Qwen2.5 Coder 32B Instruct vs Qwen3.7 Plus
Updated October 21, 2026. 26 benchmarks have a result for both. Coding is ranked on the Vibe Coding Index; every other board is shown as published.
Decision reading
Only Qwen3.7 Plus has a coding score, 33.2 on the Vibe Coding Index; Qwen2.5 Coder 32B Instruct has none, so the two cannot be ranked on coding.
Qwen2.5 Coder 32B Instruct has the edge where output tokens cost 1.3x less.
- Shared results
- 26
- Qwen2.5 Coder 32B Instruct only
- 9
- Qwen3.7 Plus only
- 49
- 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, six public coding benchmarks
No call
Only Qwen3.7 Plus has a coding score, so no call is made.
One side not measured
Intelligence
AA Intelligence Index
Qwen3.7 Plus
Qwen3.7 Plus leads, 25.2 against 6.7.
Same board, both measured
Agentic work
AA Agentic Index
No call
Only Qwen3.7 Plus has a AA Agentic Index result, 17.5.
Directional only
Web design
Design Arena: websites
No call
Only Qwen3.7 Plus has a Design Arena: websites result, 1269.
Directional only
Long documents
Listed context window
Qwen3.7 Plus
Qwen3.7 Plus takes 1M tokens against 33K.
Listed by OpenRouter
Everyday cost
1K input + 500 output tokens
Qwen3.7 Plus
Qwen2.5 Coder 32B Instruct $0.0012, Qwen3.7 Plus $0.0010 per turn.
List prices
At a glance
- Coding index
- Qwen2.5 Coder 32B Instruct not benchmarked, Qwen3.7 Plus 33.2 from 2 benchmarks.
- Widest category
- General, 39.9 points apart on average over 11 shared benchmarks.
- Widest single gap
- GPQA Diamond (Artificial Analysis run): Qwen2.5 Coder 32B Instruct 41.7% against Qwen3.7 Plus 90.0%, 48.3 points apart on a 0 to 100 scale.
- Output price
- Qwen2.5 Coder 32B Instruct $1.00 against Qwen3.7 Plus $1.28 per million output tokens, 1.3x apart.
- Context window
- Qwen2.5 Coder 32B Instruct takes 33K tokens, Qwen3.7 Plus 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 | Qwen2.5 Coder 32B Instruct | Bars | Qwen3.7 Plus | Ties |
|---|---|---|---|---|
| Coding | 0 | 2 | ||
| Intelligence | 0 | 2 | ||
| Reasoning | 0 | 5 | ||
| Math | 0 | 2 | ||
| Knowledge | 0 | 4 | ||
| General | 0 | 11 | ||
| All shared boards | 0 | 26 |
CodingLike-for-likeSix of these boards feed the Vibe Coding Index02
| Benchmark | Qwen2.5 Coder 32B Instruct | Qwen3.7 Plus | Leader |
|---|---|---|---|
| Aider polyglot | 16.4% | Not measured | Only Qwen2.5 Coder 32B Instruct measured |
| SWE-bench Verified | 47.0% | Not measured | Only Qwen2.5 Coder 32B Instruct measured |
| AA Coding Index | Not measured | 55.9 | Only Qwen3.7 Plus measured |
| Vibe Code Bench (Vals AI) | Not measured | 46.4% | Only Qwen3.7 Plus measured |
| Code migration (Vals AI) | Not measured | 12.9% | Only Qwen3.7 Plus measured |
| Terminal-Bench 2.1 (Vals AI) | Not measured | 52.8% | Only Qwen3.7 Plus measured |
| SkillsBench (Vals AI) | Not measured | 54.3% | Only Qwen3.7 Plus measured |
| LiveCodeBench (Artificial Analysis run) | 29.5% | Not measured | Only Qwen2.5 Coder 32B Instruct measured |
| SciCode | Not measured | 46.1% | Only Qwen3.7 Plus measured |
| Terminal-Bench Hard (Artificial Analysis run) | Not measured | 47.0% | Only Qwen3.7 Plus measured |
| FrontierCode | Not measured | 10.2% | Only Qwen3.7 Plus measured |
| LMArena Text: coding | 1276 | 1473 | Qwen3.7 Plus |
| LMArena Text: software and IT | 1261 | 1473 | Qwen3.7 Plus |
| Neither model has a result on the other 25 boards here | |||
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index02
| Benchmark | Qwen2.5 Coder 32B Instruct | Qwen3.7 Plus | Leader |
|---|---|---|---|
| AA Intelligence Index | 6.7 | 25.2 | Qwen3.7 Plus |
| Epoch Capabilities Index | 119.5 | 147.0 | Qwen3.7 Plus |
Agentic workDirectional onlyPublic boards, shown as published, kept out of the index7 boards, none shared
| Benchmark | Qwen2.5 Coder 32B Instruct | Qwen3.7 Plus | Leader |
|---|---|---|---|
| AA Agentic Index | Not measured | 17.5 | Only Qwen3.7 Plus measured |
| Finance Agent (Vals AI) | Not measured | 38.2% | Only Qwen3.7 Plus measured |
