DeepSeek V4 Flash 0731 vs Qwen3.6 Plus
DeepSeek V4 Flash 0731 leads Qwen3.6 Plus on coding, 51.8 to 44.1 on the Vibe Coding Index, and DeepSeek V4 Flash 0731 costs 7.0x less per output token ($0.28 vs $1.95 per million). Updated October 21, 2026; 40 benchmarks have a result for both.
DeepSeek V4 Flash 0731 or Qwen3.6 Plus: which to pick
Pick DeepSeek V4 Flash 0731 for coding: it scores 51.8 on the Vibe Coding Index against 44.1 for Qwen3.6 Plus.
Pick Qwen3.6 Plus for work measured by MMLU Pro or LegalBench (Vals AI), where it leads.
- Shared results
- 40
- DeepSeek V4 Flash 0731 only
- 15
- Qwen3.6 Plus only
- 43
- 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 Flash 0731
DeepSeek V4 Flash 0731 scores 51.8 against 44.1.
4 and 3 benchmarks behind the scores
Intelligence
AA Intelligence Index
DeepSeek V4 Flash 0731
DeepSeek V4 Flash 0731 leads, 34.3 against 27.0.
Same board, both measured
Agentic work
AA Agentic Index
No call
Only DeepSeek V4 Flash 0731 has a AA Agentic Index result, 41.0.
Directional only
Reasoning
GPQA Diamond
DeepSeek V4 Flash 0731
DeepSeek V4 Flash 0731 leads, 89.9% against 87.4%.
Same board, both measured
Math
AIME
No call
Only Qwen3.6 Plus has a AIME result, 94.6%.
Directional only
Knowledge
MMLU Pro
Qwen3.6 Plus
Qwen3.6 Plus leads, 87.7% against 86.2%.
Same board, both measured
Web design
Design Arena: websites
Qwen3.6 Plus
Qwen3.6 Plus leads, 1243 against 1238.
Same board, both measured
Long documents
Listed context window
DeepSeek V4 Flash 0731
DeepSeek V4 Flash 0731 takes 1.05M tokens against 1M.
Listed by OpenRouter
Everyday cost
1K input + 500 output tokens
DeepSeek V4 Flash 0731
DeepSeek V4 Flash 0731 $0.0003, Qwen3.6 Plus $0.0013 per turn.
List prices
Cost per solved task
One SWE-bench Verified task, solved
DeepSeek V4 Flash 0731
DeepSeek V4 Flash 0731 $0.01, Qwen3.6 Plus $1.19.
Published attempt cost and pass rate
At a glance
- Coding index
- DeepSeek V4 Flash 0731 51.8 from 4 benchmarks, Qwen3.6 Plus 44.1 from 3 benchmarks.
- Widest category
- Coding, 17.9 points apart on average over 8 shared benchmarks.
- Widest single gap
- Vibe Code Bench (Vals AI): DeepSeek V4 Flash 0731 74.7% against Qwen3.6 Plus 25.6%, 49.2 points apart on a 0 to 100 scale.
- Output price
- DeepSeek V4 Flash 0731 $0.28 against Qwen3.6 Plus $1.95 per million output tokens, 7.0x apart.
