DeepSeek V4 Pro 0813 vs Qwen3.8 Max (0902)
Updated October 21, 2026. 70 benchmarks have a result for both. Coding is ranked on the Vibe Coding Index; every other board is shown as published.
Decision reading
Pick Qwen3.8 Max (0902) for coding: it scores 63.5 on the Vibe Coding Index against 54.6 for DeepSeek V4 Pro 0813.
Pick DeepSeek V4 Pro 0813 when output tokens cost 3.0x less, or when a solved task costs $0.10 against $1.32.
- Shared results
- 70
- DeepSeek V4 Pro 0813 only
- 8
- Qwen3.8 Max (0902) only
- 43
- Like-for-like categories
- 7 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
Qwen3.8 Max (0902)
Qwen3.8 Max (0902) scores 63.5 against 54.6.
1 and 2 benchmarks behind the scores
Intelligence
AA Intelligence Index
Qwen3.8 Max (0902)
Qwen3.8 Max (0902) leads, 45.4 against 36.0.
Same board, both measured
Agentic work
AA Agentic Index
Qwen3.8 Max (0902)
Qwen3.8 Max (0902) leads, 56.0 against 41.3.
Same board, both measured
Reasoning
GPQA Diamond
Qwen3.8 Max (0902)
Qwen3.8 Max (0902) leads, 93.7% against 92.4%.
Same board, both measured
Knowledge
MMLU Pro
Qwen3.8 Max (0902)
Qwen3.8 Max (0902) leads, 88.6% against 87.0%.
Same board, both measured
Web design
Design Arena: websites
No call
Only Qwen3.8 Max (0902) has a Design Arena: websites result, 1275.
Directional only
General
Vals Index
No call
Only DeepSeek V4 Pro 0813 has a Vals Index result, 53.0%.
Directional only
Long documents
Listed context window
DeepSeek V4 Pro 0813
DeepSeek V4 Pro 0813 takes 1.05M tokens against 1M.
Listed by OpenRouter
Everyday cost
1K input + 500 output tokens
DeepSeek V4 Pro 0813
DeepSeek V4 Pro 0813 $0.0016, Qwen3.8 Max (0902) $0.0050 per turn.
List prices
Cost per solved task
One SWE-bench Verified task, solved
DeepSeek V4 Pro 0813
DeepSeek V4 Pro 0813 $0.10, Qwen3.8 Max (0902) $1.32.
Published attempt cost and pass rate
At a glance
- Coding index
- DeepSeek V4 Pro 0813 54.6 from 1 benchmark, Qwen3.8 Max (0902) 63.5 from 2 benchmarks.
- Widest category
- Coding, 11.1 points apart on average over 18 shared benchmarks.
- Widest single gap
- CyberBench (Vals AI): DeepSeek V4 Pro 0813 72.9% against Qwen3.8 Max (0902) 28.6%, 44.3 points apart on a 0 to 100 scale.
- Output price
- DeepSeek V4 Pro 0813 $1.98 against Qwen3.8 Max (0902) $6.00 per million output tokens, 3.0x apart.