| Tax Agent Bench (Vals AI) | Not measured | 10.5% | Only Qwen3.7 Plus measured |
| Legal Research Bench (Vals AI) | Not measured | 16.4% | Only Qwen3.7 Plus measured |
| Excel Modeling Benchmark (Vals AI) | Not measured | 49.3% | Only Qwen3.7 Plus measured |
| τ²-Bench Telecom | Not measured | 93.0% | Only Qwen3.7 Plus measured |
| OSWorld 2.0 | Not measured | 2.8% | Only Qwen3.7 Plus measured |
| Neither model has a result on the other 32 boards here | |||
ReasoningLike-for-likePublic boards, shown as published, kept out of the index05
| Benchmark | Qwen2.5 Coder 32B Instruct | Qwen3.7 Plus | Leader |
|---|---|---|---|
| GPQA Diamond (Artificial Analysis run) | 41.7% | 90.0% | Qwen3.7 Plus |
| Humanity's Last Exam (Artificial Analysis run) | 3.5% | 35.6% | Qwen3.7 Plus |
| GPQA Diamond (Epoch AI run) | Not measured | 87.9% | Only Qwen3.7 Plus measured |
| Mystery game puzzles | Not measured | 17.0% | Only Qwen3.7 Plus measured |
| LMArena Text: hard prompts | 1251 | 1460 | Qwen3.7 Plus |
| LMArena Text: expert | 1221 | 1466 | Qwen3.7 Plus |
| LMArena Text: hard prompts in English | 1269 | 1460 | Qwen3.7 Plus |
| LMArena Vision: diagrams | Not measured | 1292 | Only Qwen3.7 Plus measured |
| LMArena Vision: homework | Not measured | 1295 | Only Qwen3.7 Plus 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 | Qwen2.5 Coder 32B Instruct | Qwen3.7 Plus | Leader |
|---|---|---|---|
| OTIS Mock AIME | Not measured | 93.3% | Only Qwen3.7 Plus measured |
| FrontierMath, tiers 1 to 3 | Not measured | 34.4% | Only Qwen3.7 Plus measured |
| GSM8K | 93.0% | Not measured | Only Qwen2.5 Coder 32B Instruct measured |
| LMArena Text: math | 1251 | 1467 | Qwen3.7 Plus |
| LMArena Text: mathematical work | 1243 | 1470 | Qwen3.7 Plus |
| Neither model has a result on the other 8 boards here | |||
KnowledgeLike-for-likePublic boards, shown as published, kept out of the index04
| Benchmark | Qwen2.5 Coder 32B Instruct | Qwen3.7 Plus | Leader |
|---|---|---|---|
| MortgageTax (Vals AI) | Not measured | 66.2% | Only Qwen3.7 Plus measured |
| MMLU Pro (Artificial Analysis run) | 63.5% | Not measured | Only Qwen2.5 Coder 32B Instruct measured |
| MMLU | 79.1% | Not measured | Only Qwen2.5 Coder 32B Instruct measured |
| AI2 Reasoning Challenge | 70.5% | Not measured | Only Qwen2.5 Coder 32B Instruct measured |
| LMArena Text: science | 1221 | 1464 | Qwen3.7 Plus |
| LMArena Text: medicine and healthcare | 1187 | 1464 | Qwen3.7 Plus |
| LMArena Text: legal and government | 1257 | 1451 | Qwen3.7 Plus |
| LMArena Text: business and finance | 1224 | 1435 | Qwen3.7 Plus |
| Neither model has a result on the other 9 boards here | |||
Web designDirectional onlyPublic boards, shown as published, kept out of the index8 boards, none shared
| Benchmark | Qwen2.5 Coder 32B Instruct | Qwen3.7 Plus | Leader |
|---|---|---|---|
| Design Arena: websites | Not measured | 1269 | Only Qwen3.7 Plus measured |
| Design Arena: UI components | Not measured | 1261 | Only Qwen3.7 Plus measured |
| Design Arena: game dev | Not measured | 1262 | Only Qwen3.7 Plus measured |
| Design Arena: data viz | Not measured | 1275 | Only Qwen3.7 Plus measured |
| Design Arena: 3D | Not measured | 1239 | Only Qwen3.7 Plus measured |
| Design Arena: all code categories | Not measured | 1269 | Only Qwen3.7 Plus measured |
| Design Arena: SVG | Not measured | 1208 | Only Qwen3.7 Plus measured |
| Design Arena: ASCII art | Not measured | 1144 | Only Qwen3.7 Plus measured |
| Neither model has a result on the other 1 board here | |||
GeneralLike-for-likePublic boards, shown as published, kept out of the index011
| Benchmark | Qwen2.5 Coder 32B Instruct | Qwen3.7 Plus | Leader |
|---|---|---|---|
| SAGE (Vals AI) | Not measured | 39.3% | Only Qwen3.7 Plus measured |
| Vals Multimodal Index | Not measured | 53.9% | Only Qwen3.7 Plus measured |
| IFBench | Not measured | 78.0% | Only Qwen3.7 Plus measured |