- Context window
- DeepSeek V4 Flash 0731 takes 1.05M tokens, Qwen3.6 Plus 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 Flash 0731 | Bars | Qwen3.6 Plus | Ties |
|---|---|---|---|---|
| Coding | 7 | 0 | 1 tie | |
| Intelligence | 2 | 0 | ||
| Agentic work | 4 | 0 | ||
| Reasoning | 6 | 0 | ||
| Math | 2 | 0 | ||
| Knowledge | 1 | 5 | ||
| Web design | 3 | 5 | ||
| General | 4 | 0 | ||
| All shared boards | 29 | 10 | 1 tie |
CodingLike-for-likeSix of these boards feed the Vibe Coding Index70
| Benchmark | DeepSeek V4 Flash 0731 | Qwen3.6 Plus | Leader |
|---|---|---|---|
| LMArena WebDev | Not measured | 1461 | Only Qwen3.6 Plus measured |
| AA Coding Index | 69.1 | 54.5 | DeepSeek V4 Flash 0731 |
| LiveCodeBench (Vals AI) | 87.3% | 86.0% | DeepSeek V4 Flash 0731 |
| SWE-bench Verified (Vals AI) | 88.8% | 73.4% | 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% | 25.6% | DeepSeek V4 Flash 0731 |
| Code migration (Vals AI) | 38.6% | 11.1% | DeepSeek V4 Flash 0731 |
| ProgramBench (Vals AI) | 0.0% | 0.0% | Tie |
| IOI (Vals AI) | 32.7% | Not measured | Only DeepSeek V4 Flash 0731 measured |
| Terminal-Bench 2.1 (Vals AI) | 67.0% | 53.2% | 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% | Not measured | Only DeepSeek V4 Flash 0731 measured |
| Terminal-Bench Hard (Artificial Analysis run) | Not measured | 43.9% | Only Qwen3.6 Plus measured |
| FrontierCode | 18.8% | Not measured | Only DeepSeek V4 Flash 0731 measured |
| WeirdML | 63.0% | Not measured | Only DeepSeek V4 Flash 0731 measured |
| ALE-Bench | 1306.1 | 670.1 | DeepSeek V4 Flash 0731 |
| LMArena Text: coding | Not measured | 1467 | Only Qwen3.6 Plus measured |
| LMArena Text: software and IT | Not measured | 1462 | Only Qwen3.6 Plus measured |
| LMArena WebDev: React | Not measured | 1454 | Only Qwen3.6 Plus measured |
| LMArena WebDev: HTML | Not measured | 1463 | Only Qwen3.6 Plus measured |
| LMArena WebDev: from an image | Not measured | 1472 | Only Qwen3.6 Plus measured |
| Neither model has a result on the other 17 boards here | |||
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index20
| Benchmark | DeepSeek V4 Flash 0731 | Qwen3.6 Plus | Leader |
|---|---|---|---|
| AA Intelligence Index | 34.3 | 27.0 | DeepSeek V4 Flash 0731 |
| Epoch Capabilities Index | 154.8 | 147.3 | DeepSeek V4 Flash 0731 |
Agentic workLike-for-likePublic boards, shown as published, kept out of the index40
| Benchmark | DeepSeek V4 Flash 0731 | Qwen3.6 Plus | Leader |
|---|---|---|---|
| AA Agentic Index | 41.0 | Not measured | Only DeepSeek V4 Flash 0731 measured |
| Finance Agent (Vals AI) | 49.5% | 40.9% | DeepSeek V4 Flash 0731 |
| Tax Agent Bench (Vals AI) | 28.1% | 7.7% | DeepSeek V4 Flash 0731 |
| Legal Research Bench (Vals AI) | 30.3% | 14.9% | DeepSeek V4 Flash 0731 |
| Excel Modeling Benchmark (Vals AI) | 57.0% | 32.9% | 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 | 97.7% | Only Qwen3.6 Plus measured |
| Vending-Bench 2 | Not measured | $5,115 | Only Qwen3.6 Plus measured |
| Neither model has a result on the other 32 boards here | |||
ReasoningLike-for-likePublic boards, shown as published, kept out of the index60
| Benchmark | DeepSeek V4 Flash 0731 | Qwen3.6 Plus | Leader |
|---|---|---|---|
| GPQA Diamond | 89.9% | 87.4% | DeepSeek V4 Flash 0731 |
| MMMU Pro (Vals AI) | Not measured | 84.2% | Only Qwen3.6 Plus measured |
| GPQA Diamond (Artificial Analysis run) | 90.8% | 88.2% | DeepSeek V4 Flash 0731 |