- Context window
- DeepSeek V4 Pro 0813 takes 1.05M tokens, Qwen3.8 Max (0902) 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 Pro 0813 | Bars | Qwen3.8 Max (0902) | Ties |
|---|---|---|---|---|
| Coding | 6 | 11 | 1 tie | |
| Intelligence | 0 | 2 | ||
| Agentic work | 0 | 7 | ||
| Reasoning | 1 | 6 | 2 ties | |
| Math | 0 | 6 | ||
| Knowledge | 2 | 8 | ||
| General | 1 | 16 | 1 tie | |
| All shared boards | 10 | 56 | 4 ties |
CodingLike-for-likeFour of these boards feed the Vibe Coding Index611
| Benchmark | DeepSeek V4 Pro 0813 | Qwen3.8 Max (0902) | Leader |
|---|---|---|---|
| LiveBench coding | Not measured | 60.3% | Only Qwen3.8 Max (0902) measured |
| LMArena WebDev | 1582 | 1674 | Qwen3.8 Max (0902) |
| AA Coding Index | 68.8 | 76.2 | Qwen3.8 Max (0902) |
| LiveCodeBench (Vals AI) | 87.5% | 87.8% | Qwen3.8 Max (0902) |
| SWE-bench Verified (Vals AI) | 96.4% | 85.6% | DeepSeek V4 Pro 0813 |
| Terminal-Bench 4 (Vals AI) | 14.1% | 34.3% | Qwen3.8 Max (0902) |
| Vibe Code Bench (Vals AI) | 82.3% | 64.7% | DeepSeek V4 Pro 0813 |
| Code migration (Vals AI) | 41.5% | 24.0% | DeepSeek V4 Pro 0813 |
| ProgramBench (Vals AI) | 0.0% | 0.0% | Tie |
| IOI (Vals AI) | 51.6% | 68.9% | Qwen3.8 Max (0902) |
| Terminal-Bench 2.1 (Vals AI) | 54.7% | 67.4% | Qwen3.8 Max (0902) |
| SWE-bench Multimodal (Vals AI) | Not measured | 42.5% | Only Qwen3.8 Max (0902) measured |
| Vibe Code Bench 1-100 (Vals AI) | 17.5% | 12.8% | DeepSeek V4 Pro 0813 |
| SkillsBench (Vals AI) | 53.8% | 42.0% | DeepSeek V4 Pro 0813 |
| CyberBench (Vals AI) | 72.9% | 28.6% | DeepSeek V4 Pro 0813 |
| SciCode | 51.0% | 53.2% | Qwen3.8 Max (0902) |
| FrontierCode | 28.5% | Not measured | Only DeepSeek V4 Pro 0813 measured |
| FrontierSWE | Not measured | 17.8% | Only Qwen3.8 Max (0902) measured |
| WeirdML | 66.2% | Not measured | Only DeepSeek V4 Pro 0813 measured |
| ALE-Bench | 1403.2 | Not measured | Only DeepSeek V4 Pro 0813 measured |
| LMArena Text: coding | 1469 | 1502 | Qwen3.8 Max (0902) |
| LMArena Text: software and IT | 1462 | 1498 | Qwen3.8 Max (0902) |
| LMArena WebDev: React | 1588 | 1692 | Qwen3.8 Max (0902) |
| LMArena WebDev: HTML | 1566 | 1649 | Qwen3.8 Max (0902) |
| LMArena WebDev: from an image | Not measured | 1637 | Only Qwen3.8 Max (0902) measured |
| Neither model has a result on the other 13 boards here | |||
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index02
| Benchmark | DeepSeek V4 Pro 0813 | Qwen3.8 Max (0902) | Leader |
|---|---|---|---|
| AA Intelligence Index | 36.0 | 45.4 | Qwen3.8 Max (0902) |
| Epoch Capabilities Index | 155.6 | 157.4 | Qwen3.8 Max (0902) |
Agentic workLike-for-likePublic boards, shown as published, kept out of the index07
| Benchmark | DeepSeek V4 Pro 0813 | Qwen3.8 Max (0902) | Leader |
|---|---|---|---|
| AA Agentic Index | 41.3 | 56.0 | Qwen3.8 Max (0902) |
| Design Arena: agents building web apps | Not measured | 1301 | Only Qwen3.8 Max (0902) measured |
| Design Arena: agents building full-stack apps | Not measured | 1305 | Only Qwen3.8 Max (0902) measured |
| Design Arena: agents building mobile apps | Not measured | 1223 | Only Qwen3.8 Max (0902) measured |
