DeepSeek V4.1 Flash vs DeepSeek V4 Pro 0423
Updated October 21, 2026. 68 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 V4.1 Flash for coding: it scores 77.2 on the Vibe Coding Index against 35.3 for DeepSeek V4 Pro 0423.
Pick DeepSeek V4 Pro 0423 when what matters is AA Intelligence Index or GPQA Diamond (Epoch AI run), where it leads.
- Shared results
- 68
- DeepSeek V4.1 Flash only
- 33
- DeepSeek V4 Pro 0423 only
- 15
- Like-for-like categories
- 8 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 V4.1 Flash
DeepSeek V4.1 Flash scores 77.2 against 35.3.
2 and 1 benchmarks behind the scores
Intelligence
AA Intelligence Index
DeepSeek V4 Pro 0423
DeepSeek V4 Pro 0423 leads, 30.4 against 24.7.
Same board, both measured
Agentic work
AA Agentic Index
No call
Only DeepSeek V4 Pro 0423 has a AA Agentic Index result, 26.3.
Directional only
Reasoning
GPQA Diamond
No call
Only DeepSeek V4 Pro 0423 has a GPQA Diamond result, 89.4%.
Directional only
Knowledge
MMLU Pro
No call
Only DeepSeek V4 Pro 0423 has a MMLU Pro result, 87.3%.
Directional only
Web design
Design Arena: websites
DeepSeek V4.1 Flash
DeepSeek V4.1 Flash leads, 1309 against 1235.
Same board, both measured
Long documents
Listed context window
No call
Both take 1.05M tokens.
Listed by OpenRouter
Everyday cost
1K input + 500 output tokens
DeepSeek V4.1 Flash
DeepSeek V4.1 Flash $0.0003, DeepSeek V4 Pro 0423 $0.0019 per turn.
List prices
Cost per solved task
One SWE-bench Verified task, solved
No call
Only DeepSeek V4 Pro 0423 has the number, $0.57.
Directional only
At a glance
- Coding index
- DeepSeek V4.1 Flash 77.2 from 2 benchmarks, DeepSeek V4 Pro 0423 35.3 from 1 benchmark.
- Widest category
- Coding, 17.2 points apart on average over 13 shared benchmarks.
- Widest single gap
- ProofBench: DeepSeek V4.1 Flash 54.0% against DeepSeek V4 Pro 0423 16.0%, 38.0 points apart on a 0 to 100 scale.
- Output price
- DeepSeek V4.1 Flash $0.525 against DeepSeek V4 Pro 0423 $1.9105 per million output tokens, 3.6x apart.
- Context window
- Both take 1.05M tokens.
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 | DeepSeek V4 Pro 0423 | Ties |
|---|---|---|---|---|
| Coding | 13 | 0 | ||
| Intelligence | 1 | 1 | ||
| Agentic work | 4 | 0 | ||
| Reasoning | 5 | 1 | ||
| Math | 6 | 0 | ||
| Knowledge | 4 | 3 | ||
| Web design | 8 | 0 | ||
| General | 16 | 6 | ||
| All shared boards | 57 | 11 |
CodingLike-for-likeFour of these boards feed the Vibe Coding Index130
| Benchmark | DeepSeek V4.1 Flash | DeepSeek V4 Pro 0423 | Leader |
|---|---|---|---|
| LiveBench coding | 90.2% | Not measured | Only DeepSeek V4.1 Flash measured |
| LMArena WebDev | 1618 | 1447 | DeepSeek V4.1 Flash |
| AA Coding Index | Not measured | 59.4 | Only DeepSeek V4 Pro 0423 measured |
| LiveCodeBench (Vals AI) | Not measured | 87.5% | Only DeepSeek V4 Pro 0423 measured |
| SWE-bench Verified (Vals AI) | Not measured | 77.4% | Only DeepSeek V4 Pro 0423 measured |
| Terminal-Bench 4 (Vals AI) | 19.7% | 11.1% | DeepSeek V4.1 Flash |
| Vibe Code Bench (Vals AI) | 84.7% | 49.9% | DeepSeek V4.1 Flash |
| Code migration (Vals AI) | 45.6% | 26.2% | DeepSeek V4.1 Flash |
