Qwen3 32B vs Solar Pro 4
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 Qwen3 32B for coding: it scores 40.0 on the Vibe Coding Index against 24.4 for Solar Pro 4.
Pick Solar Pro 4 when the context window is larger, 524K against 131K tokens, or when what matters is SciCode or LMArena Text: coding, where it leads.
- Shared results
- 28
- Qwen3 32B only
- 14
- Solar Pro 4 only
- 17
- 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
Qwen3 32B
Qwen3 32B scores 40.0 against 24.4.
One benchmark behind each score
Intelligence
AA Intelligence Index
Solar Pro 4
Solar Pro 4 leads, 28.2 against 7.3.
Same board, both measured
Web design
Design Arena: websites
No call
Only Solar Pro 4 has a Design Arena: websites result, 1176.
Directional only
Long documents
Listed context window
Solar Pro 4
Solar Pro 4 takes 524K tokens against 131K.
Listed by OpenRouter
Everyday cost
1K input + 500 output tokens
Qwen3 32B
Qwen3 32B $0.0002, Solar Pro 4 $0.0004 per turn.
List prices
At a glance
- Coding index
- Qwen3 32B 40.0 from 1 benchmark, Solar Pro 4 24.4 from 1 benchmark.
- Widest category
- Intelligence, 20.9 points apart on average over 1 shared benchmark.
- Widest single gap
- Long context reasoning (AA-LCR): Qwen3 32B 0.0% against Solar Pro 4 70.7%, 70.7 points apart on a 0 to 100 scale.
- Output price
- Qwen3 32B $0.28 against Solar Pro 4 $0.60 per million output tokens, 2.1x apart.
- Context window
- Qwen3 32B takes 131K tokens, Solar Pro 4 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 32B | Bars | Solar Pro 4 | Ties |
|---|---|---|---|---|
| Coding | 0 | 3 | ||
| Intelligence | 0 | 1 | ||
| Reasoning | 0 | 5 | ||
| Math | 0 | 2 | ||
| Knowledge | 0 | 4 | ||
| General | 0 | 13 | ||
| All shared boards | 0 | 28 |
CodingLike-for-likeFour of these boards feed the Vibe Coding Index03
| Benchmark | Qwen3 32B | Solar Pro 4 | Leader |
|---|---|---|---|
| Aider polyglot | 40.0% | Not measured | Only Qwen3 32B measured |
| LMArena WebDev | Not measured | 1371 | Only Solar Pro 4 measured |
| AA Coding Index | Not measured | 52.7 | Only Solar Pro 4 measured |
| LiveCodeBench (Artificial Analysis run) | 54.6% | Not measured | Only Qwen3 32B measured |
| SciCode | 36.0% | 48.0% | Solar Pro 4 |
| Terminal-Bench Hard (Artificial Analysis run) | 3.0% | Not measured | Only Qwen3 32B measured |
| ALE-Bench | Not measured | 179.3 | Only Solar Pro 4 measured |
| LMArena Text: coding | 1357 | 1438 | Solar Pro 4 |
| LMArena Text: software and IT | 1366 | 1431 | Solar Pro 4 |
| LMArena WebDev: React | Not measured | 1363 | Only Solar Pro 4 measured |
| LMArena WebDev: HTML | Not measured | 1371 | Only Solar Pro 4 measured |
| Neither model has a result on the other 27 boards here | |||
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index01
| Benchmark | Qwen3 32B | Solar Pro 4 | Leader |
|---|---|---|---|
| AA Intelligence Index | 7.3 | 28.2 | Solar Pro 4 |
| Epoch Capabilities Index | 138.4 | Not measured | Only Qwen3 32B measured |
Agentic workDirectional onlyPublic boards, shown as published, kept out of the index2 boards, none shared
| Benchmark | Qwen3 32B | Solar Pro 4 | Leader |
|---|---|---|---|
| Design Arena: agents building web apps | Not measured | 1105 | Only Solar Pro 4 measured |
| τ²-Bench Telecom | 29.8% | Not measured | Only Qwen3 32B measured |
| Neither model has a result on the other 37 boards here | |||
ReasoningLike-for-likePublic boards, shown as published, kept out of the index05
| Benchmark | Qwen3 32B | Solar Pro 4 | Leader |
|---|---|---|---|
| GPQA Diamond (Artificial Analysis run) | 66.8% | 89.1% | Solar Pro 4 |
| Humanity's Last Exam (Artificial Analysis run) | 7.4% | 29.8% | Solar Pro 4 |
| GPQA Diamond (Epoch AI run) | 65.7% | Not measured | Only Qwen3 32B measured |
| LMArena Text: hard prompts | 1334 | 1400 | Solar Pro 4 |
| LMArena Text: expert | 1362 | 1428 | Solar Pro 4 |
| LMArena Text: hard prompts in English | 1350 | 1427 | Solar Pro 4 |
| Neither model has a result on the other 15 boards here | |||
MathLike-for-likePublic boards, shown as published, kept out of the index02
| Benchmark | Qwen3 32B | Solar Pro 4 | 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 | 1421 | Solar Pro 4 |
| LMArena Text: mathematical work | 1420 | 1427 | Solar Pro 4 |
| Neither model has a result on the other 8 boards here | |||
KnowledgeLike-for-likePublic boards, shown as published, kept out of the index04