| Humanity's Last Exam (Artificial Analysis run) | 38.6% | 27.8% | DeepSeek V4 Flash 0731 |
| GPQA Diamond (Epoch AI run) | 91.0% | 88.4% | DeepSeek V4 Flash 0731 |
| ARC-AGI | 89.0% | Not measured | Only DeepSeek V4 Flash 0731 measured |
| ARC-AGI-2 | 61.4% | Not measured | Only DeepSeek V4 Flash 0731 measured |
| SimpleBench | 61.1% | Not measured | Only DeepSeek V4 Flash 0731 measured |
| Chess puzzles | 32.0% | 14.0% | DeepSeek V4 Flash 0731 |
| Mystery game puzzles | 34.0% | 12.0% | DeepSeek V4 Flash 0731 |
| LMArena Text: hard prompts | Not measured | 1448 | Only Qwen3.6 Plus measured |
| LMArena Text: expert | Not measured | 1454 | Only Qwen3.6 Plus measured |
| LMArena Text: hard prompts in English | Not measured | 1455 | Only Qwen3.6 Plus measured |
| Neither model has a result on the other 9 boards here | |||
MathLike-for-likePublic boards, shown as published, kept out of the index20
| Benchmark | DeepSeek V4 Flash 0731 | Qwen3.6 Plus | Leader |
|---|---|---|---|
| AIME | Not measured | 94.6% | Only Qwen3.6 Plus measured |
| OTIS Mock AIME | 94.4% | 93.3% | DeepSeek V4 Flash 0731 |
| FrontierMath, tiers 1 to 3 | 57.5% | 38.2% | DeepSeek V4 Flash 0731 |
| FrontierMath, tier 4 | 24.4% | Not measured | Only DeepSeek V4 Flash 0731 measured |
| ProofBench | 56.0% | Not measured | Only DeepSeek V4 Flash 0731 measured |
| LMArena Text: math | Not measured | 1449 | Only Qwen3.6 Plus measured |
| LMArena Text: mathematical work | Not measured | 1448 | Only Qwen3.6 Plus measured |
| Neither model has a result on the other 6 boards here | |||
KnowledgeLike-for-likePublic boards, shown as published, kept out of the index15
| Benchmark | DeepSeek V4 Flash 0731 | Qwen3.6 Plus | Leader |
|---|---|---|---|
| MMLU Pro | 86.2% | 87.7% | Qwen3.6 Plus |
| LegalBench (Vals AI) | 77.7% | 84.2% | Qwen3.6 Plus |
| CaseLaw (Vals AI) | Not measured | 51.5% | Only Qwen3.6 Plus measured |
| CorpFin (Vals AI) | 61.9% | 61.9% | Qwen3.6 Plus |
| TaxEval (Vals AI) | 70.7% | 74.7% | Qwen3.6 Plus |
| MortgageTax (Vals AI) | Not measured | 68.0% | Only Qwen3.6 Plus measured |
| MedCode (Vals AI) | 41.4% | 36.9% | DeepSeek V4 Flash 0731 |
| SimpleQA Verified | 33.6% | 44.1% | Qwen3.6 Plus |
| LMArena Text: science | Not measured | 1439 | Only Qwen3.6 Plus measured |
| LMArena Text: medicine and healthcare | Not measured | 1442 | Only Qwen3.6 Plus measured |
| LMArena Text: legal and government | Not measured | 1437 | Only Qwen3.6 Plus measured |
| LMArena Text: business and finance | Not measured | 1430 | Only Qwen3.6 Plus measured |
| Neither model has a result on the other 6 boards here | |||
Web designLike-for-likePublic boards, shown as published, kept out of the index35
| Benchmark | DeepSeek V4 Flash 0731 | Qwen3.6 Plus | Leader |
|---|---|---|---|
| Design Arena: websites | 1238 | 1243 | Qwen3.6 Plus |
| Design Arena: UI components | 1235 | 1233 | DeepSeek V4 Flash 0731 |
| Design Arena: game dev | 1208 | 1211 | Qwen3.6 Plus |
| Design Arena: data viz | 1180 | 1228 | Qwen3.6 Plus |
| Design Arena: 3D | 1209 | 1202 | DeepSeek V4 Flash 0731 |
| Design Arena: all code categories | 1230 | 1236 | Qwen3.6 Plus |
| Design Arena: SVG | 1185 | 1161 | DeepSeek V4 Flash 0731 |
| Design Arena: ASCII art | 1090 | 1113 | Qwen3.6 Plus |
| 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 | Qwen3.6 Plus | Leader |
|---|---|---|---|
| SAGE (Vals AI) | Not measured | 44.9% | Only Qwen3.6 Plus measured |
| MedScribe (Vals AI) | 80.4% | 77.0% | DeepSeek V4 Flash 0731 |