| ProgramBench (Vals AI) | 0.5% | 0.0% | DeepSeek V4.1 Flash |
| IOI (Vals AI) | 40.3% | Not measured | Only DeepSeek V4.1 Flash measured |
| Terminal-Bench 2.1 (Vals AI) | 74.5% | 50.2% | DeepSeek V4.1 Flash |
| 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% | 51.3% | DeepSeek V4.1 Flash |
| CyberBench (Vals AI) | 73.7% | Not measured | Only DeepSeek V4.1 Flash measured |
| SciCode | 51.9% | Not measured | Only DeepSeek V4.1 Flash measured |
| FrontierCode | 43.9% | 17.6% | DeepSeek V4.1 Flash |
| WeirdML | Not measured | 48.9% | Only DeepSeek V4 Pro 0423 measured |
| ALE-Bench | 1092.3 | 1006.1 | DeepSeek V4.1 Flash |
| LMArena Text: coding | 1502 | 1470 | DeepSeek V4.1 Flash |
| LMArena Text: software and IT | 1496 | 1469 | DeepSeek V4.1 Flash |
| LMArena WebDev: React | 1628 | 1441 | DeepSeek V4.1 Flash |
| LMArena WebDev: HTML | 1612 | 1435 | 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 index11
| Benchmark | DeepSeek V4.1 Flash | DeepSeek V4 Pro 0423 | Leader |
|---|---|---|---|
| AA Intelligence Index | 24.7 | 30.4 | DeepSeek V4 Pro 0423 |
| Epoch Capabilities Index | 155.9 | 149.1 | DeepSeek V4.1 Flash |
Agentic workLike-for-likePublic boards, shown as published, kept out of the index40
| Benchmark | DeepSeek V4.1 Flash | DeepSeek V4 Pro 0423 | Leader |
|---|---|---|---|
| AA Agentic Index | Not measured | 26.3 | Only DeepSeek V4 Pro 0423 measured |
| Design Arena: agents building web apps | Not measured | 1000 | Only DeepSeek V4 Pro 0423 measured |
| Design Arena: agents building full-stack apps | Not measured | 948 | Only DeepSeek V4 Pro 0423 measured |
| Design Arena: agents building Godot games | Not measured | 1059 | Only DeepSeek V4 Pro 0423 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% | 44.1% | DeepSeek V4.1 Flash |
| Tax Agent Bench (Vals AI) | 26.6% | 25.2% | DeepSeek V4.1 Flash |
| Legal Research Bench (Vals AI) | 41.4% | 23.1% | DeepSeek V4.1 Flash |
| Excel Modeling Benchmark (Vals AI) | 57.2% | 51.6% | DeepSeek V4.1 Flash |
| 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 |
| APEX-Agents | 39.5% | Not measured | Only DeepSeek V4.1 Flash measured |
| Vending-Bench 2 | Not measured | $3,285 | Only DeepSeek V4 Pro 0423 measured |
| Neither model has a result on the other 22 boards here | |||
ReasoningLike-for-likePublic boards, shown as published, kept out of the index51
| Benchmark | DeepSeek V4.1 Flash | DeepSeek V4 Pro 0423 | Leader |
|---|---|---|---|
| GPQA Diamond | Not measured | 89.4% | Only DeepSeek V4 Pro 0423 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 |
| Humanity's Last Exam (Artificial Analysis run) | 39.2% | Not measured | Only DeepSeek V4.1 Flash measured |
| GPQA Diamond (Epoch AI run) | 89.8% | 90.9% | DeepSeek V4 Pro 0423 |
| 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% | 19.0% | DeepSeek V4.1 Flash |
| Mystery game puzzles | 43.0% | 17.0% | DeepSeek V4.1 Flash |
| LMArena Text: hard prompts | 1483 | 1461 | DeepSeek V4.1 Flash |
| LMArena Text: expert | 1501 | 1463 | DeepSeek V4.1 Flash |
| LMArena Text: hard prompts in English | 1488 | 1466 | 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 |
