R1 0528 vs Qwen3.5 397B A17B
Updated October 21, 2026. 45 benchmarks have a result for both. Coding is ranked on the Vibe Coding Index; every other board is shown as published.
Decision reading
Pick R1 0528 for coding: it scores 71.4 on the Vibe Coding Index against 28.6 for Qwen3.5 397B A17B.
Pick Qwen3.5 397B A17B when the context window is larger, 262K against 164K tokens, or when what matters is Terminal-Bench Hard (Artificial Analysis run) or LMArena Text: coding, where it leads.
- Shared results
- 45
- R1 0528 only
- 14
- Qwen3.5 397B A17B only
- 20
- Like-for-like categories
- 8 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 28.6.
One benchmark behind each score
Intelligence
AA Intelligence Index
Qwen3.5 397B A17B
Qwen3.5 397B A17B leads, 21.4 against 13.1.
Same board, both measured
Web design
Design Arena: websites
Qwen3.5 397B A17B
Qwen3.5 397B A17B leads, 1191 against 1149.
Same board, both measured
Long documents
Listed context window
Qwen3.5 397B A17B
Qwen3.5 397B A17B takes 262K tokens against 164K.
Listed by OpenRouter
Everyday cost
1K input + 500 output tokens
Qwen3.5 397B A17B
R1 0528 $0.0016, Qwen3.5 397B A17B $0.0016 per turn.
List prices
At a glance
- Coding index
- R1 0528 71.4 from 1 benchmark, Qwen3.5 397B A17B 28.6 from 1 benchmark.
- Widest category
- Agentic work, 59.1 points apart on average over 1 shared benchmark.
- Widest single gap
- τ²-Bench Telecom: R1 0528 36.5% against Qwen3.5 397B A17B 95.6%, 59.1 points apart on a 0 to 100 scale.
- Output price
- R1 0528 $2.15 against Qwen3.5 397B A17B $2.34 per million output tokens, 1.1x apart.
- Context window
- R1 0528 takes 164K tokens, Qwen3.5 397B A17B 262K.
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 | Qwen3.5 397B A17B | Ties |
|---|---|---|---|---|
| Coding | 1 | 3 | ||
| Intelligence | 0 | 1 | ||
| Agentic work | 0 | 1 | ||
| Reasoning | 0 | 6 | ||
| Math | 0 | 3 | ||
| Knowledge | 0 | 4 | ||
| Web design | 1 | 6 | ||
| General | 2 | 17 | ||
| All shared boards | 4 | 41 |
CodingLike-for-likeFour of these boards feed the Vibe Coding Index13
| Benchmark | R1 0528 | Qwen3.5 397B A17B | Leader |
|---|---|---|---|
| Aider polyglot | 71.4% | Not measured | Only R1 0528 measured |
| LMArena WebDev | Not measured | 1400 | Only Qwen3.5 397B A17B measured |
| LiveCodeBench (Artificial Analysis run) | 77.0% | Not measured | Only R1 0528 measured |
| SciCode | Not measured | 44.8% | Only Qwen3.5 397B A17B measured |
| Terminal-Bench Hard (Artificial Analysis run) | 15.9% | 40.9% | Qwen3.5 397B A17B |
| WeirdML | 41.6% | Not measured | Only R1 0528 measured |
| ALE-Bench | 804.1 | 621.9 | R1 0528 |
| LMArena Text: coding | 1427 | 1464 | Qwen3.5 397B A17B |
| LMArena Text: software and IT | 1435 | 1463 | Qwen3.5 397B A17B |
| LMArena WebDev: React | Not measured | 1388 | Only Qwen3.5 397B A17B measured |
| LMArena WebDev: HTML | Not measured | 1410 | Only Qwen3.5 397B A17B measured |
| Neither model has a result on the other 27 boards here | |||
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index01
| Benchmark | R1 0528 | Qwen3.5 397B A17B | Leader |
|---|---|---|---|
| AA Intelligence Index | 13.1 | 21.4 | Qwen3.5 397B A17B |
| Epoch Capabilities Index | Not measured | 146.8 | Only Qwen3.5 397B A17B measured |
Agentic workLike-for-likePublic boards, shown as published, kept out of the index01
| Benchmark | R1 0528 | Qwen3.5 397B A17B | Leader |
|---|---|---|---|
| τ²-Bench Telecom | 36.5% | 95.6% | Qwen3.5 397B A17B |
| APEX-Agents | Not measured | 24.9% | Only Qwen3.5 397B A17B measured |
