DeepSeek V4.1 Flash vs Qwen3.5-Flash
DeepSeek V4.1 Flash leads Qwen3.5-Flash on coding, 62.5 to 41.1 on the Vibe Coding Index, and Qwen3.5-Flash costs 3.2x less per output token ($0.26 vs $0.84 per million). Updated October 22, 2026; 45 benchmarks have a result for both.
DeepSeek V4.1 Flash or Qwen3.5-Flash: which to pick
Pick DeepSeek V4.1 Flash for coding: it scores 62.5 on the Vibe Coding Index against 41.1 for Qwen3.5-Flash.
Pick Qwen3.5-Flash for output tokens 3.2x cheaper ($0.26 vs $0.84 per million) and work measured by LegalBench (Vals AI), where it leads.
- Shared results
- 45
- DeepSeek V4.1 Flash only
- 56
- Qwen3.5-Flash only
- 10
- Like-for-like categories
- 6 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 41.1.
5 and 2 benchmarks behind the scores
Intelligence
AA Intelligence Index
No call
Only DeepSeek V4.1 Flash has a AA Intelligence Index result, 24.7.
Directional only
Reasoning
GPQA Diamond
No call
Only Qwen3.5-Flash has a GPQA Diamond result, 82.8%.
Directional only
Math
AIME
No call
Only Qwen3.5-Flash has a AIME result, 92.5%.
Directional only
Knowledge
MMLU Pro
No call
Only Qwen3.5-Flash has a MMLU Pro result, 84.1%.
Directional only
Web design
Design Arena: websites
No call
Only DeepSeek V4.1 Flash has a Design Arena: websites result, 1308.
Directional only
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
Qwen3.5-Flash
DeepSeek V4.1 Flash $0.0006, Qwen3.5-Flash $0.0002 per turn.
List prices
Cost per solved task
One SWE-bench Verified task, solved
No call
Only Qwen3.5-Flash has the number, $0.40.
Directional only
At a glance
- Coding index
- DeepSeek V4.1 Flash 62.5 from 5 benchmarks, Qwen3.5-Flash 41.1 from 2 benchmarks.
- Widest category
- Coding, 37.1 points apart on average over 6 shared benchmarks.
- Widest single gap
- LMArena WebDev: React: DeepSeek V4.1 Flash 1628 against Qwen3.5-Flash 1229, 61.8 points apart on a 0 to 100 scale.
- Output price
- DeepSeek V4.1 Flash $0.84 against Qwen3.5-Flash $0.26 per million output tokens, 3.2x apart.
- Context window
- DeepSeek V4.1 Flash takes 1.05M tokens, Qwen3.5-Flash 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 | Qwen3.5-Flash | Ties |
|---|---|---|---|---|
| Coding | 6 | 0 | ||
| Intelligence | 1 | 0 | ||
| Reasoning | 6 | 0 | ||
| Math | 4 | 0 | ||
| Knowledge | 6 | 1 | ||
| General | 21 | 0 | ||
| All shared boards | 44 | 1 |
CodingLike-for-likeSix of these boards feed the Vibe Coding Index60
| Benchmark | DeepSeek V4.1 Flash | Qwen3.5-Flash | Leader |
|---|---|---|---|
| LiveBench coding | 90.2% | Not measured | Only DeepSeek V4.1 Flash measured |
| LMArena WebDev | 1618 | 1244 | DeepSeek V4.1 Flash |
| LiveCodeBench (Vals AI) | Not measured | 83.3% | Only Qwen3.5-Flash measured |
| SWE-bench Verified (Vals AI) | Not measured | 64.4% | Only Qwen3.5-Flash 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 |
| SciCode | 51.9% | Not measured | Only DeepSeek V4.1 Flash measured |
| FrontierCode | 43.9% | Not measured | Only DeepSeek V4.1 Flash measured |
| ALE-Bench | 1092.3 | 265.9 | DeepSeek V4.1 Flash |
| LMArena Text: coding | 1502 | 1412 | DeepSeek V4.1 Flash |
| LMArena Text: software and IT | 1496 | 1416 | DeepSeek V4.1 Flash |
| LMArena WebDev: React | 1628 | 1229 | DeepSeek V4.1 Flash |
| LMArena WebDev: HTML | 1612 | 1291 | 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 17 boards here | |||
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index10
| Benchmark | DeepSeek V4.1 Flash | Qwen3.5-Flash | Leader |