| Neither model has a result on the other 7 boards here | |||
MathLike-for-likePublic boards, shown as published, kept out of the index60
| Benchmark | DeepSeek V4.1 Flash | DeepSeek V4 Pro 0423 | Leader |
|---|---|---|---|
| OTIS Mock AIME | 98.3% | 96.7% | DeepSeek V4.1 Flash |
| FrontierMath, tiers 1 to 3 | 67.4% | 45.3% | DeepSeek V4.1 Flash |
| FrontierMath, tier 4 | 26.8% | 2.4% | DeepSeek V4.1 Flash |
| ProofBench | 54.0% | 16.0% | DeepSeek V4.1 Flash |
| LMArena Text: math | 1478 | 1443 | DeepSeek V4.1 Flash |
| LMArena Text: mathematical work | 1485 | 1455 | DeepSeek V4.1 Flash |
| Neither model has a result on the other 7 boards here | |||
KnowledgeLike-for-likePublic boards, shown as published, kept out of the index43
| Benchmark | DeepSeek V4.1 Flash | DeepSeek V4 Pro 0423 | Leader |
|---|---|---|---|
| MMLU Pro | Not measured | 87.3% | Only DeepSeek V4 Pro 0423 measured |
| LegalBench (Vals AI) | 83.3% | 80.3% | DeepSeek V4.1 Flash |
| CaseLaw (Vals AI) | Not measured | 59.4% | Only DeepSeek V4 Pro 0423 measured |
| CorpFin (Vals AI) | Not measured | 61.4% | Only DeepSeek V4 Pro 0423 measured |
| TaxEval (Vals AI) | Not measured | 72.1% | Only DeepSeek V4 Pro 0423 measured |
| MedCode (Vals AI) | 41.2% | 40.5% | DeepSeek V4.1 Flash |
| SimpleQA Verified | 42.9% | 47.0% | DeepSeek V4 Pro 0423 |
| LMArena Text: science | 1469 | 1470 | DeepSeek V4 Pro 0423 |
| LMArena Text: medicine and healthcare | 1484 | 1466 | DeepSeek V4.1 Flash |
| LMArena Text: legal and government | 1443 | 1464 | DeepSeek V4 Pro 0423 |
| LMArena Text: business and finance | 1461 | 1443 | DeepSeek V4.1 Flash |
| Neither model has a result on the other 6 boards here | |||
Web designLike-for-likePublic boards, shown as published, kept out of the index80
| Benchmark | DeepSeek V4.1 Flash | DeepSeek V4 Pro 0423 | Leader |
|---|---|---|---|
| Design Arena: websites | 1309 | 1235 | DeepSeek V4.1 Flash |
| Design Arena: UI components | 1314 | 1221 | DeepSeek V4.1 Flash |
| Design Arena: game dev | 1331 | 1229 | DeepSeek V4.1 Flash |
| Design Arena: data viz | 1290 | 1203 | DeepSeek V4.1 Flash |
| Design Arena: 3D | 1356 | 1254 | DeepSeek V4.1 Flash |
| Design Arena: all code categories | 1320 | 1240 | DeepSeek V4.1 Flash |
| Design Arena: SVG | 1243 | 1139 | DeepSeek V4.1 Flash |
| Design Arena: ASCII art | 1265 | 1148 | DeepSeek V4.1 Flash |
| LiveBench design | 79.2% | Not measured | Only DeepSeek V4.1 Flash measured |
GeneralLike-for-likePublic boards, shown as published, kept out of the index166
| Benchmark | DeepSeek V4.1 Flash | DeepSeek V4 Pro 0423 | Leader |
|---|---|---|---|
| LiveBench data analysis | 79.3% | Not measured | Only DeepSeek V4.1 Flash measured |
| Public Benefits Bench (Vals AI) | 64.3% | 62.9% | DeepSeek V4.1 Flash |
| SAGE (Vals AI) | 47.9% | Not measured | Only DeepSeek V4.1 Flash measured |
| MedScribe (Vals AI) | 85.5% | 75.1% | DeepSeek V4.1 Flash |
| Long context reasoning (AA-LCR) | 84.0% | Not measured | Only DeepSeek V4.1 Flash measured |
| DTBench | 89.9% | 90.7% | DeepSeek V4 Pro 0423 |
| LMCA | 47.0% | 41.2% | DeepSeek V4.1 Flash |
| Surface Evolver Bench | 46.3% | 40.0% | DeepSeek V4.1 Flash |
