Qwen2.5 Coder 32B Instruct vs Qwen3 30B A3B Instruct 2507
Qwen3 30B A3B Instruct 2507 leads Qwen2.5 Coder 32B Instruct on the Artificial Analysis Intelligence Index, 7.5 to 6.7, and Qwen3 30B A3B Instruct 2507 costs 3.3x less per output token ($0.30 vs $1.00 per million). Updated October 22, 2026; 27 benchmarks have a result for both.
Qwen2.5 Coder 32B Instruct or Qwen3 30B A3B Instruct 2507: which to pick
Neither model has a coding score yet, so the two cannot be ranked on coding.
Pick Qwen2.5 Coder 32B Instruct for work measured by LiveCodeBench (Artificial Analysis run) or LMArena Text: coding, where it leads.
- Shared results
- 27
- Qwen2.5 Coder 32B Instruct only
- 8
- Qwen3 30B A3B Instruct 2507 only
- 18
- Like-for-like categories
- 6 of 9
Only benchmarks that tested both models count toward a pick; a result only one model has is shown but not compared.
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
Qwen3 30B A3B Instruct 2507
Qwen3 30B A3B Instruct 2507 leads, 7.5 against 6.7.
Same board, both measured
Long documents
Listed context window
Qwen3 30B A3B Instruct 2507
Qwen3 30B A3B Instruct 2507 takes 262K tokens against 33K.
Listed by OpenRouter
Everyday cost
1K input + 500 output tokens
Qwen3 30B A3B Instruct 2507
Qwen2.5 Coder 32B Instruct $0.0012, Qwen3 30B A3B Instruct 2507 $0.0002 per turn.
List prices
At a glance
- Coding index
- Qwen2.5 Coder 32B Instruct not benchmarked, Qwen3 30B A3B Instruct 2507 not benchmarked.
- Widest category
- Coding, 30.2 points apart on average over 3 shared benchmarks.
- Widest single gap
- LiveCodeBench (Artificial Analysis run): Qwen2.5 Coder 32B Instruct 29.5% against Qwen3 30B A3B Instruct 2507 70.7%, 41.2 points apart on a 0 to 100 scale.
- Output price
- Qwen2.5 Coder 32B Instruct $1.00 against Qwen3 30B A3B Instruct 2507 $0.30 per million output tokens, 3.3x apart.
- Context window
- Qwen2.5 Coder 32B Instruct takes 33K tokens, Qwen3 30B A3B Instruct 2507 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 | Qwen2.5 Coder 32B Instruct | Bars | Qwen3 30B A3B Instruct 2507 | Ties |
|---|---|---|---|---|
| Coding | 0 | 3 | ||
| Intelligence | 0 | 1 | ||
| Reasoning | 0 | 5 | ||
| Math | 0 | 2 | ||
| Knowledge | 0 | 5 | ||
| General | 0 | 11 | ||
| All shared boards | 0 | 27 |
CodingLike-for-likeSix of these boards feed the Vibe Coding Index03
| Benchmark | Qwen2.5 Coder 32B Instruct | Qwen3 30B A3B Instruct 2507 | 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 |
| LiveCodeBench (Artificial Analysis run) | 29.5% | 70.7% | Qwen3 30B A3B Instruct 2507 |
| SciCode | Not measured | 33.0% | Only Qwen3 30B A3B Instruct 2507 measured |
| Terminal-Bench Hard (Artificial Analysis run) | Not measured | 6.1% | Only Qwen3 30B A3B Instruct 2507 measured |
| LMArena Text: coding | 1276 | 1416 | Qwen3 30B A3B Instruct 2507 |
| LMArena Text: software and IT | 1261 | 1417 | Qwen3 30B A3B Instruct 2507 |
| Neither model has a result on the other 32 boards here | |||
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index01
| Benchmark | Qwen2.5 Coder 32B Instruct | Qwen3 30B A3B Instruct 2507 | Leader |
|---|---|---|---|
| AA Intelligence Index | 6.7 | 7.5 | Qwen3 30B A3B Instruct 2507 |
| Epoch Capabilities Index | 119.5 | Not measured | Only Qwen2.5 Coder 32B Instruct measured |