|---|---|---|---|
| AA Intelligence Index | 24.7 | Not measured | Only DeepSeek V4.1 Flash measured |
| Epoch Capabilities Index | 155.9 | 143.5 | DeepSeek V4.1 Flash |
Agentic workDirectional onlyPublic boards, shown as published, kept out of the index12 boards, none shared
| Benchmark | DeepSeek V4.1 Flash | Qwen3.5-Flash | 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 |
| APEX-Agents | 39.5% | Not measured | Only DeepSeek V4.1 Flash measured |
| Neither model has a result on the other 29 boards here | |||
ReasoningLike-for-likePublic boards, shown as published, kept out of the index60
| Benchmark | DeepSeek V4.1 Flash | Qwen3.5-Flash | Leader |
|---|---|---|---|
| GPQA Diamond | Not measured | 82.8% | Only Qwen3.5-Flash 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 | 81.9% | Only Qwen3.5-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% | 82.3% | DeepSeek V4.1 Flash |
| 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% | 14.0% | DeepSeek V4.1 Flash |
| Mystery game puzzles | 43.0% | 20.0% | DeepSeek V4.1 Flash |
| LMArena Text: hard prompts | 1483 | 1403 | DeepSeek V4.1 Flash |
| LMArena Text: expert | 1501 | 1407 | DeepSeek V4.1 Flash |
| LMArena Text: hard prompts in English | 1488 | 1409 | 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 index40
| Benchmark | DeepSeek V4.1 Flash | Qwen3.5-Flash | Leader |
|---|---|---|---|
| AIME | Not measured | 92.5% | Only Qwen3.5-Flash measured |
| OTIS Mock AIME | 98.3% | 84.4% | DeepSeek V4.1 Flash |
| FrontierMath, tiers 1 to 3 | 67.4% | 18.2% | DeepSeek V4.1 Flash |
| 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 | 1407 | DeepSeek V4.1 Flash |
| LMArena Text: mathematical work | 1485 | 1413 | DeepSeek V4.1 Flash |
| Neither model has a result on the other 6 boards here | |||
KnowledgeLike-for-likePublic boards, shown as published, kept out of the index61
| Benchmark | DeepSeek V4.1 Flash | Qwen3.5-Flash | Leader |
|---|---|---|---|
| MMLU Pro | Not measured | 84.1% | Only Qwen3.5-Flash measured |
| LegalBench (Vals AI) | 83.3% | 84.3% | Qwen3.5-Flash |
| CaseLaw (Vals AI) | Not measured | 56.0% | Only Qwen3.5-Flash measured |
| CorpFin (Vals AI) | Not measured | 63.6% | Only Qwen3.5-Flash measured |
| TaxEval (Vals AI) | Not measured | 72.2% | Only Qwen3.5-Flash measured |
| MortgageTax (Vals AI) | Not measured | 67.4% | Only Qwen3.5-Flash measured |
| MedCode (Vals AI) | 41.2% | 33.0% | DeepSeek V4.1 Flash |
| SimpleQA Verified | 42.9% | 20.3% | DeepSeek V4.1 Flash |
| LMArena Text: science | 1469 | 1415 | DeepSeek V4.1 Flash |
| LMArena Text: medicine and healthcare | 1484 | 1407 | DeepSeek V4.1 Flash |
| LMArena Text: legal and government | 1443 | 1398 | DeepSeek V4.1 Flash |
| LMArena Text: business and finance | 1461 | 1394 | DeepSeek V4.1 Flash |
| Neither model has a result on the other 6 boards here | |||
Web designDirectional onlyPublic boards, shown as published, kept out of the index9 boards, none shared
| Benchmark | DeepSeek V4.1 Flash | Qwen3.5-Flash | Leader |
|---|---|---|---|
| Design Arena: websites | 1308 | Not measured | Only DeepSeek V4.1 Flash measured |
| Design Arena: UI components | 1312 | Not measured | Only DeepSeek V4.1 Flash measured |
| Design Arena: game dev | 1330 | Not measured | Only DeepSeek V4.1 Flash measured |
| Design Arena: data viz | 1291 | Not measured | Only DeepSeek V4.1 Flash measured |
| Design Arena: 3D | 1355 | Not measured | Only DeepSeek V4.1 Flash measured |
