R1 0528 vs Qwen3.8 Max (0902)
Updated October 21, 2026. 40 benchmarks have a result for both. Coding is ranked on the Vibe Coding Index; every other board is shown as published.
vs boards won of 40 shared
Decision reading
Pick R1 0528 for coding: it scores 71.4 on the Vibe Coding Index against 63.5 for Qwen3.8 Max (0902), though on 1 benchmark against 2.
Pick Qwen3.8 Max (0902) when the context window is larger, 1M against 164K tokens, or when what matters is LMArena Text: coding or LMArena Text: software and IT, where it leads.
Model AR1 0528DeepSeek71.4/1001 independent benchmarkNo cost per solved taskModel BQwen3.8 Max (0902)Qwen63.5/1002 independent benchmarks$1.32 per solved task
- Shared results
- 40
- R1 0528 only
- 19
- Qwen3.8 Max (0902) only
- 73
- 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
R1 0528
R1 0528 scores 71.4 against 63.5.
1 and 2 benchmarks behind the scores
Intelligence
AA Intelligence Index
Qwen3.8 Max (0902)
Qwen3.8 Max (0902) leads, 45.4 against 13.1.
Same board, both measured
Agentic work
AA Agentic Index
No call
Only Qwen3.8 Max (0902) has a AA Agentic Index result, 56.0.
Directional only
Reasoning
GPQA Diamond
No call
Only Qwen3.8 Max (0902) has a GPQA Diamond result, 93.7%.
Directional only
Knowledge
MMLU Pro
No call
Only Qwen3.8 Max (0902) has a MMLU Pro result, 88.6%.
Directional only
Web design
Design Arena: websites
Qwen3.8 Max (0902)
Qwen3.8 Max (0902) leads, 1275 against 1149.
Same board, both measured
Long documents
Listed context window
Qwen3.8 Max (0902)
Qwen3.8 Max (0902) takes 1M tokens against 164K.
Listed by OpenRouter
Everyday cost
1K input + 500 output tokens
R1 0528
R1 0528 $0.0016, Qwen3.8 Max (0902) $0.0050 per turn.
List prices
Cost per solved task
One SWE-bench Verified task, solved
No call
Only Qwen3.8 Max (0902) has the number, $1.32.
Directional only
At a glance
- Coding index
- R1 0528 71.4 from 1 benchmark, Qwen3.8 Max (0902) 63.5 from 2 benchmarks.
- Widest category
- Intelligence, 32.3 points apart on average over 1 shared benchmark.
- Widest single gap
- OTIS Mock AIME: R1 0528 66.4% against Qwen3.8 Max (0902) 100.0%, 33.6 points apart on a 0 to 100 scale.
- Output price
- R1 0528 $2.15 against Qwen3.8 Max (0902) $6.00 per million output tokens, 2.8x apart.
- Context window
- R1 0528 takes 164K 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 | R1 0528 | Bars | Qwen3.8 Max (0902) | Ties |
|---|---|---|---|---|
| Coding | 0 | 2 | ||
| Intelligence | 0 | 1 | ||
| Reasoning | 0 | 6 | ||
| Math | 0 | 3 | ||
| Knowledge | 0 | 4 | ||
| Web design | 0 | 6 | ||
| General | 0 | 18 | ||
| All shared boards | 0 | 40 |
CodingLike-for-likeFour of these boards feed the Vibe Coding Index02
| Benchmark | R1 0528 | Qwen3.8 Max (0902) | Leader |
|---|---|---|---|
| Aider polyglot | 71.4% | Not measured | Only R1 0528 measured |
| LiveBench coding | Not measured | 60.3% | Only Qwen3.8 Max (0902) measured |
| LMArena WebDev | Not measured | 1674 | Only Qwen3.8 Max (0902) measured |
| AA Coding Index | Not measured | 76.2 | Only Qwen3.8 Max (0902) measured |
| LiveCodeBench (Vals AI) | Not measured | 87.8% | Only Qwen3.8 Max (0902) measured |
| SWE-bench Verified (Vals AI) | Not measured | 85.6% | Only Qwen3.8 Max (0902) measured |
| Terminal-Bench 4 (Vals AI) | Not measured | 34.3% | Only Qwen3.8 Max (0902) measured |
| Vibe Code Bench (Vals AI) | Not measured | 64.7% | Only Qwen3.8 Max (0902) measured |
| Code migration (Vals AI) | Not measured | 24.0% | Only Qwen3.8 Max (0902) measured |
| ProgramBench (Vals AI) | Not measured | 0.0% | Only Qwen3.8 Max (0902) measured |
