Qwen3.5 397B A17B vs Beam 1.0 501B A23B
Updated October 21, 2026. 28 benchmarks have a result for both. Coding is ranked on the Vibe Coding Index; every other board is shown as published.
Decision reading
Pick Beam 1.0 501B A23B for coding: it scores 33.8 on the Vibe Coding Index against 28.6 for Qwen3.5 397B A17B.
Pick Qwen3.5 397B A17B when what matters is LMArena Text: software and IT or LMArena Text: hard prompts, where it leads.
- Shared results
- 28
- Qwen3.5 397B A17B only
- 37
- Beam 1.0 501B A23B only
- 0
- Like-for-like categories
- 6 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
Beam 1.0 501B A23B
Beam 1.0 501B A23B scores 33.8 against 28.6.
One benchmark behind each score
Intelligence
AA Intelligence Index
No call
Only Qwen3.5 397B A17B has a AA Intelligence Index result, 21.4.
Directional only
Web design
Design Arena: websites
Beam 1.0 501B A23B
Beam 1.0 501B A23B leads, 1253 against 1191.
Same board, both measured
Long documents
Listed context window
Beam 1.0 501B A23B
Beam 1.0 501B A23B takes 1.05M tokens against 262K.
Listed by OpenRouter
Everyday cost
1K input + 500 output tokens
Beam 1.0 501B A23B
Qwen3.5 397B A17B $0.0016, Beam 1.0 501B A23B $0.0008 per turn.
List prices
At a glance
- Coding index
- Qwen3.5 397B A17B 28.6 from 1 benchmark, Beam 1.0 501B A23B 33.8 from 1 benchmark.
- Widest category
- Web design, 8.9 points apart on average over 2 shared benchmarks.
- Widest single gap
- LMArena Text: medicine and healthcare: Qwen3.5 397B A17B 1455 against Beam 1.0 501B A23B 1376, 13.2 points apart on a 0 to 100 scale.
- Output price
- Qwen3.5 397B A17B $2.34 against Beam 1.0 501B A23B $1.00 per million output tokens, 2.3x apart.
- Context window
- Qwen3.5 397B A17B takes 262K tokens, Beam 1.0 501B A23B 1.05M.
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 | Qwen3.5 397B A17B | Bars | Beam 1.0 501B A23B | Ties |
|---|---|---|---|---|
| Coding | 1 | 4 | ||
| Reasoning | 2 | 1 | ||
| Math | 0 | 2 | ||
| Knowledge | 4 | 0 | ||
| Web design | 0 | 2 | ||
| General | 10 | 2 | ||
| All shared boards | 17 | 11 |
CodingLike-for-likeFour of these boards feed the Vibe Coding Index14
| Benchmark | Qwen3.5 397B A17B | Beam 1.0 501B A23B | Leader |
|---|---|---|---|
| LMArena WebDev | 1400 | 1437 | Beam 1.0 501B A23B |
| SciCode | 44.8% | Not measured | Only Qwen3.5 397B A17B measured |
| Terminal-Bench Hard (Artificial Analysis run) | 40.9% | Not measured | Only Qwen3.5 397B A17B measured |
| ALE-Bench | 621.9 | Not measured | Only Qwen3.5 397B A17B measured |
| LMArena Text: coding | 1464 | 1473 | Beam 1.0 501B A23B |
| LMArena Text: software and IT | 1463 | 1461 | Qwen3.5 397B A17B |
| LMArena WebDev: React | 1388 | 1443 | Beam 1.0 501B A23B |
| LMArena WebDev: HTML | 1410 | 1436 | Beam 1.0 501B A23B |
| Neither model has a result on the other 30 boards here | |||
IntelligenceDirectional onlyPublic boards, shown as published, kept out of the index2 boards, none shared
| Benchmark | Qwen3.5 397B A17B | Beam 1.0 501B A23B | Leader |
|---|---|---|---|
| AA Intelligence Index | 21.4 | Not measured | Only Qwen3.5 397B A17B measured |
| Epoch Capabilities Index | 146.8 | Not measured | Only Qwen3.5 397B A17B measured |
Agentic workDirectional onlyPublic boards, shown as published, kept out of the index2 boards, none shared
| Benchmark | Qwen3.5 397B A17B | Beam 1.0 501B A23B | Leader |
|---|---|---|---|
| τ²-Bench Telecom | 95.6% | Not measured | Only Qwen3.5 397B A17B measured |
| APEX-Agents | 24.9% | Not measured | Only Qwen3.5 397B A17B measured |
