Qwen3.8 27B vs Solar Pro 4
Updated October 21, 2026. 37 benchmarks have a result for both. Coding is ranked on the Vibe Coding Index; every other board is shown as published.
Decision reading
Pick Qwen3.8 27B for coding: it scores 73.6 on the Vibe Coding Index against 24.4 for Solar Pro 4.
Pick Solar Pro 4 when output tokens cost 2.3x less, or when the benchmark that matters is SciCode, where it leads.
- Shared results
- 37
- Qwen3.8 27B only
- 48
- Solar Pro 4 only
- 8
- 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
Qwen3.8 27B
Qwen3.8 27B scores 73.6 against 24.4.
2 and 1 benchmarks behind the scores
Intelligence
AA Intelligence Index
Qwen3.8 27B
Qwen3.8 27B leads, 33.7 against 28.2.
Same board, both measured
Agentic work
AA Agentic Index
No call
Only Qwen3.8 27B has a AA Agentic Index result, 45.8.
Directional only
Reasoning
GPQA Diamond
No call
Only Qwen3.8 27B has a GPQA Diamond result, 88.9%.
Directional only
Knowledge
MMLU Pro
No call
Only Qwen3.8 27B has a MMLU Pro result, 84.3%.
Directional only
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
Qwen3.8 27B
Qwen3.8 27B takes 1M tokens against 524K.
Listed by OpenRouter
Everyday cost
1K input + 500 output tokens
Solar Pro 4
Qwen3.8 27B $0.0007, Solar Pro 4 $0.0004 per turn.
List prices
Cost per solved task
One SWE-bench Verified task, solved
No call
Only Qwen3.8 27B has the number, $1.26.
Directional only
At a glance
- Coding index
- Qwen3.8 27B 73.6 from 2 benchmarks, Solar Pro 4 24.4 from 1 benchmark.
- Widest category
- Coding, 19.5 points apart on average over 7 shared benchmarks.
- Widest single gap
- LMArena WebDev: React: Qwen3.8 27B 1602 against Solar Pro 4 1363, 39.5 points apart on a 0 to 100 scale.
- Output price
- Qwen3.8 27B $1.35 against Solar Pro 4 $0.60 per million output tokens, 2.3x apart.
- Context window
- Qwen3.8 27B takes 1M 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 | Qwen3.8 27B | Bars | Solar Pro 4 | Ties |
|---|---|---|---|---|
| Coding | 6 | 1 | ||
| Intelligence | 1 | 0 | ||
| Reasoning | 5 | 0 | ||
| Math | 2 | 0 | ||
| Knowledge | 4 | 0 | ||
| General | 18 | 0 | ||
| All shared boards | 36 | 1 |
CodingLike-for-likeFour of these boards feed the Vibe Coding Index61
| Benchmark | Qwen3.8 27B | Solar Pro 4 | Leader |
|---|---|---|---|
| LiveBench coding | 86.8% | Not measured | Only Qwen3.8 27B measured |
| LMArena WebDev | 1593 | 1371 | Qwen3.8 27B |
| AA Coding Index | 68.1 | 52.7 | Qwen3.8 27B |
| LiveCodeBench (Vals AI) | 84.0% | Not measured | Only Qwen3.8 27B measured |
| SWE-bench Verified (Vals AI) | 86.0% | Not measured | Only Qwen3.8 27B measured |
| Vibe Code Bench (Vals AI) | 64.8% | Not measured | Only Qwen3.8 27B measured |
| Code migration (Vals AI) | 14.2% | Not measured | Only Qwen3.8 27B measured |
| ProgramBench (Vals AI) | 0.0% | Not measured | Only Qwen3.8 27B measured |
| IOI (Vals AI) | 39.1% | Not measured | Only Qwen3.8 27B measured |
| Terminal-Bench 2.1 (Vals AI) | 58.4% | Not measured | Only Qwen3.8 27B measured |
| SkillsBench (Vals AI) | 38.1% | Not measured | Only Qwen3.8 27B measured |
| CyberBench (Vals AI) | 67.8% | Not measured | Only Qwen3.8 27B measured |
| SciCode | 46.6% | 48.0% | Solar Pro 4 |
| ALE-Bench | Not measured | 179.3 | Only Solar Pro 4 measured |
| LMArena Text: coding | 1483 | 1438 | Qwen3.8 27B |
| LMArena Text: software and IT | 1478 | 1431 | Qwen3.8 27B |
| LMArena WebDev: React | 1602 | 1363 | Qwen3.8 27B |
| LMArena WebDev: HTML | 1570 | 1371 | Qwen3.8 27B |