Agentic workDirectional onlyPublic boards, shown as published, kept out of the index2 boards, none shared
| Benchmark | Qwen2.5 Coder 32B Instruct | Qwen3 30B A3B Instruct 2507 | Leader |
|---|---|---|---|
| τ²-Bench Telecom | Not measured | 28.1% | Only Qwen3 30B A3B Instruct 2507 measured |
| Berkeley Function Calling Leaderboard (BFCL) | Not measured | 41.4% | Only Qwen3 30B A3B Instruct 2507 measured |
| Neither model has a result on the other 39 boards here | |||
ReasoningLike-for-likePublic boards, shown as published, kept out of the index05
| Benchmark | Qwen2.5 Coder 32B Instruct | Qwen3 30B A3B Instruct 2507 | Leader |
|---|---|---|---|
| GPQA Diamond (Artificial Analysis run) | 41.7% | 70.7% | Qwen3 30B A3B Instruct 2507 |
| Humanity's Last Exam (Artificial Analysis run) | 3.5% | 10.3% | Qwen3 30B A3B Instruct 2507 |
| GPQA Diamond (Epoch AI run) | Not measured | 55.6% | Only Qwen3 30B A3B Instruct 2507 measured |
| LMArena Text: hard prompts | 1251 | 1398 | Qwen3 30B A3B Instruct 2507 |
| LMArena Text: expert | 1221 | 1397 | Qwen3 30B A3B Instruct 2507 |
| LMArena Text: hard prompts in English | 1269 | 1406 | Qwen3 30B A3B Instruct 2507 |
| Neither model has a result on the other 16 boards here | |||
MathLike-for-likePublic boards, shown as published, kept out of the index02
| Benchmark | Qwen2.5 Coder 32B Instruct | Qwen3 30B A3B Instruct 2507 | Leader |
|---|---|---|---|
| AA Math Index | Not measured | 66.3 | Only Qwen3 30B A3B Instruct 2507 measured |
| AIME 2025 (Artificial Analysis run) | Not measured | 66.3% | Only Qwen3 30B A3B Instruct 2507 measured |
| OTIS Mock AIME | Not measured | 62.2% | Only Qwen3 30B A3B Instruct 2507 measured |
| GSM8K | 93.0% | Not measured | Only Qwen2.5 Coder 32B Instruct measured |
| LMArena Text: math | 1251 | 1394 | Qwen3 30B A3B Instruct 2507 |
| LMArena Text: mathematical work | 1243 | 1411 | Qwen3 30B A3B Instruct 2507 |
| Neither model has a result on the other 7 boards here | |||
KnowledgeLike-for-likePublic boards, shown as published, kept out of the index05
| Benchmark | Qwen2.5 Coder 32B Instruct | Qwen3 30B A3B Instruct 2507 | Leader |
|---|---|---|---|
| MMLU Pro (Artificial Analysis run) | 63.5% | 80.5% | Qwen3 30B A3B Instruct 2507 |
| 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 | 1393 | Qwen3 30B A3B Instruct 2507 |
| LMArena Text: medicine and healthcare | 1187 | 1392 | Qwen3 30B A3B Instruct 2507 |
| LMArena Text: legal and government | 1257 | 1387 | Qwen3 30B A3B Instruct 2507 |
| LMArena Text: business and finance | 1224 | 1389 | Qwen3 30B A3B Instruct 2507 |
| Neither model has a result on the other 11 boards here | |||
Web designNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
| Benchmark | Qwen2.5 Coder 32B Instruct | Qwen3 30B A3B Instruct 2507 | Leader |
|---|---|---|---|
| Neither model has a result on 9 boards here | |||
GeneralLike-for-likePublic boards, shown as published, kept out of the index011
| Benchmark | Qwen2.5 Coder 32B Instruct | Qwen3 30B A3B Instruct 2507 | Leader |
|---|---|---|---|
| IFBench | Not measured | 50.7% | Only Qwen3 30B A3B Instruct 2507 measured |
| Long context reasoning (AA-LCR) | Not measured | 61.3% | Only Qwen3 30B A3B Instruct 2507 measured |
| DTBench | Not measured | 67.2% | Only Qwen3 30B A3B Instruct 2507 measured |
