Qwen3.5 397B A17B vs Inkling Small
Updated October 21, 2026. 49 benchmarks have a result for both. Coding is ranked on the Vibe Coding Index; every other board is shown as published.
Decision reading
Qwen3.5 397B A17B and Inkling Small are level for coding, 28.6 against 29.9 on the Vibe Coding Index, so price and context decide.
Pick Qwen3.5 397B A17B when what matters is LMArena Text: coding or LMArena Text: software and IT, where it leads. Pick Inkling Small when output tokens cost 1.9x less, or when the context window is larger, 524K against 262K tokens.
- Shared results
- 49
- Qwen3.5 397B A17B only
- 16
- Inkling Small only
- 35
- 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
No call
Level: 28.6 against 29.9, inside 2 points.
One benchmark behind each score
Intelligence
AA Intelligence Index
Inkling Small
Inkling Small leads, 25.7 against 21.4.
Same board, both measured
Agentic work
AA Agentic Index
No call
Only Inkling Small has a AA Agentic Index result, 23.5.
Directional only
Reasoning
GPQA Diamond
No call
Only Inkling Small has a GPQA Diamond result, 83.6%.
Directional only
Knowledge
MMLU Pro
No call
Only Inkling Small has a MMLU Pro result, 85.6%.
Directional only
Web design
Design Arena: websites
No call
Only Qwen3.5 397B A17B has a Design Arena: websites result, 1191.
Directional only
General
Vals Index
No call
Only Inkling Small has a Vals Index result, 27.6%.
Directional only
Long documents
Listed context window
Inkling Small
Inkling Small takes 524K tokens against 262K.
Listed by OpenRouter
Everyday cost
1K input + 500 output tokens
Inkling Small
Qwen3.5 397B A17B $0.0016, Inkling Small $0.0010 per turn.
List prices
Cost per solved task
One SWE-bench Verified task, solved
No call
Only Inkling Small has the number, $0.16.
Directional only
At a glance
- Coding index
- Qwen3.5 397B A17B 28.6 from 1 benchmark, Inkling Small 29.9 from 1 benchmark.
- Widest category
- General, 5.4 points apart on average over 24 shared benchmarks.
- Widest single gap
- FrontierMath, tiers 1 to 3: Qwen3.5 397B A17B 31.2% against Inkling Small 46.3%, 15.1 points apart on a 0 to 100 scale.
- Output price
- Qwen3.5 397B A17B $2.34 against Inkling Small $1.20 per million output tokens, 1.9x apart.
- Context window
- Qwen3.5 397B A17B takes 262K tokens, Inkling Small 524K.
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 | Inkling Small | Ties |
|---|---|---|---|---|
| Coding | 3 | 3 | ||
| Intelligence | 0 | 2 | ||
| Reasoning | 6 | 3 | ||
| Math | 1 | 3 | ||
| Knowledge | 4 | 0 | ||
| General | 24 | 0 | ||
| All shared boards | 38 | 11 |
CodingLike-for-likeFour of these boards feed the Vibe Coding Index33
| Benchmark | Qwen3.5 397B A17B | Inkling Small | Leader |
|---|---|---|---|
| LMArena WebDev | 1400 | 1409 | Inkling Small |
| AA Coding Index | Not measured | 52.9 | Only Inkling Small measured |
| LiveCodeBench (Vals AI) | Not measured | 85.9% | Only Inkling Small measured |
| SWE-bench Verified (Vals AI) | Not measured | 82.2% | Only Inkling Small measured |
| Terminal-Bench 4 (Vals AI) | Not measured | 0.0% | Only Inkling Small measured |
| Vibe Code Bench (Vals AI) | Not measured | 19.1% | Only Inkling Small measured |
| Code migration (Vals AI) | Not measured | 13.7% | Only Inkling Small measured |
| ProgramBench (Vals AI) | Not measured | 0.5% | Only Inkling Small measured |
| IOI (Vals AI) | Not measured | 9.3% | Only Inkling Small measured |
| Terminal-Bench 2.1 (Vals AI) | Not measured | 55.1% | Only Inkling Small measured |
| SkillsBench (Vals AI) | Not measured | 33.6% | Only Inkling Small measured |
| CyberBench (Vals AI) | Not measured | 64.1% | Only Inkling Small measured |
| SciCode | 44.8% | 49.7% | Inkling Small |
| 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 | 1450 | Qwen3.5 397B A17B |
| LMArena Text: software and IT | 1463 | 1447 | Qwen3.5 397B A17B |
| LMArena WebDev: React | 1388 | 1399 | Inkling Small |
| LMArena WebDev: HTML | 1410 | 1398 | Qwen3.5 397B A17B |
| LMArena WebDev: from an image | Not measured | 1410 | Only Inkling Small measured |
| Neither model has a result on the other 18 boards here | |||