| Neither model has a result on the other 37 boards here | |||
ReasoningLike-for-likePublic boards, shown as published, kept out of the index21
| Benchmark | Qwen3.5 397B A17B | Beam 1.0 501B A23B | Leader |
|---|---|---|---|
| GPQA Diamond (Artificial Analysis run) | 89.3% | Not measured | Only Qwen3.5 397B A17B measured |
| Humanity's Last Exam (Artificial Analysis run) | 29.0% | Not measured | Only Qwen3.5 397B A17B measured |
| GPQA Diamond (Epoch AI run) | 86.4% | Not measured | Only Qwen3.5 397B A17B measured |
| Mystery game puzzles | 18.0% | Not measured | Only Qwen3.5 397B A17B measured |
| LMArena Text: hard prompts | 1448 | 1442 | Qwen3.5 397B A17B |
| LMArena Text: expert | 1462 | 1447 | Qwen3.5 397B A17B |
| LMArena Text: hard prompts in English | 1450 | 1451 | Beam 1.0 501B A23B |
| LMArena Vision: diagrams | 1277 | Not measured | Only Qwen3.5 397B A17B measured |
| LMArena Vision: homework | 1292 | Not measured | Only Qwen3.5 397B A17B measured |
| Neither model has a result on the other 12 boards here | |||
MathLike-for-likePublic boards, shown as published, kept out of the index02
| Benchmark | Qwen3.5 397B A17B | Beam 1.0 501B A23B | Leader |
|---|---|---|---|
| OTIS Mock AIME | 88.9% | Not measured | Only Qwen3.5 397B A17B measured |
| FrontierMath, tiers 1 to 3 | 31.2% | Not measured | Only Qwen3.5 397B A17B measured |
| LMArena Text: math | 1453 | 1459 | Beam 1.0 501B A23B |
| LMArena Text: mathematical work | 1454 | 1475 | Beam 1.0 501B A23B |
| Neither model has a result on the other 9 boards here | |||
KnowledgeLike-for-likePublic boards, shown as published, kept out of the index40
| Benchmark | Qwen3.5 397B A17B | Beam 1.0 501B A23B | Leader |
|---|---|---|---|
| LMArena Text: science | 1457 | 1430 | Qwen3.5 397B A17B |
| LMArena Text: medicine and healthcare | 1455 | 1376 | Qwen3.5 397B A17B |
| LMArena Text: legal and government | 1441 | 1433 | Qwen3.5 397B A17B |
| LMArena Text: business and finance | 1435 | 1430 | Qwen3.5 397B A17B |
| Neither model has a result on the other 13 boards here | |||
Web designLike-for-likePublic boards, shown as published, kept out of the index02
| Benchmark | Qwen3.5 397B A17B | Beam 1.0 501B A23B | Leader |
|---|---|---|---|
| Design Arena: websites | 1191 | 1253 | Beam 1.0 501B A23B |
| Design Arena: UI components | 1163 | Not measured | Only Qwen3.5 397B A17B measured |
| Design Arena: game dev | 1141 | 1222 | Beam 1.0 501B A23B |
| Design Arena: data viz | 1175 | Not measured | Only Qwen3.5 397B A17B measured |
| Design Arena: 3D | 1161 | Not measured | Only Qwen3.5 397B A17B measured |
| Design Arena: all code categories | 1180 | Not measured | Only Qwen3.5 397B A17B measured |
| Design Arena: SVG | 1139 | Not measured | Only Qwen3.5 397B A17B measured |
| Neither model has a result on the other 2 boards here | |||
GeneralLike-for-likePublic boards, shown as published, kept out of the index102
| Benchmark | Qwen3.5 397B A17B | Beam 1.0 501B A23B | Leader |
|---|---|---|---|
| IFBench | 78.8% | Not measured | Only Qwen3.5 397B A17B measured |
| Long context reasoning (AA-LCR) | 77.3% | Not measured | Only Qwen3.5 397B A17B measured |
| DTBench | 87.5% | Not measured | Only Qwen3.5 397B A17B measured |
| LMCA | 37.9% | Not measured | Only Qwen3.5 397B A17B measured |
| LMArena Text | 1437 | 1425 | Qwen3.5 397B A17B |
| LMArena Text: instruction following | 1424 | 1430 | Beam 1.0 501B A23B |
| LMArena Text: creative writing | 1402 | 1390 | Qwen3.5 397B A17B |
| LMArena Vision | 1262 | Not measured | Only Qwen3.5 397B A17B measured |
