |
| Design Arena: SVG | 1244 | 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 index10
| Benchmark | DeepSeek V4.1 Flash | GPT-5.1-Codex | 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 | 70.0% | Only GPT-5.1-Codex measured |
| Long context reasoning (AA-LCR) | 84.0% | 69.3% | DeepSeek V4.1 Flash |
| DTBench | 89.9% | Not measured | Only DeepSeek V4.1 Flash measured |
| LMCA | 47.0% | Not measured | Only DeepSeek V4.1 Flash 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 | Not measured | Only DeepSeek V4.1 Flash measured |
| LMArena Text: instruction following | 1473 | Not measured | Only DeepSeek V4.1 Flash measured |
| LMArena Text: creative writing | 1437 | Not measured | Only DeepSeek V4.1 Flash measured |
| LMArena Vision | 1278 | Not measured | Only DeepSeek V4.1 Flash measured |
| LMArena Text: English | 1473 | Not measured | Only DeepSeek V4.1 Flash measured |
| LMArena Text: non-English | 1449 | Not measured | Only DeepSeek V4.1 Flash measured |
| LMArena Text: Chinese | 1501 | Not measured | Only DeepSeek V4.1 Flash measured |
| LMArena Text: German | 1470 | Not measured | Only DeepSeek V4.1 Flash measured |
| LMArena Text: Japanese | 1432 | Not measured | Only DeepSeek V4.1 Flash measured |
| 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 | Not measured | Only DeepSeek V4.1 Flash measured |
| LMArena Text: Polish | 1457 | Not measured | Only DeepSeek V4.1 Flash measured |
| LMArena Text: multi-turn | 1461 | Not measured | Only DeepSeek V4.1 Flash measured |
| LMArena Text: longer queries | 1473 | Not measured | Only DeepSeek V4.1 Flash measured |
| LMArena Text: writing and language | 1450 | Not measured | Only DeepSeek V4.1 Flash measured |
| LMArena Text: entertainment and media | 1445 | Not measured | Only DeepSeek V4.1 Flash measured |
| LMArena Vision: English | 1288 | Not measured | Only DeepSeek V4.1 Flash measured |
| 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 13 boards here | |||
Image generationNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
| Benchmark | DeepSeek V4.1 Flash | GPT-5.1-Codex | 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-5.1-Codex$0.0063Fits in one request
DeepSeek V4.1 Flash costs less
Repository review
50K input + 3K output tokens
DeepSeek V4.1 Flash$0.013Fits in one request
GPT-5.1-Codex$0.092Fits in one request
DeepSeek V4.1 Flash costs less
Agent loop
200K input + 10K output tokens
DeepSeek V4.1 Flash$0.050Fits in one request
GPT-5.1-Codex$0.350Fits in one request
DeepSeek V4.1 Flash 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-5.1-Codex |
|---|---|---|
| Maker | DeepSeek | OpenAI |
| Weights | Open weights | No public weights listed |
| Released | September 10, 2026 | November 13, 2025 |
| Context window | 1.05M | 400K |
| Input $/Mtok | $0.21 | $1.25 |
| Output $/Mtok | $0.84 | $10.00 |
| Coding index | 62.5 | 15.3 |
| Independent measurements behind it | 5 | 2 |
| Cost per solved task | Not computable | $0.892 |
| Source | OpenRouter listing | OpenRouter listing |
Questions
Is DeepSeek V4.1 Flash better than GPT-5.1-Codex for coding?
Pick DeepSeek V4.1 Flash for coding: it scores 62.5 on the Vibe Coding Index against 15.3 for GPT-5.1-Codex. Pick GPT-5.1-Codex for work measured by ALE-Bench, where it leads.
Which is cheaper, DeepSeek V4.1 Flash or GPT-5.1-Codex?
DeepSeek V4.1 Flash costs $0.21 per million input tokens and $0.84 per million output tokens; GPT-5.1-Codex costs $1.25 and $10.00. Cost per solved task is known for GPT-5.1-Codex only.
Which has the bigger context window, DeepSeek V4.1 Flash or GPT-5.1-Codex?
DeepSeek V4.1 Flash, with 1.05M tokens against 400K.
How many benchmarks is the DeepSeek V4.1 Flash vs GPT-5.1-Codex comparison based on?
12 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-5.1-Codex's on 2. Where only one model has a result, the page says so instead of naming a winner.