| Long context reasoning (AA-LCR) | Not measured | 73.0% | Only Qwen3.7 Plus measured |
| DTBench | Not measured | 84.0% | Only Qwen3.7 Plus measured |
| LMCA | Not measured | 37.6% | Only Qwen3.7 Plus measured |
| HellaSwag | 83.0% | Not measured | Only Qwen2.5 Coder 32B Instruct measured |
| WinoGrande | 80.8% | Not measured | Only Qwen2.5 Coder 32B Instruct measured |
| LMArena Text | 1230 | 1454 | Qwen3.7 Plus |
| LMArena Text: instruction following | 1223 | 1439 | Qwen3.7 Plus |
| LMArena Text: creative writing | 1174 | 1438 | Qwen3.7 Plus |
| LMArena Vision | Not measured | 1278 | Only Qwen3.7 Plus measured |
| LMArena Text: English | 1248 | 1458 | Qwen3.7 Plus |
| LMArena Text: non-English | 1205 | 1445 | Qwen3.7 Plus |
| LMArena Text: Chinese | 1222 | 1509 | Qwen3.7 Plus |
| LMArena Text: German | Not measured | 1471 | Only Qwen3.7 Plus measured |
| LMArena Text: Japanese | Not measured | 1412 | Only Qwen3.7 Plus measured |
| LMArena Text: Korean | Not measured | 1413 | Only Qwen3.7 Plus measured |
| LMArena Text: French | Not measured | 1472 | Only Qwen3.7 Plus measured |
| LMArena Text: Spanish | Not measured | 1457 | Only Qwen3.7 Plus measured |
| LMArena Text: Russian | 1228 | 1457 | Qwen3.7 Plus |
| LMArena Text: Polish | Not measured | 1449 | Only Qwen3.7 Plus measured |
| LMArena Text: multi-turn | 1222 | 1459 | Qwen3.7 Plus |
| LMArena Text: longer queries | 1251 | 1454 | Qwen3.7 Plus |
| LMArena Text: writing and language | 1191 | 1437 | Qwen3.7 Plus |
| LMArena Text: entertainment and media | 1150 | 1422 | Qwen3.7 Plus |
| LMArena Vision: English | Not measured | 1280 | Only Qwen3.7 Plus measured |
| LMArena Vision: Chinese | Not measured | 1332 | Only Qwen3.7 Plus measured |
| LMArena Vision: reading text | Not measured | 1288 | Only Qwen3.7 Plus measured |
| LMArena Vision: humor | Not measured | 1261 | Only Qwen3.7 Plus measured |
| LMArena Vision: creative writing | Not measured | 1258 | Only Qwen3.7 Plus measured |
| LMArena Document | Not measured | 1444 | Only Qwen3.7 Plus measured |
| Neither model has a result on the other 14 boards here | |||
Image generationNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
| Benchmark | Qwen2.5 Coder 32B Instruct | Qwen3.7 Plus | 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
Qwen3.7 Plus costs less
Repository review
50K input + 3K output tokens
Qwen3.7 Plus costs less
Agent loop
200K input + 10K output tokens
Qwen3.7 Plus 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 | Qwen2.5 Coder 32B Instruct | Qwen3.7 Plus |
|---|---|---|
| Maker | Qwen | Qwen |
| Weights | Open weights | No public weights listed |
| Released | November 11, 2024 | June 3, 2026 |
| Context window | 33K | 1M |
| Input $/Mtok | $0.66 | $0.32 |
| Output $/Mtok | $1.00 | $1.28 |
| Coding index | Not benchmarked | 33.2 |
| Independent measurements behind it | 0 | 2 |
| Cost per solved task | Not computable | Not computable |
| Source | OpenRouter listing | OpenRouter listing |
Questions
Is Qwen2.5 Coder 32B Instruct better than Qwen3.7 Plus for coding?
Only Qwen3.7 Plus has a coding score, 33.2 on the Vibe Coding Index; Qwen2.5 Coder 32B Instruct has none, so the two cannot be ranked on coding. Qwen2.5 Coder 32B Instruct has the edge where output tokens cost 1.3x less.
Which is cheaper, Qwen2.5 Coder 32B Instruct or Qwen3.7 Plus?
Qwen2.5 Coder 32B Instruct costs $0.66 per million input tokens and $1.00 per million output tokens; Qwen3.7 Plus costs $0.32 and $1.28. Cost per solved task is known for neither of them.
Which has the bigger context window, Qwen2.5 Coder 32B Instruct or Qwen3.7 Plus?
Qwen3.7 Plus, with 1M tokens against 33K.
How many benchmarks is the Qwen2.5 Coder 32B Instruct vs Qwen3.7 Plus comparison based on?
26 benchmarks have a result for both models as of October 21, 2026. Qwen2.5 Coder 32B Instruct's coding index rests on 0 independent benchmarks and Qwen3.7 Plus's on 2. Where only one model has a result, the page says so instead of naming a winner.