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index02
| Benchmark | Qwen3.5 397B A17B | Inkling Small | Leader |
|---|---|---|---|
| AA Intelligence Index | 21.4 | 25.7 | Inkling Small |
| Epoch Capabilities Index | 146.8 | 150.3 | Inkling Small |
Agentic workDirectional onlyPublic boards, shown as published, kept out of the index8 boards, none shared
| Benchmark | Qwen3.5 397B A17B | Inkling Small | Leader |
|---|---|---|---|
| AA Agentic Index | Not measured | 23.5 | Only Inkling Small measured |
| Finance Agent (Vals AI) | Not measured | 41.3% | Only Inkling Small measured |
| Tax Agent Bench (Vals AI) | Not measured | 15.4% | Only Inkling Small measured |
| Legal Research Bench (Vals AI) | Not measured | 25.5% | Only Inkling Small measured |
| Harvey's Legal Agent Benchmark (Vals AI) | Not measured | 2.9% | Only Inkling Small measured |
| Excel Modeling Benchmark (Vals AI) | Not measured | 31.8% | Only Inkling Small measured |
| 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 31 boards here | |||
ReasoningLike-for-likePublic boards, shown as published, kept out of the index63
| Benchmark | Qwen3.5 397B A17B | Inkling Small | Leader |
|---|---|---|---|
| GPQA Diamond | Not measured | 83.6% | Only Inkling Small measured |
| GPQA Diamond (Artificial Analysis run) | 89.3% | 89.5% | Inkling Small |
| Humanity's Last Exam (Artificial Analysis run) | 29.0% | 33.3% | Inkling Small |
| GPQA Diamond (Epoch AI run) | 86.4% | 88.5% | Inkling Small |
| ARC-AGI | Not measured | 84.0% | Only Inkling Small measured |
| ARC-AGI-2 | Not measured | 40.1% | Only Inkling Small measured |
| Mystery game puzzles | 18.0% | 6.0% | Qwen3.5 397B A17B |
| LMArena Text: hard prompts | 1448 | 1423 | Qwen3.5 397B A17B |
| LMArena Text: expert | 1462 | 1441 | Qwen3.5 397B A17B |
| LMArena Text: hard prompts in English | 1450 | 1429 | Qwen3.5 397B A17B |
| LMArena Vision: diagrams | 1277 | 1251 | Qwen3.5 397B A17B |
| LMArena Vision: homework | 1292 | 1257 | Qwen3.5 397B A17B |
| Neither model has a result on the other 9 boards here | |||
MathLike-for-likePublic boards, shown as published, kept out of the index13
| Benchmark | Qwen3.5 397B A17B | Inkling Small | Leader |
|---|---|---|---|
| OTIS Mock AIME | 88.9% | 90.0% | Inkling Small |
| FrontierMath, tiers 1 to 3 | 31.2% | 46.3% | Inkling Small |
| FrontierMath, tier 4 | Not measured | 17.1% | Only Inkling Small measured |
| ProofBench | Not measured | 6.0% | Only Inkling Small measured |
| LMArena Text: math | 1453 | 1459 | Inkling Small |
| LMArena Text: mathematical work | 1454 | 1441 | Qwen3.5 397B A17B |
| Neither model has a result on the other 7 boards here | |||
KnowledgeLike-for-likePublic boards, shown as published, kept out of the index40
| Benchmark | Qwen3.5 397B A17B | Inkling Small | Leader |
|---|---|---|---|
| MMLU Pro | Not measured | 85.6% | Only Inkling Small measured |
| LegalBench (Vals AI) | Not measured | 83.0% | Only Inkling Small measured |
| CorpFin (Vals AI) | Not measured | 69.6% | Only Inkling Small measured |
| TaxEval (Vals AI) | Not measured | 75.5% | Only Inkling Small measured |
| MortgageTax (Vals AI) | Not measured | 62.3% | Only Inkling Small measured |
| MedCode (Vals AI) | Not measured | 37.9% | Only Inkling Small measured |
| SimpleQA Verified | Not measured | 19.1% | Only Inkling Small measured |
| LMArena Text: science | 1457 | 1428 | Qwen3.5 397B A17B |
| LMArena Text: medicine and healthcare | 1455 | 1413 | Qwen3.5 397B A17B |
| LMArena Text: legal and government | 1441 | 1415 | Qwen3.5 397B A17B |
| LMArena Text: business and finance | 1435 | 1413 | Qwen3.5 397B A17B |
| Neither model has a result on the other 6 boards here | |||
Web designDirectional onlyPublic boards, shown as published, kept out of the index7 boards, none shared
| Benchmark | Qwen3.5 397B A17B | Inkling Small | Leader |
|---|---|---|---|
| Design Arena: websites | 1191 | Not measured | Only Qwen3.5 397B A17B measured |
| Design Arena: UI components | 1163 | Not measured | Only Qwen3.5 397B A17B measured |