| Design Arena: agents building Android apps | Not measured | 1207 | Only Qwen3.8 Max (0902) measured |
| Design Arena: agents building Godot games | Not measured | 1234 | Only Qwen3.8 Max (0902) measured |
| Design Arena: PowerPoint slides | Not measured | 1257 | Only Qwen3.8 Max (0902) measured |
| Design Arena: spreadsheets | Not measured | 868 | Only Qwen3.8 Max (0902) measured |
| LiveBench research | Not measured | 69.9% | Only Qwen3.8 Max (0902) measured |
| LiveBench browser | Not measured | 32.0% | Only Qwen3.8 Max (0902) measured |
| LiveBench long agentic | Not measured | 42.3% | Only Qwen3.8 Max (0902) measured |
| SREBench (Vals AI) | 1.9% | Not measured | Only DeepSeek V4 Pro 0813 measured |
| Finance Agent (Vals AI) | 50.4% | 50.6% | Qwen3.8 Max (0902) |
| Tax Agent Bench (Vals AI) | 26.8% | 32.1% | Qwen3.8 Max (0902) |
| Legal Research Bench (Vals AI) | 40.9% | 47.6% | Qwen3.8 Max (0902) |
| Harvey's Legal Agent Benchmark (Vals AI) | 10.8% | Not measured | Only DeepSeek V4 Pro 0813 measured |
| Excel Modeling Benchmark (Vals AI) | 52.8% | 60.1% | Qwen3.8 Max (0902) |
| Terminal-Bench-Science (Vals AI) | 4.3% | 12.9% | Qwen3.8 Max (0902) |
| APEX-Agents | 47.3% | 63.3% | Qwen3.8 Max (0902) |
| LMArena Search | Not measured | 1261 | Only Qwen3.8 Max (0902) measured |
| Neither model has a result on the other 19 boards here | |||
ReasoningLike-for-likePublic boards, shown as published, kept out of the index16
| Benchmark | DeepSeek V4 Pro 0813 | Qwen3.8 Max (0902) | Leader |
|---|---|---|---|
| GPQA Diamond | 92.4% | 93.7% | Qwen3.8 Max (0902) |
| LiveBench reasoning | Not measured | 88.2% | Only Qwen3.8 Max (0902) measured |
| MysteryMechanism (Vals AI) | Not measured | 23.9% | Only Qwen3.8 Max (0902) measured |
| MMMU Pro (Vals AI) | Not measured | 88.0% | Only Qwen3.8 Max (0902) measured |
| GPQA Diamond (Artificial Analysis run) | 92.8% | 92.8% | Tie |
| Humanity's Last Exam (Artificial Analysis run) | 41.0% | 43.1% | Qwen3.8 Max (0902) |
| GPQA Diamond (Epoch AI run) | 91.7% | 92.7% | Qwen3.8 Max (0902) |
| ARC-AGI | 90.5% | Not measured | Only DeepSeek V4 Pro 0813 measured |
| ARC-AGI-2 | 61.3% | Not measured | Only DeepSeek V4 Pro 0813 measured |
| Chess puzzles | 46.0% | 46.0% | Tie |
| Mystery game puzzles | 43.0% | 38.0% | DeepSeek V4 Pro 0813 |
| LMArena Text: hard prompts | 1458 | 1496 | Qwen3.8 Max (0902) |
| LMArena Text: expert | 1459 | 1507 | Qwen3.8 Max (0902) |
| LMArena Text: hard prompts in English | 1463 | 1503 | Qwen3.8 Max (0902) |
| LMArena Vision: diagrams | Not measured | 1323 | Only Qwen3.8 Max (0902) measured |
| LMArena Vision: homework | Not measured | 1336 | Only Qwen3.8 Max (0902) measured |
| Neither model has a result on the other 5 boards here | |||
MathLike-for-likePublic boards, shown as published, kept out of the index06
| Benchmark | DeepSeek V4 Pro 0813 | Qwen3.8 Max (0902) | Leader |
|---|---|---|---|
| OTIS Mock AIME | 98.6% | 100.0% | Qwen3.8 Max (0902) |
| FrontierMath, tiers 1 to 3 | 64.6% | 74.7% | Qwen3.8 Max (0902) |
| FrontierMath, tier 4 | 26.8% | 46.3% | Qwen3.8 Max (0902) |
| ProofBench | 50.0% | 58.0% | Qwen3.8 Max (0902) |
| LMArena Text: math | 1441 | 1501 | Qwen3.8 Max (0902) |
