Qwen3 32B vs Extract
Updated October 21, 2026. 0 benchmarks have a result for both. Coding is ranked on the Vibe Coding Index; every other board is shown as published.
- Coding
- No data
- Overall
- 7.3
- Output $/M
- $0.40
- Coding
- No data
- Overall
- No data
- Output $/M
- No data
Decision reading
Neither model has a coding score yet, so the two cannot be ranked on coding.
Compare them on price, context and the boards below.
- Shared results
- 0
- Qwen3 32B only
- 42
- Extract only
- 0
- Like-for-like categories
- 0 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, six public coding benchmarks
No call
Neither has a coding score yet.
One side not measured
Intelligence
AA Intelligence Index
No call
Only Qwen3 32B has a AA Intelligence Index result, 7.3.
Directional only
Long documents
Listed context window
Extract
Extract takes 1M tokens against 131K.
Listed by OpenRouter
Everyday cost
1K input + 500 output tokens
Extract
Qwen3 32B $0.0003, Extract $0.0000 per turn.
List prices
At a glance
- Coding index
- Qwen3 32B not benchmarked, Extract not benchmarked.
- Widest category
- No category has a result for both models.
- Widest single gap
- No benchmark has a result for both models.
- Output price
- Qwen3 32B $0.40 against Extract Free per million output tokens.
- Context window
- Qwen3 32B takes 131K tokens, Extract 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.
CodingDirectional onlySix of these boards feed the Vibe Coding Index6 boards, none shared
| Benchmark | Qwen3 32B | Extract | Leader |
|---|---|---|---|
| Aider polyglot | 40.0% | Not measured | Only Qwen3 32B measured |
| LiveCodeBench (Artificial Analysis run) | 54.6% | Not measured | Only Qwen3 32B measured |
| SciCode | 36.0% | Not measured | Only Qwen3 32B measured |
| Terminal-Bench Hard (Artificial Analysis run) | 3.0% | Not measured | Only Qwen3 32B measured |
| LMArena Text: coding | 1357 | Not measured | Only Qwen3 32B measured |
| LMArena Text: software and IT | 1366 | Not measured | Only Qwen3 32B measured |
| Neither model has a result on the other 32 boards here | |||
IntelligenceDirectional onlyPublic boards, shown as published, kept out of the index2 boards, none shared
| Benchmark | Qwen3 32B | Extract | Leader |
|---|---|---|---|
| AA Intelligence Index | 7.3 | Not measured | Only Qwen3 32B measured |
| Epoch Capabilities Index | 138.4 | Not measured | Only Qwen3 32B measured |
Agentic workDirectional onlyPublic boards, shown as published, kept out of the index1 board, none shared
| Benchmark | Qwen3 32B | Extract | Leader |
|---|---|---|---|
| τ²-Bench Telecom | 29.8% | Not measured | Only Qwen3 32B measured |
| Neither model has a result on the other 38 boards here | |||
ReasoningDirectional onlyPublic boards, shown as published, kept out of the index6 boards, none shared
| Benchmark | Qwen3 32B | Extract | Leader |
|---|---|---|---|
| GPQA Diamond (Artificial Analysis run) | 66.8% | Not measured | Only Qwen3 32B measured |
| Humanity's Last Exam (Artificial Analysis run) | 7.4% | Not measured | Only Qwen3 32B measured |
| GPQA Diamond (Epoch AI run) | 65.7% | Not measured | Only Qwen3 32B measured |
| LMArena Text: hard prompts | 1334 | Not measured | Only Qwen3 32B measured |
| LMArena Text: expert | 1362 | Not measured | Only Qwen3 32B measured |
| LMArena Text: hard prompts in English | 1350 | Not measured | Only Qwen3 32B measured |
| Neither model has a result on the other 15 boards here | |||
MathDirectional onlyPublic boards, shown as published, kept out of the index5 boards, none shared
| Benchmark | Qwen3 32B | Extract | Leader |
|---|---|---|---|
| AA Math Index | 73.0 | Not measured | Only Qwen3 32B measured |
| AIME 2025 (Artificial Analysis run) | 73.0% | Not measured | Only Qwen3 32B measured |
| OTIS Mock AIME | 66.9% | Not measured | Only Qwen3 32B measured |
| LMArena Text: math | 1399 | Not measured | Only Qwen3 32B measured |
| LMArena Text: mathematical work | 1420 | Not measured | Only Qwen3 32B measured |