| Furniture assembly | 34.2% | Not measured | Only DeepSeek V4.1 Flash measured |
| CL-bench Life | Not measured | 13.5% | Only DeepSeek V4 Pro 0423 measured |
| LMArena Text | 1464 | 1451 | DeepSeek V4.1 Flash |
| LMArena Text: instruction following | 1473 | 1445 | DeepSeek V4.1 Flash |
| LMArena Text: creative writing | 1437 | 1446 | DeepSeek V4 Pro 0423 |
| LMArena Vision | 1278 | Not measured | Only DeepSeek V4.1 Flash measured |
| LMArena Text: English | 1473 | 1459 | DeepSeek V4.1 Flash |
| LMArena Text: non-English | 1449 | 1439 | DeepSeek V4.1 Flash |
| LMArena Text: Chinese | 1501 | 1481 | DeepSeek V4.1 Flash |
| LMArena Text: German | 1470 | 1458 | DeepSeek V4.1 Flash |
| LMArena Text: Japanese | 1432 | 1446 | DeepSeek V4 Pro 0423 |
| LMArena Text: Korean | 1436 | 1409 | DeepSeek V4.1 Flash |
| LMArena Text: French | 1465 | 1473 | DeepSeek V4 Pro 0423 |
| LMArena Text: Spanish | 1459 | 1457 | DeepSeek V4.1 Flash |
| LMArena Text: Russian | 1467 | 1453 | DeepSeek V4.1 Flash |
| LMArena Text: Polish | 1457 | 1461 | DeepSeek V4 Pro 0423 |
| LMArena Text: multi-turn | 1461 | 1468 | DeepSeek V4 Pro 0423 |
| LMArena Text: longer queries | 1473 | 1458 | DeepSeek V4.1 Flash |
| LMArena Text: writing and language | 1450 | 1447 | DeepSeek V4.1 Flash |
| LMArena Text: entertainment and media | 1445 | 1431 | DeepSeek V4.1 Flash |
| 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 | DeepSeek V4 Pro 0423 | 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 costs less
Repository review
50K input + 3K output tokens
DeepSeek V4.1 Flash costs less
Agent loop
200K input + 10K output tokens
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 | DeepSeek V4 Pro 0423 |
|---|---|---|
| Maker | DeepSeek | DeepSeek |
| Weights | Open weights | Open weights |
| Released | September 10, 2026 | April 24, 2026 |
| Context window | 1.05M | 1.05M |
| Input $/Mtok | $0.049 | $0.9553 |
| Output $/Mtok | $0.525 | $1.9105 |
| Coding index | 77.2 | 35.3 |
| Independent measurements behind it | 2 | 1 |
| Cost per solved task | Not computable | $0.57 |
| Source | OpenRouter listing | OpenRouter listing |
Questions
Is DeepSeek V4.1 Flash better than DeepSeek V4 Pro 0423 for coding?
Pick DeepSeek V4.1 Flash for coding: it scores 77.2 on the Vibe Coding Index against 35.3 for DeepSeek V4 Pro 0423. Pick DeepSeek V4 Pro 0423 when what matters is AA Intelligence Index or GPQA Diamond (Epoch AI run), where it leads.
Which is cheaper, DeepSeek V4.1 Flash or DeepSeek V4 Pro 0423?
DeepSeek V4.1 Flash costs $0.049 per million input tokens and $0.525 per million output tokens; DeepSeek V4 Pro 0423 costs $0.9553 and $1.9105. Cost per solved task is known for DeepSeek V4 Pro 0423 only.
Which has the bigger context window, DeepSeek V4.1 Flash or DeepSeek V4 Pro 0423?
Neither: both take 1.05M tokens.
How many benchmarks is the DeepSeek V4.1 Flash vs DeepSeek V4 Pro 0423 comparison based on?
68 benchmarks have a result for both models as of October 21, 2026. DeepSeek V4.1 Flash's coding index rests on 2 independent benchmarks and DeepSeek V4 Pro 0423's on 1. Where only one model has a result, the page says so instead of naming a winner.