| Benchmark | Qwen3 32B | Solar Pro 4 | Leader |
|---|---|---|---|
| MMLU Pro (Artificial Analysis run) | 79.8% | Not measured | Only Qwen3 32B measured |
| LMArena Text: science | 1372 | 1404 | Solar Pro 4 |
| LMArena Text: medicine and healthcare | 1368 | 1374 | Solar Pro 4 |
| LMArena Text: legal and government | 1324 | 1383 | Solar Pro 4 |
| LMArena Text: business and finance | 1318 | 1381 | Solar Pro 4 |
| Neither model has a result on the other 12 boards here | |||
Web designDirectional onlyPublic boards, shown as published, kept out of the index6 boards, none shared
| Benchmark | Qwen3 32B | Solar Pro 4 | Leader |
|---|---|---|---|
| Design Arena: websites | Not measured | 1176 | Only Solar Pro 4 measured |
| Design Arena: UI components | Not measured | 1150 | Only Solar Pro 4 measured |
| Design Arena: game dev | Not measured | 1170 | Only Solar Pro 4 measured |
| Design Arena: data viz | Not measured | 1177 | Only Solar Pro 4 measured |
| Design Arena: 3D | Not measured | 1178 | Only Solar Pro 4 measured |
| Design Arena: all code categories | Not measured | 1182 | Only Solar Pro 4 measured |
| Neither model has a result on the other 3 boards here | |||
GeneralLike-for-likePublic boards, shown as published, kept out of the index013
| Benchmark | Qwen3 32B | Solar Pro 4 | Leader |
|---|---|---|---|
| IFBench | 36.3% | Not measured | Only Qwen3 32B measured |
| Long context reasoning (AA-LCR) | 0.0% | 70.7% | Solar Pro 4 |
| 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 | 1388 | Solar Pro 4 |
| LMArena Text: instruction following | 1305 | 1375 | Solar Pro 4 |
| LMArena Text: creative writing | 1297 | 1317 | Solar Pro 4 |
| LMArena Text: English | 1359 | 1414 | Solar Pro 4 |
| LMArena Text: non-English | 1317 | 1363 | Solar Pro 4 |
| LMArena Text: Chinese | 1357 | 1422 | Solar Pro 4 |
| LMArena Text: German | 1341 | 1358 | Solar Pro 4 |
| LMArena Text: Japanese | Not measured | 1320 | Only Solar Pro 4 measured |
| LMArena Text: Korean | Not measured | 1383 | Only Solar Pro 4 measured |
| LMArena Text: French | Not measured | 1400 | Only Solar Pro 4 measured |
| LMArena Text: Spanish | Not measured | 1409 | Only Solar Pro 4 measured |
| LMArena Text: Russian | 1311 | 1357 | Solar Pro 4 |
| LMArena Text: Polish | Not measured | 1304 | Only Solar Pro 4 measured |
| LMArena Text: multi-turn | 1331 | 1385 | Solar Pro 4 |
| LMArena Text: longer queries | 1327 | 1382 | Solar Pro 4 |
| LMArena Text: writing and language | 1298 | 1344 | Solar Pro 4 |
| LMArena Text: entertainment and media | 1279 | 1332 | Solar Pro 4 |
| Neither model has a result on the other 24 boards here | |||
Image generationNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
| Benchmark | Qwen3 32B | Solar Pro 4 | 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 32B costs less
Repository review
50K input + 3K output tokens
Qwen3 32B costs less
Agent loop
200K input + 10K output tokens
Qwen3 32B 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 | Upstage Solar Pro 4 |
|---|---|---|
| Maker | Qwen | Upstage |
| Weights | Open weights | No public weights listed |
| Released | April 28, 2025 | August 10, 2026 |
| Context window | 131K | 524K |
| Input $/Mtok | $0.08 | $0.15 |
| Output $/Mtok | $0.28 | $0.60 |
| Coding index | 40.0 | 24.4 |
| Independent measurements behind it | 1 | 1 |
| Cost per solved task | Not computable | Not computable |
| Source | OpenRouter listing | OpenRouter listing |
Questions
Is Qwen3 32B better than Solar Pro 4 for coding?
Pick Qwen3 32B for coding: it scores 40.0 on the Vibe Coding Index against 24.4 for Solar Pro 4. Pick Solar Pro 4 when the context window is larger, 524K against 131K tokens, or when what matters is SciCode or LMArena Text: coding, where it leads.
Which is cheaper, Qwen3 32B or Solar Pro 4?
Qwen3 32B costs $0.08 per million input tokens and $0.28 per million output tokens; Solar Pro 4 costs $0.15 and $0.60. Cost per solved task is known for neither of them.
Which has the bigger context window, Qwen3 32B or Solar Pro 4?
Solar Pro 4, with 524K tokens against 131K.
How many benchmarks is the Qwen3 32B vs Solar Pro 4 comparison based on?
28 benchmarks have a result for both models as of October 21, 2026. Qwen3 32B's coding index rests on 1 independent benchmark and Solar Pro 4's on 1. Where only one model has a result, the page says so instead of naming a winner.