| IOI (Vals AI) | Not measured | 68.9% | Only Qwen3.8 Max (0902) measured |
| Terminal-Bench 2.1 (Vals AI) | Not measured | 67.4% | Only Qwen3.8 Max (0902) measured |
| SWE-bench Multimodal (Vals AI) | Not measured | 42.5% | Only Qwen3.8 Max (0902) measured |
| Vibe Code Bench 1-100 (Vals AI) | Not measured | 12.8% | Only Qwen3.8 Max (0902) measured |
| SkillsBench (Vals AI) | Not measured | 42.0% | Only Qwen3.8 Max (0902) measured |
| CyberBench (Vals AI) | Not measured | 28.6% | Only Qwen3.8 Max (0902) measured |
| LiveCodeBench (Artificial Analysis run) | 77.0% | Not measured | Only R1 0528 measured |
| SciCode | Not measured | 53.2% | Only Qwen3.8 Max (0902) measured |
| Terminal-Bench Hard (Artificial Analysis run) | 15.9% | Not measured | Only R1 0528 measured |
| FrontierSWE | Not measured | 17.8% | Only Qwen3.8 Max (0902) measured |
| WeirdML | 41.6% | Not measured | Only R1 0528 measured |
| ALE-Bench | 804.1 | Not measured | Only R1 0528 measured |
| LMArena Text: coding | 1427 | 1502 | Qwen3.8 Max (0902) |
| LMArena Text: software and IT | 1435 | 1498 | Qwen3.8 Max (0902) |
| LMArena WebDev: React | Not measured | 1692 | Only Qwen3.8 Max (0902) measured |
| LMArena WebDev: HTML | Not measured | 1649 | Only Qwen3.8 Max (0902) measured |
| LMArena WebDev: from an image | Not measured | 1637 | Only Qwen3.8 Max (0902) measured |
| Neither model has a result on the other 11 boards here | |||
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index01
| Benchmark | R1 0528 | Qwen3.8 Max (0902) | Leader |
|---|---|---|---|
| AA Intelligence Index | 13.1 | 45.4 | Qwen3.8 Max (0902) |
| Epoch Capabilities Index | Not measured | 157.4 | Only Qwen3.8 Max (0902) measured |
Agentic workDirectional onlyPublic boards, shown as published, kept out of the index21 boards, none shared
| Benchmark | R1 0528 | Qwen3.8 Max (0902) | Leader |
|---|---|---|---|
| AA Agentic Index | Not measured | 56.0 | Only Qwen3.8 Max (0902) measured |
| 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 |
| Finance Agent (Vals AI) | Not measured | 50.6% | Only Qwen3.8 Max (0902) measured |
| Tax Agent Bench (Vals AI) | Not measured | 32.1% | Only Qwen3.8 Max (0902) measured |
| Legal Research Bench (Vals AI) | Not measured | 47.6% | Only Qwen3.8 Max (0902) measured |
| Excel Modeling Benchmark (Vals AI) | Not measured | 60.1% | Only Qwen3.8 Max (0902) measured |
| Terminal-Bench-Science (Vals AI) | Not measured | 12.9% | Only Qwen3.8 Max (0902) measured |
| τ²-Bench Telecom | 36.5% | Not measured | Only R1 0528 measured |
| APEX-Agents | Not measured | 63.3% | Only Qwen3.8 Max (0902) measured |
| METR time horizons | 53.8% | Not measured | Only R1 0528 measured |
| DeepResearch Bench | 35.1% | Not measured | Only R1 0528 measured |
| LMArena Search | Not measured | 1261 | Only Qwen3.8 Max (0902) measured |
| Neither model has a result on the other 18 boards here | |||
ReasoningLike-for-likePublic boards, shown as published, kept out of the index06
| Benchmark | R1 0528 | Qwen3.8 Max (0902) | Leader |
|---|---|---|---|
| GPQA Diamond | Not measured | 93.7% | Only Qwen3.8 Max (0902) measured |
| 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) | 81.3% | 92.8% | Qwen3.8 Max (0902) |
| Humanity's Last Exam (Artificial Analysis run) | 15.8% | 43.1% | Qwen3.8 Max (0902) |
| GPQA Diamond (Epoch AI run) | 76.3% | 92.7% | Qwen3.8 Max (0902) |
| ARC-AGI | 21.2% | Not measured | Only R1 0528 measured |
| ARC-AGI-2 | 1.1% | Not measured | Only R1 0528 measured |
| SimpleBench | 40.8% | Not measured | Only R1 0528 measured |
