DeepSeek V4.1 Flash vs Qwen3.7 Max
DeepSeek V4.1 Flash leads Qwen3.7 Max on coding, 62.5 to 54.1 on the Vibe Coding Index, and DeepSeek V4.1 Flash costs 5.3x less per output token ($0.84 vs $4.425 per million). Updated October 22, 2026; 37 benchmarks have a result for both.
vs boards won of 37 shared
DeepSeek V4.1 Flash or Qwen3.7 Max: which to pick
Pick DeepSeek V4.1 Flash for coding: it scores 62.5 on the Vibe Coding Index against 54.1 for Qwen3.7 Max.
Pick Qwen3.7 Max for work measured by ALE-Bench or AA Intelligence Index, where it leads.
Model ADeepSeek V4.1 FlashDeepSeek62.5/1005 independent benchmarksNo cost per solved taskModel BQwen3.7 MaxQwen54.1/1003 independent benchmarks$4.69 per solved task
- Shared results
- 37
- DeepSeek V4.1 Flash only
- 64
- Qwen3.7 Max only
- 22
- Like-for-like categories
- 8 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 54.1.
5 and 3 benchmarks behind the scores
Intelligence
AA Intelligence Index
Qwen3.7 Max
Qwen3.7 Max leads, 29.5 against 24.7.
Same board, both measured
Agentic work
AA Agentic Index
No call
Only Qwen3.7 Max has a AA Agentic Index result, 22.5.
Directional only
Reasoning
GPQA Diamond
No call
Only Qwen3.7 Max has a GPQA Diamond result, 90.2%.
Directional only
Knowledge
MMLU Pro
No call
Only Qwen3.7 Max has a MMLU Pro result, 89.3%.
Directional only
Web design
Design Arena: websites
DeepSeek V4.1 Flash
DeepSeek V4.1 Flash leads, 1308 against 1274.
Same board, both measured
Long documents
Listed context window
DeepSeek V4.1 Flash
DeepSeek V4.1 Flash takes 1.05M tokens against 1M.
Listed by OpenRouter
Everyday cost
1K input + 500 output tokens
DeepSeek V4.1 Flash
DeepSeek V4.1 Flash $0.0006, Qwen3.7 Max $0.0037 per turn.
List prices
Cost per solved task
One SWE-bench Verified task, solved
No call
Only Qwen3.7 Max has the number, $4.69.
Directional only
At a glance
- Coding index
- DeepSeek V4.1 Flash 62.5 from 5 benchmarks, Qwen3.7 Max 54.1 from 3 benchmarks.
- Widest category
- Coding, 16.6 points apart on average over 8 shared benchmarks.
- Widest single gap
- Vibe Code Bench (Vals AI): DeepSeek V4.1 Flash 84.7% against Qwen3.7 Max 47.7%, 37.1 points apart on a 0 to 100 scale.
- Output price
- DeepSeek V4.1 Flash $0.84 against Qwen3.7 Max $4.425 per million output tokens, 5.3x apart.
- Context window
- DeepSeek V4.1 Flash takes 1.05M tokens, Qwen3.7 Max 1M.
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 | Qwen3.7 Max | Ties |
|---|---|---|---|---|
| Coding | 7 | 1 | ||
| Intelligence | 1 | 1 | ||
| Agentic work | 4 | 0 | ||
| Reasoning | 2 | 2 | ||
| Math | 3 | 1 | ||
| Knowledge | 1 | 2 | ||
| Web design | 8 | 0 | ||
| General | 3 | 1 | ||
| All shared boards | 29 | 8 |
CodingLike-for-likeSix of these boards feed the Vibe Coding Index71
| Benchmark | DeepSeek V4.1 Flash | Qwen3.7 Max | Leader |
|---|---|---|---|
| LiveBench coding | 90.2% | Not measured | Only DeepSeek V4.1 Flash measured |
| LMArena WebDev | 1618 | 1515 | DeepSeek V4.1 Flash |
| AA Coding Index | Not measured | 66.0 | Only Qwen3.7 Max measured |
| LiveCodeBench (Vals AI) | Not measured | 87.1% | Only Qwen3.7 Max measured |
| SWE-bench Verified (Vals AI) | Not measured | 68.8% | Only Qwen3.7 Max measured |
| Terminal-Bench 4 (Vals AI) | 19.7% | Not measured | Only DeepSeek V4.1 Flash measured |
| Vibe Code Bench (Vals AI) | 84.7% | 47.7% | DeepSeek V4.1 Flash |
| Code migration (Vals AI) | 45.6% | 13.1% | DeepSeek V4.1 Flash |
| 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% | 61.0% | 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% | Not measured | Only DeepSeek V4.1 Flash measured |