| LMArena Text: mathematical work | 1443 | 1491 | Qwen3.8 Max (0902) |
| Neither model has a result on the other 7 boards here | |||
KnowledgeLike-for-likePublic boards, shown as published, kept out of the index28
| Benchmark | DeepSeek V4 Pro 0813 | Qwen3.8 Max (0902) | Leader |
|---|---|---|---|
| MMLU Pro | 87.0% | 88.6% | Qwen3.8 Max (0902) |
| LegalBench (Vals AI) | 82.4% | 83.6% | Qwen3.8 Max (0902) |
| CorpFin (Vals AI) | 65.4% | 65.8% | Qwen3.8 Max (0902) |
| TaxEval (Vals AI) | 73.1% | 75.5% | Qwen3.8 Max (0902) |
| MortgageTax (Vals AI) | Not measured | 64.0% | Only Qwen3.8 Max (0902) measured |
| MedCode (Vals AI) | 42.5% | 40.7% | DeepSeek V4 Pro 0813 |
| SimpleQA Verified | 52.9% | 47.3% | DeepSeek V4 Pro 0813 |
| LMArena Text: science | 1457 | 1512 | Qwen3.8 Max (0902) |
| LMArena Text: medicine and healthcare | 1446 | 1503 | Qwen3.8 Max (0902) |
| LMArena Text: legal and government | 1459 | 1492 | Qwen3.8 Max (0902) |
| LMArena Text: business and finance | 1442 | 1480 | Qwen3.8 Max (0902) |
| Neither model has a result on the other 6 boards here | |||
Web designDirectional onlyPublic boards, shown as published, kept out of the index8 boards, none shared
| Benchmark | DeepSeek V4 Pro 0813 | Qwen3.8 Max (0902) | Leader |
|---|---|---|---|
| Design Arena: websites | Not measured | 1275 | Only Qwen3.8 Max (0902) measured |
| Design Arena: UI components | Not measured | 1340 | Only Qwen3.8 Max (0902) measured |
| Design Arena: game dev | Not measured | 1313 | Only Qwen3.8 Max (0902) measured |
| Design Arena: data viz | Not measured | 1281 | Only Qwen3.8 Max (0902) measured |
| Design Arena: 3D | Not measured | 1337 | Only Qwen3.8 Max (0902) measured |
| Design Arena: all code categories | Not measured | 1293 | Only Qwen3.8 Max (0902) measured |
| Design Arena: ASCII art | Not measured | 1201 | Only Qwen3.8 Max (0902) measured |
| LiveBench design | Not measured | 78.6% | Only Qwen3.8 Max (0902) measured |
| Neither model has a result on the other 1 board here | |||
GeneralLike-for-likePublic boards, shown as published, kept out of the index116
| Benchmark | DeepSeek V4 Pro 0813 | Qwen3.8 Max (0902) | Leader |
|---|---|---|---|
| Vals Index | 53.0% | Not measured | Only DeepSeek V4 Pro 0813 measured |
| LiveBench data analysis | Not measured | 78.4% | Only Qwen3.8 Max (0902) measured |
| Public Benefits Bench (Vals AI) | Not measured | 67.1% | Only Qwen3.8 Max (0902) measured |
| SAGE (Vals AI) | Not measured | 51.2% | Only Qwen3.8 Max (0902) measured |
| MedScribe (Vals AI) | 80.2% | 85.0% | Qwen3.8 Max (0902) |
| Vals Multimodal Index | Not measured | 65.4% | Only Qwen3.8 Max (0902) measured |
| Long context reasoning (AA-LCR) | 80.3% | 80.3% | Tie |
| DTBench | 93.9% | 92.0% | DeepSeek V4 Pro 0813 |
| LMCA | 45.5% | 46.2% | Qwen3.8 Max (0902) |
| Furniture assembly | Not measured | 20.0% | Only Qwen3.8 Max (0902) measured |
| LMArena Text | 1446 | 1483 | Qwen3.8 Max (0902) |
| LMArena Text: instruction following | 1448 | 1481 | Qwen3.8 Max (0902) |
| LMArena Text: creative writing | 1439 | 1477 | Qwen3.8 Max (0902) |
| LMArena Vision | Not measured | 1313 | Only Qwen3.8 Max (0902) measured |
| LMArena Text: English | 1457 | 1491 | Qwen3.8 Max (0902) |