| Design Arena: all code categories | 1320 | Not measured | Only DeepSeek V4.1 Flash measured |
| 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 index210
| Benchmark | DeepSeek V4.1 Flash | Qwen3.5-Flash | 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% | 42.5% | DeepSeek V4.1 Flash |
| MedScribe (Vals AI) | 85.5% | 70.6% | DeepSeek V4.1 Flash |
| Long context reasoning (AA-LCR) | 84.0% | Not measured | Only DeepSeek V4.1 Flash measured |
| DTBench | 89.9% | 82.9% | DeepSeek V4.1 Flash |
| LMCA | 47.0% | 29.1% | 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 | 1397 | DeepSeek V4.1 Flash |
| LMArena Text: instruction following | 1473 | 1374 | DeepSeek V4.1 Flash |
| LMArena Text: creative writing | 1437 | 1343 | DeepSeek V4.1 Flash |
| LMArena Vision | 1278 | Not measured | Only DeepSeek V4.1 Flash measured |
| LMArena Text: English | 1473 | 1404 | DeepSeek V4.1 Flash |
| LMArena Text: non-English | 1449 | 1385 | DeepSeek V4.1 Flash |
| LMArena Text: Chinese | 1501 | 1445 | DeepSeek V4.1 Flash |
| LMArena Text: German | 1470 | 1390 | DeepSeek V4.1 Flash |
| LMArena Text: Japanese | 1432 | 1369 | DeepSeek V4.1 Flash |
| LMArena Text: Korean | 1436 | 1344 | DeepSeek V4.1 Flash |
| LMArena Text: French | 1465 | 1413 | DeepSeek V4.1 Flash |
| LMArena Text: Spanish | 1459 | 1400 | DeepSeek V4.1 Flash |
| LMArena Text: Russian | 1467 | 1380 | DeepSeek V4.1 Flash |
| LMArena Text: Polish | 1457 | 1376 | DeepSeek V4.1 Flash |
| LMArena Text: multi-turn | 1461 | 1393 | DeepSeek V4.1 Flash |
| LMArena Text: longer queries | 1473 | 1392 | DeepSeek V4.1 Flash |
| LMArena Text: writing and language | 1450 | 1369 | DeepSeek V4.1 Flash |
| LMArena Text: entertainment and media | 1445 | 1347 | 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 14 boards here | |||
Image generationNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
| Benchmark | DeepSeek V4.1 Flash | Qwen3.5-Flash | 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
Qwen3.5-Flash costs less
Repository review
50K input + 3K output tokens
Qwen3.5-Flash costs less
Agent loop
200K input + 10K output tokens
Qwen3.5-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 | Qwen3.5-Flash |
|---|---|---|
| Maker | DeepSeek | Qwen |
| Weights | Open weights | No public weights listed |
| Released | September 10, 2026 | February 25, 2026 |
| Context window | 1.05M | 1M |
| Input $/Mtok | $0.2225 | $0.065 |
| Output $/Mtok | $0.84 | $0.26 |
| Coding index | 62.5 | 41.1 |
| Independent measurements behind it | 5 | 2 |
| Cost per solved task | Not computable | $0.40 |
| Source | OpenRouter listing | OpenRouter listing |
Questions
Is DeepSeek V4.1 Flash better than Qwen3.5-Flash for coding?
Pick DeepSeek V4.1 Flash for coding: it scores 62.5 on the Vibe Coding Index against 41.1 for Qwen3.5-Flash. Pick Qwen3.5-Flash for output tokens 3.2x cheaper ($0.26 vs $0.84 per million) and work measured by LegalBench (Vals AI), where it leads.
Which is cheaper, DeepSeek V4.1 Flash or Qwen3.5-Flash?
DeepSeek V4.1 Flash costs $0.2225 per million input tokens and $0.84 per million output tokens; Qwen3.5-Flash costs $0.065 and $0.26. Cost per solved task is known for Qwen3.5-Flash only.
Which has the bigger context window, DeepSeek V4.1 Flash or Qwen3.5-Flash?
DeepSeek V4.1 Flash, with 1.05M tokens against 1M.
How many benchmarks is the DeepSeek V4.1 Flash vs Qwen3.5-Flash 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 Qwen3.5-Flash's on 2. Where only one model has a result, the page says so instead of naming a winner.