| Neither model has a result on the other 8 boards here | |||
KnowledgeDirectional onlyPublic boards, shown as published, kept out of the index5 boards, none shared
| Benchmark | Qwen3 32B | Extract | Leader |
|---|---|---|---|
| MMLU Pro (Artificial Analysis run) | 79.8% | Not measured | Only Qwen3 32B measured |
| LMArena Text: science | 1372 | Not measured | Only Qwen3 32B measured |
| LMArena Text: medicine and healthcare | 1368 | Not measured | Only Qwen3 32B measured |
| LMArena Text: legal and government | 1324 | Not measured | Only Qwen3 32B measured |
| LMArena Text: business and finance | 1318 | Not measured | Only Qwen3 32B measured |
| Neither model has a result on the other 12 boards here | |||
Web designNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
| Benchmark | Qwen3 32B | Extract | Leader |
|---|---|---|---|
| Neither model has a result on 9 boards here | |||
GeneralDirectional onlyPublic boards, shown as published, kept out of the index17 boards, none shared
| Benchmark | Qwen3 32B | Extract | Leader |
|---|---|---|---|
| IFBench | 36.3% | Not measured | Only Qwen3 32B measured |
| Long context reasoning (AA-LCR) | 0.0% | Not measured | Only Qwen3 32B measured |
| DTBench | 67.5% | Not measured | Only Qwen3 32B measured |
| LMCA | 17.3% | Not measured | Only Qwen3 32B measured |
| Fiction.LiveBench | 74.2% | Not measured | Only Qwen3 32B measured |
| LMArena Text | 1340 | Not measured | Only Qwen3 32B measured |
| LMArena Text: instruction following | 1305 | Not measured | Only Qwen3 32B measured |
| LMArena Text: creative writing | 1297 | Not measured | Only Qwen3 32B measured |
| LMArena Text: English | 1359 | Not measured | Only Qwen3 32B measured |
| LMArena Text: non-English | 1317 | Not measured | Only Qwen3 32B measured |
| LMArena Text: Chinese | 1357 | Not measured | Only Qwen3 32B measured |
| LMArena Text: German | 1341 | Not measured | Only Qwen3 32B measured |
| LMArena Text: Russian | 1311 | Not measured | Only Qwen3 32B measured |
| LMArena Text: multi-turn | 1331 | Not measured | Only Qwen3 32B measured |
| LMArena Text: longer queries | 1327 | Not measured | Only Qwen3 32B measured |
| LMArena Text: writing and language | 1298 | Not measured | Only Qwen3 32B measured |
| LMArena Text: entertainment and media | 1279 | Not measured | Only Qwen3 32B measured |
| Neither model has a result on the other 29 boards here | |||
Image generationNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
| Benchmark | Qwen3 32B | Extract | 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
Extract costs less
Repository review
50K input + 3K output tokens
Extract costs less
Agent loop
200K input + 10K output tokens
Extract 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 32B | ScaleDown Extract |
|---|---|---|
| Maker | Qwen | Scaledown |
| Weights | Open weights | No public weights listed |
| Released | April 28, 2025 | October 13, 2026 |
| Context window | 131K | 1M |
| Input $/Mtok | $0.14 | $0.04 |
| Output $/Mtok | $0.40 | Free |
| Coding index | Not benchmarked | Not benchmarked |
| Independent measurements behind it | 0 | 0 |
| Cost per solved task | Not computable | Not computable |
| Source | OpenRouter listing | OpenRouter listing |
Questions
Is Qwen3 32B better than Extract for coding?
Neither model has a coding score yet, so the two cannot be ranked on coding. Compare them on price, context and the boards below.
Which is cheaper, Qwen3 32B or Extract?
Qwen3 32B costs $0.14 per million input tokens and $0.40 per million output tokens; Extract costs $0.04 and Free. Cost per solved task is known for neither of them.
Which has the bigger context window, Qwen3 32B or Extract?
Extract, with 1M tokens against 131K.
How many benchmarks is the Qwen3 32B vs Extract comparison based on?
0 benchmarks have a result for both models as of October 21, 2026. Qwen3 32B's coding index rests on 0 independent benchmarks and Extract's on 0. Where only one model has a result, the page says so instead of naming a winner.