| CyberBench (Vals AI) | 73.7% | Not measured | Only DeepSeek V4.1 Flash measured |
| SciCode | 51.9% | 49.5% | DeepSeek V4.1 Flash |
| Terminal-Bench Hard (Artificial Analysis run) | Not measured | 50.8% | Only Qwen3.7 Max measured |
| FrontierCode | 43.9% | Not measured | Only DeepSeek V4.1 Flash measured |
| ALE-Bench | 1092.3 | 1189.4 | Qwen3.7 Max |
| 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 | 1514 | DeepSeek V4.1 Flash |
| LMArena WebDev: HTML | 1612 | 1512 | 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 15 boards here | |||
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index11
| Benchmark | DeepSeek V4.1 Flash | Qwen3.7 Max | Leader |
|---|---|---|---|
| AA Intelligence Index | 24.7 | 29.5 | Qwen3.7 Max |
| Epoch Capabilities Index | 155.9 | 154.0 | DeepSeek V4.1 Flash |
Agentic workLike-for-likePublic boards, shown as published, kept out of the index40
| Benchmark | DeepSeek V4.1 Flash | Qwen3.7 Max | Leader |
|---|---|---|---|
| AA Agentic Index | Not measured | 22.5 | Only Qwen3.7 Max measured |
| Design Arena: agents building web apps | Not measured | 1208 | Only Qwen3.7 Max measured |
| Design Arena: agents building full-stack apps | Not measured | 1191 | Only Qwen3.7 Max measured |
| Design Arena: agents building mobile apps | Not measured | 1155 | Only Qwen3.7 Max measured |
| Design Arena: agents building Android apps | Not measured | 1159 | Only Qwen3.7 Max measured |
| Design Arena: agents building Godot games | Not measured | 1187 | Only Qwen3.7 Max measured |
| Design Arena: agents building games | Not measured | 1161 | Only Qwen3.7 Max measured |
| Design Arena: HTML slides | Not measured | 1108 | Only Qwen3.7 Max measured |
| Design Arena: PowerPoint slides | Not measured | 1171 | Only Qwen3.7 Max 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% | 47.8% | DeepSeek V4.1 Flash |
| Tax Agent Bench (Vals AI) | 26.6% | 15.8% | DeepSeek V4.1 Flash |
| Legal Research Bench (Vals AI) | 41.4% | 25.5% | DeepSeek V4.1 Flash |
| Excel Modeling Benchmark (Vals AI) | 57.2% | 57.0% | 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 |
| τ²-Bench Telecom | Not measured | 94.7% | Only Qwen3.7 Max measured |
| APEX-Agents | 39.5% | Not measured | Only DeepSeek V4.1 Flash measured |
| Neither model has a result on the other 19 boards here | |||
ReasoningLike-for-likePublic boards, shown as published, kept out of the index22
| Benchmark | DeepSeek V4.1 Flash | Qwen3.7 Max | Leader |
|---|---|---|---|
| GPQA Diamond | Not measured | 90.2% | Only Qwen3.7 Max 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 |
| GPQA Diamond (Artificial Analysis run) | Not measured | 92.3% | Only Qwen3.7 Max measured |
| Humanity's Last Exam (Artificial Analysis run) | 39.2% | 40.5% | Qwen3.7 Max |
| GPQA Diamond (Epoch AI run) | 89.8% | 90.9% | Qwen3.7 Max |
| 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 |
| SimpleBench | Not measured | 70.4% | Only Qwen3.7 Max measured |
| Chess puzzles | 48.0% | 26.0% | DeepSeek V4.1 Flash |
| Mystery game puzzles | 43.0% | 32.0% | DeepSeek V4.1 Flash |
| EBR-bench | Not measured | 9.5% | Only Qwen3.7 Max 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 5 boards here | |||
MathLike-for-likePublic boards, shown as published, kept out of the index31
| Benchmark | DeepSeek V4.1 Flash | Qwen3.7 Max | Leader |
|---|---|---|---|
| OTIS Mock AIME | 98.3% | 95.6% | DeepSeek V4.1 Flash |
| FrontierMath, tiers 1 to 3 | 67.4% | 64.6% | DeepSeek V4.1 Flash |
| FrontierMath, tier 4 | 26.8% | 34.1% | Qwen3.7 Max |
| ProofBench | 54.0% | 26.0% | DeepSeek V4.1 Flash |