| Chess puzzles | Not measured | 46.0% | Only Qwen3.8 Max (0902) measured |
| Mystery game puzzles | Not measured | 38.0% | Only Qwen3.8 Max (0902) measured |
| LMArena Text: hard prompts | 1415 | 1496 | Qwen3.8 Max (0902) |
| LMArena Text: expert | 1394 | 1507 | Qwen3.8 Max (0902) |
| LMArena Text: hard prompts in English | 1422 | 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 4 boards here | |||
MathLike-for-likePublic boards, shown as published, kept out of the index03
| Benchmark | R1 0528 | Qwen3.8 Max (0902) | Leader |
|---|---|---|---|
| AA Math Index | 76.0 | Not measured | Only R1 0528 measured |
| AIME 2025 (Artificial Analysis run) | 76.0% | Not measured | Only R1 0528 measured |
| OTIS Mock AIME | 66.4% | 100.0% | Qwen3.8 Max (0902) |
| FrontierMath, tiers 1 to 3 | Not measured | 74.7% | Only Qwen3.8 Max (0902) measured |
| FrontierMath, tier 4 | Not measured | 46.3% | Only Qwen3.8 Max (0902) measured |
| ProofBench | Not measured | 58.0% | Only Qwen3.8 Max (0902) measured |
| MATH level 5 | 96.6% | Not measured | Only R1 0528 measured |
| LMArena Text: math | 1400 | 1501 | Qwen3.8 Max (0902) |
| LMArena Text: mathematical work | 1415 | 1491 | Qwen3.8 Max (0902) |
| Neither model has a result on the other 4 boards here | |||
KnowledgeLike-for-likePublic boards, shown as published, kept out of the index04
| Benchmark | R1 0528 | Qwen3.8 Max (0902) | Leader |
|---|---|---|---|
| MMLU Pro | Not measured | 88.6% | Only Qwen3.8 Max (0902) measured |
| LegalBench (Vals AI) | Not measured | 83.6% | Only Qwen3.8 Max (0902) measured |
| CorpFin (Vals AI) | Not measured | 65.8% | Only Qwen3.8 Max (0902) measured |
| TaxEval (Vals AI) | Not measured | 75.5% | Only Qwen3.8 Max (0902) measured |
| MortgageTax (Vals AI) | Not measured | 64.0% | Only Qwen3.8 Max (0902) measured |
| MedCode (Vals AI) | Not measured | 40.7% | Only Qwen3.8 Max (0902) measured |
| MMLU Pro (Artificial Analysis run) | 84.9% | Not measured | Only R1 0528 measured |
| SimpleQA Verified | Not measured | 47.3% | Only Qwen3.8 Max (0902) measured |
| LMArena Text: science | 1430 | 1512 | Qwen3.8 Max (0902) |
| LMArena Text: medicine and healthcare | 1445 | 1503 | Qwen3.8 Max (0902) |
| LMArena Text: legal and government | 1419 | 1492 | Qwen3.8 Max (0902) |
| LMArena Text: business and finance | 1402 | 1480 | Qwen3.8 Max (0902) |
| Neither model has a result on the other 5 boards here | |||
Web designLike-for-likePublic boards, shown as published, kept out of the index06
| Benchmark | R1 0528 | Qwen3.8 Max (0902) | Leader |
|---|---|---|---|
| Design Arena: websites | 1149 | 1275 | Qwen3.8 Max (0902) |
| Design Arena: UI components | 1102 | 1340 | Qwen3.8 Max (0902) |
| Design Arena: game dev | 1098 | 1313 | Qwen3.8 Max (0902) |
| Design Arena: data viz | 1182 | 1281 | Qwen3.8 Max (0902) |
| Design Arena: 3D | 1111 | 1337 | Qwen3.8 Max (0902) |
| Design Arena: all code categories | 1139 | 1293 | Qwen3.8 Max (0902) |
| Design Arena: SVG | 1038 | Not measured | Only R1 0528 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 |
GeneralLike-for-likePublic boards, shown as published, kept out of the index018
| Benchmark | R1 0528 | Qwen3.8 Max (0902) | Leader |
|---|---|---|---|
| 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) | Not measured | 85.0% | Only Qwen3.8 Max (0902) measured |
| Vals Multimodal Index | Not measured | 65.4% | Only Qwen3.8 Max (0902) measured |
| IFBench | 39.6% | Not measured | Only R1 0528 measured |
| Long context reasoning (AA-LCR) | 55.7% | 80.3% | Qwen3.8 Max (0902) |