| LMArena Text: English | 1443 | 1436 | Qwen3.5 397B A17B |
| LMArena Text: non-English | 1430 | 1413 | Qwen3.5 397B A17B |
| LMArena Text: Chinese | 1498 | 1424 | Qwen3.5 397B A17B |
| LMArena Text: German | 1445 | Not measured | Only Qwen3.5 397B A17B measured |
| LMArena Text: Japanese | 1429 | Not measured | Only Qwen3.5 397B A17B measured |
| LMArena Text: Korean | 1384 | Not measured | Only Qwen3.5 397B A17B measured |
| LMArena Text: French | 1462 | 1461 | Qwen3.5 397B A17B |
| LMArena Text: Spanish | 1441 | Not measured | Only Qwen3.5 397B A17B measured |
| LMArena Text: Russian | 1430 | 1412 | Qwen3.5 397B A17B |
| LMArena Text: Polish | 1447 | Not measured | Only Qwen3.5 397B A17B measured |
| LMArena Text: multi-turn | 1446 | 1414 | Qwen3.5 397B A17B |
| LMArena Text: longer queries | 1441 | 1429 | Qwen3.5 397B A17B |
| LMArena Text: writing and language | 1415 | 1400 | Qwen3.5 397B A17B |
| LMArena Text: entertainment and media | 1399 | 1399 | Beam 1.0 501B A23B |
| LMArena Vision: English | 1268 | Not measured | Only Qwen3.5 397B A17B measured |
| LMArena Vision: Chinese | 1314 | Not measured | Only Qwen3.5 397B A17B measured |
| LMArena Vision: reading text | 1271 | Not measured | Only Qwen3.5 397B A17B measured |
| LMArena Vision: humor | 1262 | Not measured | Only Qwen3.5 397B A17B measured |
| LMArena Vision: captioning | 1230 | Not measured | Only Qwen3.5 397B A17B measured |
| LMArena Vision: recognizing things | 1265 | Not measured | Only Qwen3.5 397B A17B measured |
| LMArena Vision: creative writing | 1260 | Not measured | Only Qwen3.5 397B A17B measured |
| Neither model has a result on the other 17 boards here | |||
Image generationNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
| Benchmark | Qwen3.5 397B A17B | Beam 1.0 501B A23B | 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
Beam 1.0 501B A23B costs less
Repository review
50K input + 3K output tokens
Beam 1.0 501B A23B costs less
Agent loop
200K input + 10K output tokens
Beam 1.0 501B A23B 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 | Qwen3.5 397B A17B | Reflection Beam 1.0 501B A23B |
|---|---|---|
| Maker | Qwen | Reflection |
| Weights | Open weights | Open weights |
| Released | February 16, 2026 | October 16, 2026 |
| Context window | 262K | 1.05M |
| Input $/Mtok | $0.39 | $0.30 |
| Output $/Mtok | $2.34 | $1.00 |
| Coding index | 28.6 | 33.8 |
| Independent measurements behind it | 1 | 1 |
| Cost per solved task | Not computable | Not computable |
| Source | OpenRouter listing | OpenRouter listing |
Questions
Is Qwen3.5 397B A17B better than Beam 1.0 501B A23B for coding?
Pick Beam 1.0 501B A23B for coding: it scores 33.8 on the Vibe Coding Index against 28.6 for Qwen3.5 397B A17B. Pick Qwen3.5 397B A17B when what matters is LMArena Text: software and IT or LMArena Text: hard prompts, where it leads.
Which is cheaper, Qwen3.5 397B A17B or Beam 1.0 501B A23B?
Qwen3.5 397B A17B costs $0.39 per million input tokens and $2.34 per million output tokens; Beam 1.0 501B A23B costs $0.30 and $1.00. Cost per solved task is known for neither of them.
Which has the bigger context window, Qwen3.5 397B A17B or Beam 1.0 501B A23B?
Beam 1.0 501B A23B, with 1.05M tokens against 262K.
How many benchmarks is the Qwen3.5 397B A17B vs Beam 1.0 501B A23B comparison based on?
28 benchmarks have a result for both models as of October 21, 2026. Qwen3.5 397B A17B's coding index rests on 1 independent benchmark and Beam 1.0 501B A23B's on 1. Where only one model has a result, the page says so instead of naming a winner.