| 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 7 boards here | |||
KnowledgeLike-for-likePublic boards, shown as published, kept out of the index12
| Benchmark | DeepSeek V4.1 Flash | Qwen3.7 Max | Leader |
|---|---|---|---|
| MMLU Pro | Not measured | 89.3% | Only Qwen3.7 Max measured |
| LegalBench (Vals AI) | 83.3% | 84.9% | Qwen3.7 Max |
| CorpFin (Vals AI) | Not measured | 63.7% | Only Qwen3.7 Max measured |
| TaxEval (Vals AI) | Not measured | 75.3% | Only Qwen3.7 Max measured |
| MedCode (Vals AI) | 41.2% | 38.8% | DeepSeek V4.1 Flash |
| SimpleQA Verified | 42.9% | 55.8% | Qwen3.7 Max |
| 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 8 boards here | |||
Web designLike-for-likePublic boards, shown as published, kept out of the index80
| Benchmark | DeepSeek V4.1 Flash | Qwen3.7 Max | Leader |
|---|---|---|---|
| Design Arena: websites | 1308 | 1274 | DeepSeek V4.1 Flash |
| Design Arena: UI components | 1312 | 1267 | DeepSeek V4.1 Flash |
| Design Arena: game dev | 1330 | 1264 | DeepSeek V4.1 Flash |
| Design Arena: data viz | 1291 | 1275 | DeepSeek V4.1 Flash |
| Design Arena: 3D | 1355 | 1265 | DeepSeek V4.1 Flash |
| Design Arena: all code categories | 1320 | 1275 | DeepSeek V4.1 Flash |
| Design Arena: SVG | 1245 | 1216 | DeepSeek V4.1 Flash |
| Design Arena: ASCII art | 1265 | 1211 | 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 index31
| Benchmark | DeepSeek V4.1 Flash | Qwen3.7 Max | 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% | 79.4% | DeepSeek V4.1 Flash |
| IFBench | Not measured | 80.5% | Only Qwen3.7 Max measured |
| Long context reasoning (AA-LCR) | 84.0% | 79.0% | DeepSeek V4.1 Flash |
| DTBench | 89.9% | 92.3% | Qwen3.7 Max |
| LMCA | 47.0% | 44.0% | DeepSeek V4.1 Flash |
| 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 | Qwen3.7 Max | 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
Qwen3.7 Max$0.0037Fits in one request
DeepSeek V4.1 Flash costs less
Repository review
50K input + 3K output tokens
DeepSeek V4.1 Flash$0.014Fits in one request
Qwen3.7 Max$0.087Fits in one request
DeepSeek V4.1 Flash costs less
Agent loop
200K input + 10K output tokens
DeepSeek V4.1 Flash$0.053Fits in one request
Qwen3.7 Max$0.339Fits 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 | Qwen3.7 Max |
|---|---|---|
| Maker | DeepSeek | Qwen |
| Weights | Open weights | No public weights listed |
| Released | September 10, 2026 | May 21, 2026 |
| Context window | 1.05M | 1M |
| Input $/Mtok | $0.2225 | $1.475 |
| Output $/Mtok | $0.84 | $4.425 |
| Coding index | 62.5 | 54.1 |
| Independent measurements behind it | 5 | 3 |
| Cost per solved task | Not computable | $4.69 |
| Source | OpenRouter listing | OpenRouter listing |
Questions
Is DeepSeek V4.1 Flash better than Qwen3.7 Max for coding?
Pick DeepSeek V4.1 Flash for coding: it scores 62.5 on the Vibe Coding Index against 54.1 for Qwen3.7 Max. Pick Qwen3.7 Max for work measured by ALE-Bench or AA Intelligence Index, where it leads.
Which is cheaper, DeepSeek V4.1 Flash or Qwen3.7 Max?
DeepSeek V4.1 Flash costs $0.2225 per million input tokens and $0.84 per million output tokens; Qwen3.7 Max costs $1.475 and $4.425. Cost per solved task is known for Qwen3.7 Max only.
Which has the bigger context window, DeepSeek V4.1 Flash or Qwen3.7 Max?
DeepSeek V4.1 Flash, with 1.05M tokens against 1M.
How many benchmarks is the DeepSeek V4.1 Flash vs Qwen3.7 Max comparison based on?
37 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 Qwen3.7 Max's on 3. Where only one model has a result, the page says so instead of naming a winner.