| LMCA | Not measured | 22.4% | Only Qwen3 30B A3B Instruct 2507 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 | 1384 | Qwen3 30B A3B Instruct 2507 |
| LMArena Text: instruction following | 1223 | 1363 | Qwen3 30B A3B Instruct 2507 |
| LMArena Text: creative writing | 1174 | 1317 | Qwen3 30B A3B Instruct 2507 |
| LMArena Text: English | 1248 | 1391 | Qwen3 30B A3B Instruct 2507 |
| LMArena Text: non-English | 1205 | 1372 | Qwen3 30B A3B Instruct 2507 |
| LMArena Text: Chinese | 1222 | 1432 | Qwen3 30B A3B Instruct 2507 |
| LMArena Text: German | Not measured | 1379 | Only Qwen3 30B A3B Instruct 2507 measured |
| LMArena Text: Japanese | Not measured | 1337 | Only Qwen3 30B A3B Instruct 2507 measured |
| LMArena Text: Korean | Not measured | 1330 | Only Qwen3 30B A3B Instruct 2507 measured |
| LMArena Text: French | Not measured | 1419 | Only Qwen3 30B A3B Instruct 2507 measured |
| LMArena Text: Spanish | Not measured | 1404 | Only Qwen3 30B A3B Instruct 2507 measured |
| LMArena Text: Russian | 1228 | 1369 | Qwen3 30B A3B Instruct 2507 |
| LMArena Text: Polish | Not measured | 1353 | Only Qwen3 30B A3B Instruct 2507 measured |
| LMArena Text: multi-turn | 1222 | 1378 | Qwen3 30B A3B Instruct 2507 |
| LMArena Text: longer queries | 1251 | 1378 | Qwen3 30B A3B Instruct 2507 |
| LMArena Text: writing and language | 1191 | 1336 | Qwen3 30B A3B Instruct 2507 |
| LMArena Text: entertainment and media | 1150 | 1334 | Qwen3 30B A3B Instruct 2507 |
| Neither model has a result on the other 23 boards here | |||
Image generationNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
| Benchmark | Qwen2.5 Coder 32B Instruct | Qwen3 30B A3B Instruct 2507 | 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 30B A3B Instruct 2507 costs less
Repository review
50K input + 3K output tokens
Qwen3 30B A3B Instruct 2507 costs less
Agent loop
200K input + 10K output tokens
Qwen3 30B A3B Instruct 2507 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 30B A3B Instruct 2507 |
|---|---|---|
| Maker | Qwen | Qwen |
| Weights | Open weights | Open weights |
| Released | November 11, 2024 | July 29, 2025 |
| Context window | 33K | 262K |
| Input $/Mtok | $0.66 | $0.09 |
| Output $/Mtok | $1.00 | $0.30 |
| 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 Qwen2.5 Coder 32B Instruct better than Qwen3 30B A3B Instruct 2507 for coding?
Neither model has a coding score yet, so the two cannot be ranked on coding. Pick Qwen2.5 Coder 32B Instruct for work measured by LiveCodeBench (Artificial Analysis run) or LMArena Text: coding, where it leads.
Which is cheaper, Qwen2.5 Coder 32B Instruct or Qwen3 30B A3B Instruct 2507?
Qwen2.5 Coder 32B Instruct costs $0.66 per million input tokens and $1.00 per million output tokens; Qwen3 30B A3B Instruct 2507 costs $0.09 and $0.30. Cost per solved task is known for neither of them.
Which has the bigger context window, Qwen2.5 Coder 32B Instruct or Qwen3 30B A3B Instruct 2507?
Qwen3 30B A3B Instruct 2507, with 262K tokens against 33K.
How many benchmarks is the Qwen2.5 Coder 32B Instruct vs Qwen3 30B A3B Instruct 2507 comparison based on?
27 benchmarks have a result for both models as of October 22, 2026. Qwen2.5 Coder 32B Instruct's coding index rests on 0 independent benchmarks and Qwen3 30B A3B Instruct 2507's on 0. Where only one model has a result, the page says so instead of naming a winner.