| METR time horizons | 53.8% | Not measured | Only R1 0528 measured |
| DeepResearch Bench | 35.1% | Not measured | Only R1 0528 measured |
| Neither model has a result on the other 35 boards here | |||
ReasoningLike-for-likePublic boards, shown as published, kept out of the index06
| Benchmark | R1 0528 | Qwen3.5 397B A17B | Leader |
|---|---|---|---|
| GPQA Diamond (Artificial Analysis run) | 81.3% | 89.3% | Qwen3.5 397B A17B |
| Humanity's Last Exam (Artificial Analysis run) | 15.8% | 29.0% | Qwen3.5 397B A17B |
| GPQA Diamond (Epoch AI run) | 76.3% | 86.4% | Qwen3.5 397B A17B |
| 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 |
| Mystery game puzzles | Not measured | 18.0% | Only Qwen3.5 397B A17B measured |
| LMArena Text: hard prompts | 1415 | 1448 | Qwen3.5 397B A17B |
| LMArena Text: expert | 1394 | 1462 | Qwen3.5 397B A17B |
| LMArena Text: hard prompts in English | 1422 | 1450 | Qwen3.5 397B A17B |
| LMArena Vision: diagrams | Not measured | 1277 | Only Qwen3.5 397B A17B measured |
| LMArena Vision: homework | Not measured | 1292 | Only Qwen3.5 397B A17B measured |
| Neither model has a result on the other 9 boards here | |||
MathLike-for-likePublic boards, shown as published, kept out of the index03
| Benchmark | R1 0528 | Qwen3.5 397B A17B | 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% | 88.9% | Qwen3.5 397B A17B |
| FrontierMath, tiers 1 to 3 | Not measured | 31.2% | Only Qwen3.5 397B A17B measured |
| MATH level 5 | 96.6% | Not measured | Only R1 0528 measured |
| LMArena Text: math | 1400 | 1453 | Qwen3.5 397B A17B |
| LMArena Text: mathematical work | 1415 | 1454 | Qwen3.5 397B A17B |
| Neither model has a result on the other 6 boards here | |||
KnowledgeLike-for-likePublic boards, shown as published, kept out of the index04
| Benchmark | R1 0528 | Qwen3.5 397B A17B | Leader |
|---|---|---|---|
| MMLU Pro (Artificial Analysis run) | 84.9% | Not measured | Only R1 0528 measured |
| LMArena Text: science | 1430 | 1457 | Qwen3.5 397B A17B |
| LMArena Text: medicine and healthcare | 1445 | 1455 | Qwen3.5 397B A17B |
| LMArena Text: legal and government | 1419 | 1441 | Qwen3.5 397B A17B |
| LMArena Text: business and finance | 1402 | 1435 | Qwen3.5 397B A17B |
| Neither model has a result on the other 12 boards here | |||
Web designLike-for-likePublic boards, shown as published, kept out of the index16
| Benchmark | R1 0528 | Qwen3.5 397B A17B | Leader |
|---|---|---|---|
| Design Arena: websites | 1149 | 1191 | Qwen3.5 397B A17B |
| Design Arena: UI components | 1102 | 1163 | Qwen3.5 397B A17B |
| Design Arena: game dev | 1098 | 1141 | Qwen3.5 397B A17B |
| Design Arena: data viz | 1182 | 1175 | R1 0528 |
| Design Arena: 3D | 1111 | 1161 | Qwen3.5 397B A17B |
| Design Arena: all code categories | 1139 | 1180 | Qwen3.5 397B A17B |
| Design Arena: SVG | 1038 | 1139 | Qwen3.5 397B A17B |
| Neither model has a result on the other 2 boards here | |||
GeneralLike-for-likePublic boards, shown as published, kept out of the index217
| Benchmark | R1 0528 | Qwen3.5 397B A17B | Leader |
|---|---|---|---|
| IFBench | 39.6% | 78.8% | Qwen3.5 397B A17B |
| Long context reasoning (AA-LCR) | 55.7% | 77.3% | Qwen3.5 397B A17B |
| DTBench | Not measured | 87.5% | Only Qwen3.5 397B A17B measured |
| LMCA | Not measured | 37.9% | Only Qwen3.5 397B A17B measured |
| Fiction.LiveBench | 75.0% | Not measured | Only R1 0528 measured |
| Creative writing (Lech Mazur) | 81.9% | Not measured | Only R1 0528 measured |
| LMArena Text | 1428 | 1437 | Qwen3.5 397B A17B |