| DTBench | Not measured | 92.0% | Only Qwen3.8 Max (0902) measured |
| LMCA | Not measured | 46.2% | Only Qwen3.8 Max (0902) measured |
| Fiction.LiveBench | 75.0% | Not measured | Only R1 0528 measured |
| Creative writing (Lech Mazur) | 81.9% | Not measured | Only R1 0528 measured |
| Furniture assembly | Not measured | 20.0% | Only Qwen3.8 Max (0902) measured |
| LMArena Text | 1428 | 1483 | Qwen3.8 Max (0902) |
| LMArena Text: instruction following | 1382 | 1481 | Qwen3.8 Max (0902) |
| LMArena Text: creative writing | 1405 | 1477 | Qwen3.8 Max (0902) |
| LMArena Vision | Not measured | 1313 | Only Qwen3.8 Max (0902) measured |
| LMArena Text: English | 1437 | 1491 | Qwen3.8 Max (0902) |
| LMArena Text: non-English | 1412 | 1473 | Qwen3.8 Max (0902) |
| LMArena Text: Chinese | 1442 | 1539 | Qwen3.8 Max (0902) |
| LMArena Text: German | 1404 | 1478 | Qwen3.8 Max (0902) |
| LMArena Text: Japanese | 1391 | 1473 | Qwen3.8 Max (0902) |
| LMArena Text: Korean | 1360 | 1460 | Qwen3.8 Max (0902) |
| LMArena Text: French | 1417 | 1498 | Qwen3.8 Max (0902) |
| LMArena Text: Spanish | 1411 | 1489 | Qwen3.8 Max (0902) |
| LMArena Text: Russian | 1423 | 1482 | Qwen3.8 Max (0902) |
| LMArena Text: Polish | 1428 | 1471 | Qwen3.8 Max (0902) |
| LMArena Text: multi-turn | 1405 | 1489 | Qwen3.8 Max (0902) |
| LMArena Text: longer queries | 1391 | 1488 | Qwen3.8 Max (0902) |
| LMArena Text: writing and language | 1402 | 1477 | Qwen3.8 Max (0902) |
| LMArena Text: entertainment and media | 1400 | 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 11 boards here | |||
Image generationNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
| Benchmark | R1 0528 | 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
R1 0528$0.0016Fits in one request
Qwen3.8 Max (0902)$0.0050Fits in one request
R1 0528 costs less
Repository review
50K input + 3K output tokens
R1 0528$0.031Fits in one request
Qwen3.8 Max (0902)$0.118Fits in one request
R1 0528 costs less
Agent loop
200K input + 10K output tokens
R1 0528$0.121Exceeds the context window
Qwen3.8 Max (0902)$0.460Fits in one request
R1 0528 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 R1 0528 | Qwen3.8 Max (0902) |
|---|---|---|
| Maker | DeepSeek | Qwen |
| Weights | Open weights | No public weights listed |
| Released | May 28, 2025 | September 3, 2026 |
| Context window | 164K | 1M |
| Input $/Mtok | $0.50 | $2.00 |
| Output $/Mtok | $2.15 | $6.00 |
| Coding index | 71.4 | 63.5 |
| Independent measurements behind it | 1 | 2 |
| Cost per solved task | Not computable | $1.32 |
| Source | OpenRouter listing | OpenRouter listing |
Questions
Is R1 0528 better than Qwen3.8 Max (0902) for coding?
Pick R1 0528 for coding: it scores 71.4 on the Vibe Coding Index against 63.5 for Qwen3.8 Max (0902), though on 1 benchmark against 2. Pick Qwen3.8 Max (0902) when the context window is larger, 1M against 164K tokens, or when what matters is LMArena Text: coding or LMArena Text: software and IT, where it leads.
Which is cheaper, R1 0528 or Qwen3.8 Max (0902)?
R1 0528 costs $0.50 per million input tokens and $2.15 per million output tokens; Qwen3.8 Max (0902) costs $2.00 and $6.00. Cost per solved task is known for Qwen3.8 Max (0902) only.
Which has the bigger context window, R1 0528 or Qwen3.8 Max (0902)?
Qwen3.8 Max (0902), with 1M tokens against 164K.
How many benchmarks is the R1 0528 vs Qwen3.8 Max (0902) comparison based on?
40 benchmarks have a result for both models as of October 21, 2026. R1 0528'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.