| Design Arena: game dev | 1141 | Not measured | Only Qwen3.5 397B A17B measured |
| 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 index240
| Benchmark | Qwen3.5 397B A17B | Inkling Small | Leader |
|---|---|---|---|
| Vals Index | Not measured | 27.6% | Only Inkling Small measured |
| Public Benefits Bench (Vals AI) | Not measured | 59.4% | Only Inkling Small measured |
| SAGE (Vals AI) | Not measured | 32.7% | Only Inkling Small measured |
| MedScribe (Vals AI) | Not measured | 84.1% | Only Inkling Small measured |
| Vals Multimodal Index | Not measured | 50.0% | Only Inkling Small measured |
| IFBench | 78.8% | Not measured | Only Qwen3.5 397B A17B measured |
| Long context reasoning (AA-LCR) | 77.3% | 75.7% | Qwen3.5 397B A17B |
| 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 | 1413 | Qwen3.5 397B A17B |
| LMArena Text: instruction following | 1424 | 1399 | Qwen3.5 397B A17B |
| LMArena Text: creative writing | 1402 | 1334 | Qwen3.5 397B A17B |
| LMArena Vision | 1262 | 1237 | Qwen3.5 397B A17B |
| LMArena Text: English | 1443 | 1421 | Qwen3.5 397B A17B |
| LMArena Text: non-English | 1430 | 1401 | Qwen3.5 397B A17B |
| LMArena Text: Chinese | 1498 | 1464 | Qwen3.5 397B A17B |
| LMArena Text: German | 1445 | 1408 | Qwen3.5 397B A17B |
| LMArena Text: Japanese | 1429 | 1401 | Qwen3.5 397B A17B |
| LMArena Text: Korean | 1384 | 1367 | Qwen3.5 397B A17B |
| LMArena Text: French | 1462 | 1435 | Qwen3.5 397B A17B |
| LMArena Text: Spanish | 1441 | 1422 | Qwen3.5 397B A17B |
| LMArena Text: Russian | 1430 | 1394 | Qwen3.5 397B A17B |
| LMArena Text: Polish | 1447 | 1428 | Qwen3.5 397B A17B |
| LMArena Text: multi-turn | 1446 | 1416 | Qwen3.5 397B A17B |
| LMArena Text: longer queries | 1441 | 1402 | Qwen3.5 397B A17B |
| LMArena Text: writing and language | 1415 | 1357 | Qwen3.5 397B A17B |
| LMArena Text: entertainment and media | 1399 | 1352 | Qwen3.5 397B A17B |
| LMArena Vision: English | 1268 | 1243 | Qwen3.5 397B A17B |
| LMArena Vision: Chinese | 1314 | 1292 | Qwen3.5 397B A17B |
| LMArena Vision: reading text | 1271 | 1243 | Qwen3.5 397B A17B |
| LMArena Vision: humor | 1262 | 1207 | Qwen3.5 397B A17B |
| 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 | 1205 | Qwen3.5 397B A17B |
| Neither model has a result on the other 12 boards here | |||
Image generationNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
| Benchmark | Qwen3.5 397B A17B | Inkling Small | 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
Inkling Small costs less
Repository review
50K input + 3K output tokens
Inkling Small 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 | Qwen3.5 397B A17B | Thinking Machines Inkling Small |
|---|---|---|
| Maker | Qwen | Thinking Machines |
| Weights | Open weights | Open weights |
| Released | February 16, 2026 | July 30, 2026 |
| Context window | 262K | 524K |
| Input $/Mtok | $0.39 | $0.45 |
| Output $/Mtok | $2.34 | $1.20 |
| Coding index | 28.6 | 29.9 |
| Independent measurements behind it | 1 | 1 |
| Cost per solved task | Not computable | $0.16 |
| Source | OpenRouter listing | OpenRouter listing |
Questions
Is Qwen3.5 397B A17B better than Inkling Small for coding?
Qwen3.5 397B A17B and Inkling Small are level for coding, 28.6 against 29.9 on the Vibe Coding Index, so price and context decide. Pick Qwen3.5 397B A17B when what matters is LMArena Text: coding or LMArena Text: software and IT, where it leads. Pick Inkling Small when output tokens cost 1.9x less, or when the context window is larger, 524K against 262K tokens.
Which is cheaper, Qwen3.5 397B A17B or Inkling Small?
Qwen3.5 397B A17B costs $0.39 per million input tokens and $2.34 per million output tokens; Inkling Small costs $0.45 and $1.20. Cost per solved task is known for Inkling Small only.
Which has the bigger context window, Qwen3.5 397B A17B or Inkling Small?
Inkling Small, with 524K tokens against 262K.
How many benchmarks is the Qwen3.5 397B A17B vs Inkling Small comparison based on?
49 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 Inkling Small's on 1. Where only one model has a result, the page says so instead of naming a winner.