| LMArena Text: instruction following | 1382 | 1424 | Qwen3.5 397B A17B |
| LMArena Text: creative writing | 1405 | 1402 | R1 0528 |
| LMArena Vision | Not measured | 1262 | Only Qwen3.5 397B A17B measured |
| LMArena Text: English | 1437 | 1443 | Qwen3.5 397B A17B |
| LMArena Text: non-English | 1412 | 1430 | Qwen3.5 397B A17B |
| LMArena Text: Chinese | 1442 | 1498 | Qwen3.5 397B A17B |
| LMArena Text: German | 1404 | 1445 | Qwen3.5 397B A17B |
| LMArena Text: Japanese | 1391 | 1429 | Qwen3.5 397B A17B |
| LMArena Text: Korean | 1360 | 1384 | Qwen3.5 397B A17B |
| LMArena Text: French | 1417 | 1462 | Qwen3.5 397B A17B |
| LMArena Text: Spanish | 1411 | 1441 | Qwen3.5 397B A17B |
| LMArena Text: Russian | 1423 | 1430 | Qwen3.5 397B A17B |
| LMArena Text: Polish | 1428 | 1447 | Qwen3.5 397B A17B |
| LMArena Text: multi-turn | 1405 | 1446 | Qwen3.5 397B A17B |
| LMArena Text: longer queries | 1391 | 1441 | Qwen3.5 397B A17B |
| LMArena Text: writing and language | 1402 | 1415 | Qwen3.5 397B A17B |
| LMArena Text: entertainment and media | 1400 | 1399 | R1 0528 |
| LMArena Vision: English | Not measured | 1268 | Only Qwen3.5 397B A17B measured |
| LMArena Vision: Chinese | Not measured | 1314 | Only Qwen3.5 397B A17B measured |
| LMArena Vision: reading text | Not measured | 1271 | Only Qwen3.5 397B A17B measured |
| LMArena Vision: humor | Not measured | 1262 | Only Qwen3.5 397B A17B measured |
| LMArena Vision: captioning | Not measured | 1230 | Only Qwen3.5 397B A17B measured |
| LMArena Vision: recognizing things | Not measured | 1265 | Only Qwen3.5 397B A17B measured |
| LMArena Vision: creative writing | Not measured | 1260 | Only Qwen3.5 397B A17B measured |
| Neither model has a result on the other 15 boards here | |||
Image generationNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
| Benchmark | R1 0528 | Qwen3.5 397B A17B | 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 397B A17B costs less
Repository review
50K input + 3K output tokens
Qwen3.5 397B A17B costs less
Agent loop
200K input + 10K output tokens
Qwen3.5 397B A17B 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 | Qwen3.5 397B A17B |
|---|---|---|
| Maker | DeepSeek | Qwen |
| Weights | Open weights | Open weights |
| Released | May 28, 2025 | February 16, 2026 |
| Context window | 164K | 262K |
| Input $/Mtok | $0.50 | $0.39 |
| Output $/Mtok | $2.15 | $2.34 |
| Coding index | 71.4 | 28.6 |
| Independent measurements behind it | 1 | 1 |
| Cost per solved task | Not computable | Not computable |
| Source | OpenRouter listing | OpenRouter listing |
Questions
Is R1 0528 better than Qwen3.5 397B A17B for coding?
Pick R1 0528 for coding: it scores 71.4 on the Vibe Coding Index against 28.6 for Qwen3.5 397B A17B. Pick Qwen3.5 397B A17B when the context window is larger, 262K against 164K tokens, or when what matters is Terminal-Bench Hard (Artificial Analysis run) or LMArena Text: coding, where it leads.
Which is cheaper, R1 0528 or Qwen3.5 397B A17B?
R1 0528 costs $0.50 per million input tokens and $2.15 per million output tokens; Qwen3.5 397B A17B costs $0.39 and $2.34. Cost per solved task is known for neither of them.
Which has the bigger context window, R1 0528 or Qwen3.5 397B A17B?
Qwen3.5 397B A17B, with 262K tokens against 164K.
How many benchmarks is the R1 0528 vs Qwen3.5 397B A17B comparison based on?
45 benchmarks have a result for both models as of October 21, 2026. R1 0528's coding index rests on 1 independent benchmark and Qwen3.5 397B A17B's on 1. Where only one model has a result, the page says so instead of naming a winner.