| LMArena Text: non-English | 1431 | 1473 | Qwen3.8 Max (0902) |
| LMArena Text: Chinese | 1481 | 1539 | Qwen3.8 Max (0902) |
| LMArena Text: German | Not measured | 1478 | Only Qwen3.8 Max (0902) measured |
| LMArena Text: Japanese | Not measured | 1473 | Only Qwen3.8 Max (0902) measured |
| LMArena Text: Korean | 1449 | 1460 | Qwen3.8 Max (0902) |
| LMArena Text: French | 1446 | 1498 | Qwen3.8 Max (0902) |
| LMArena Text: Spanish | 1435 | 1489 | Qwen3.8 Max (0902) |
| LMArena Text: Russian | 1448 | 1482 | Qwen3.8 Max (0902) |
| LMArena Text: Polish | Not measured | 1471 | Only Qwen3.8 Max (0902) measured |
| LMArena Text: multi-turn | 1454 | 1489 | Qwen3.8 Max (0902) |
| LMArena Text: longer queries | 1458 | 1488 | Qwen3.8 Max (0902) |
| LMArena Text: writing and language | 1443 | 1477 | Qwen3.8 Max (0902) |
| LMArena Text: entertainment and media | 1424 | 1464 | Qwen3.8 Max (0902) |
| LMArena Vision: English | Not measured | 1311 | Only Qwen3.8 Max (0902) measured |
| LMArena Vision: Chinese | Not measured | 1358 | Only Qwen3.8 Max (0902) measured |
| LMArena Vision: reading text | Not measured | 1322 | Only Qwen3.8 Max (0902) measured |
| LMArena Vision: humor | Not measured | 1304 | Only Qwen3.8 Max (0902) measured |
| LMArena Vision: creative writing | Not measured | 1312 | Only Qwen3.8 Max (0902) 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 Pro 0813 | Qwen3.8 Max (0902) | 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 Pro 0813 costs less
Repository review
50K input + 3K output tokens
DeepSeek V4 Pro 0813 costs less
Agent loop
200K input + 10K output tokens
DeepSeek V4 Pro 0813 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 Pro 0813 | Qwen3.8 Max (0902) |
|---|---|---|
| Maker | DeepSeek | Qwen |
| Weights | Open weights | No public weights listed |
| Released | August 12, 2026 | September 3, 2026 |
| Context window | 1.05M | 1M |
| Input $/Mtok | $0.66 | $2.00 |
| Output $/Mtok | $1.98 | $6.00 |
| Coding index | 54.6 | 63.5 |
| Independent measurements behind it | 1 | 2 |
| Cost per solved task | $0.10 | $1.32 |
| Source | OpenRouter listing | OpenRouter listing |
Questions
Is DeepSeek V4 Pro 0813 better than Qwen3.8 Max (0902) for coding?
Pick Qwen3.8 Max (0902) for coding: it scores 63.5 on the Vibe Coding Index against 54.6 for DeepSeek V4 Pro 0813. Pick DeepSeek V4 Pro 0813 when output tokens cost 3.0x less, or when a solved task costs $0.10 against $1.32.
Which is cheaper, DeepSeek V4 Pro 0813 or Qwen3.8 Max (0902)?
DeepSeek V4 Pro 0813 costs $0.66 per million input tokens and $1.98 per million output tokens; Qwen3.8 Max (0902) costs $2.00 and $6.00. Per solved SWE-bench Verified task, DeepSeek V4 Pro 0813 costs $0.10 and Qwen3.8 Max (0902) $1.32.
Which has the bigger context window, DeepSeek V4 Pro 0813 or Qwen3.8 Max (0902)?
DeepSeek V4 Pro 0813, with 1.05M tokens against 1M.
How many benchmarks is the DeepSeek V4 Pro 0813 vs Qwen3.8 Max (0902) comparison based on?
70 benchmarks have a result for both models as of October 21, 2026. DeepSeek V4 Pro 0813's coding index rests on 1 independent benchmark and Qwen3.8 Max (0902)'s on 2. Where only one model has a result, the page says so instead of naming a winner.