| Vals Multimodal Index | Not measured | 51.5% | Only Qwen3.6 Plus measured |
| IFBench | Not measured | 75.2% | Only Qwen3.6 Plus measured |
| Long context reasoning (AA-LCR) | 79.7% | 78.3% | DeepSeek V4 Flash 0731 |
| DTBench | 90.9% | 81.9% | DeepSeek V4 Flash 0731 |
| LMCA | 41.7% | 33.1% | DeepSeek V4 Flash 0731 |
| CL-bench | Not measured | 20.3% | Only Qwen3.6 Plus measured |
| LMArena Text | Not measured | 1436 | Only Qwen3.6 Plus measured |
| LMArena Text: instruction following | Not measured | 1424 | Only Qwen3.6 Plus measured |
| LMArena Text: creative writing | Not measured | 1404 | Only Qwen3.6 Plus measured |
| LMArena Text: English | Not measured | 1445 | Only Qwen3.6 Plus measured |
| LMArena Text: non-English | Not measured | 1424 | Only Qwen3.6 Plus measured |
| LMArena Text: Chinese | Not measured | 1477 | Only Qwen3.6 Plus measured |
| LMArena Text: German | Not measured | 1451 | Only Qwen3.6 Plus measured |
| LMArena Text: Japanese | Not measured | 1390 | Only Qwen3.6 Plus measured |
| LMArena Text: Korean | Not measured | 1379 | Only Qwen3.6 Plus measured |
| LMArena Text: French | Not measured | 1455 | Only Qwen3.6 Plus measured |
| LMArena Text: Spanish | Not measured | 1432 | Only Qwen3.6 Plus measured |
| LMArena Text: Russian | Not measured | 1434 | Only Qwen3.6 Plus measured |
| LMArena Text: Polish | Not measured | 1433 | Only Qwen3.6 Plus measured |
| LMArena Text: multi-turn | Not measured | 1438 | Only Qwen3.6 Plus measured |
| LMArena Text: longer queries | Not measured | 1439 | Only Qwen3.6 Plus measured |
| LMArena Text: writing and language | Not measured | 1418 | Only Qwen3.6 Plus measured |
| LMArena Text: entertainment and media | Not measured | 1402 | Only Qwen3.6 Plus measured |
| Neither model has a result on the other 21 boards here | |||
Image generationNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
| Benchmark | DeepSeek V4 Flash 0731 | Qwen3.6 Plus | 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 | Qwen3.6 Plus |
|---|---|---|
| Maker | DeepSeek | Qwen |
| Weights | Open weights | No public weights listed |
| Released | July 31, 2026 | April 2, 2026 |
| Context window | 1.05M | 1M |
| Input $/Mtok | $0.14 | $0.325 |
| Output $/Mtok | $0.28 | $1.95 |
| Coding index | 51.8 | 44.1 |
| Independent measurements behind it | 4 | 3 |
| Cost per solved task | $0.01 | $1.19 |
| Source | OpenRouter listing | OpenRouter listing |
Questions
Is DeepSeek V4 Flash 0731 better than Qwen3.6 Plus for coding?
Pick DeepSeek V4 Flash 0731 for coding: it scores 51.8 on the Vibe Coding Index against 44.1 for Qwen3.6 Plus. Pick Qwen3.6 Plus for work measured by MMLU Pro or LegalBench (Vals AI), where it leads.
Which is cheaper, DeepSeek V4 Flash 0731 or Qwen3.6 Plus?
DeepSeek V4 Flash 0731 costs $0.14 per million input tokens and $0.28 per million output tokens; Qwen3.6 Plus costs $0.325 and $1.95. Per solved SWE-bench Verified task, DeepSeek V4 Flash 0731 costs $0.01 and Qwen3.6 Plus $1.19.
Which has the bigger context window, DeepSeek V4 Flash 0731 or Qwen3.6 Plus?
DeepSeek V4 Flash 0731, with 1.05M tokens against 1M.
How many benchmarks is the DeepSeek V4 Flash 0731 vs Qwen3.6 Plus comparison based on?
40 benchmarks have a result for both models as of October 21, 2026. DeepSeek V4 Flash 0731's coding index rests on 4 independent benchmarks and Qwen3.6 Plus's on 3. Where only one model has a result, the page says so instead of naming a winner.