| LMArena WebDev: from an image | 1577 | Not measured | Only Qwen3.8 27B measured |
| Neither model has a result on the other 19 boards here | |||
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index10
| Benchmark | Qwen3.8 27B | Solar Pro 4 | Leader |
|---|---|---|---|
| AA Intelligence Index | 33.7 | 28.2 | Qwen3.8 27B |
| Epoch Capabilities Index | 151.7 | Not measured | Only Qwen3.8 27B measured |
Agentic workDirectional onlyPublic boards, shown as published, kept out of the index11 boards, none shared
| Benchmark | Qwen3.8 27B | Solar Pro 4 | Leader |
|---|---|---|---|
| AA Agentic Index | 45.8 | Not measured | Only Qwen3.8 27B measured |
| Design Arena: agents building web apps | Not measured | 1105 | Only Solar Pro 4 measured |
| LiveBench research | 59.4% | Not measured | Only Qwen3.8 27B measured |
| LiveBench browser | 32.0% | Not measured | Only Qwen3.8 27B measured |
| LiveBench long agentic | 27.9% | Not measured | Only Qwen3.8 27B measured |
| Finance Agent (Vals AI) | 48.5% | Not measured | Only Qwen3.8 27B measured |
| Tax Agent Bench (Vals AI) | 30.9% | Not measured | Only Qwen3.8 27B measured |
| Legal Research Bench (Vals AI) | 36.1% | Not measured | Only Qwen3.8 27B measured |
| Excel Modeling Benchmark (Vals AI) | 59.7% | Not measured | Only Qwen3.8 27B measured |
| Terminal-Bench-Science (Vals AI) | 0.0% | Not measured | Only Qwen3.8 27B measured |
| APEX-Agents | 47.5% | Not measured | Only Qwen3.8 27B measured |
| Neither model has a result on the other 28 boards here | |||
ReasoningLike-for-likePublic boards, shown as published, kept out of the index50
| Benchmark | Qwen3.8 27B | Solar Pro 4 | Leader |
|---|---|---|---|
| GPQA Diamond | 88.9% | Not measured | Only Qwen3.8 27B measured |
| LiveBench reasoning | 80.0% | Not measured | Only Qwen3.8 27B measured |
| MMMU Pro (Vals AI) | 83.9% | Not measured | Only Qwen3.8 27B measured |
| GPQA Diamond (Artificial Analysis run) | 90.5% | 89.1% | Qwen3.8 27B |
| Humanity's Last Exam (Artificial Analysis run) | 33.9% | 29.8% | Qwen3.8 27B |
| ARC-AGI | 87.5% | Not measured | Only Qwen3.8 27B measured |
| ARC-AGI-2 | 42.4% | Not measured | Only Qwen3.8 27B measured |
| LMArena Text: hard prompts | 1459 | 1400 | Qwen3.8 27B |
| LMArena Text: expert | 1479 | 1428 | Qwen3.8 27B |
| LMArena Text: hard prompts in English | 1461 | 1427 | Qwen3.8 27B |
| LMArena Vision: diagrams | 1285 | Not measured | Only Qwen3.8 27B measured |
| LMArena Vision: homework | 1295 | Not measured | Only Qwen3.8 27B measured |
| Neither model has a result on the other 9 boards here | |||
MathLike-for-likePublic boards, shown as published, kept out of the index20
| Benchmark | Qwen3.8 27B | Solar Pro 4 | Leader |
|---|---|---|---|
| ProofBench | 16.0% | Not measured | Only Qwen3.8 27B measured |
| LMArena Text: math | 1455 | 1421 | Qwen3.8 27B |
| LMArena Text: mathematical work | 1458 | 1427 | Qwen3.8 27B |
| Neither model has a result on the other 10 boards here | |||
KnowledgeLike-for-likePublic boards, shown as published, kept out of the index40
| Benchmark | Qwen3.8 27B | Solar Pro 4 | Leader |
|---|---|---|---|
| MMLU Pro | 84.3% | Not measured | Only Qwen3.8 27B measured |
| LegalBench (Vals AI) | 82.4% | Not measured | Only Qwen3.8 27B measured |
| TaxEval (Vals AI) | 70.8% | Not measured | Only Qwen3.8 27B measured |
| MortgageTax (Vals AI) | 64.9% | Not measured | Only Qwen3.8 27B measured |
| MedCode (Vals AI) | 28.7% | Not measured | Only Qwen3.8 27B measured |
| LMArena Text: science | 1467 | 1404 | Qwen3.8 27B |
| LMArena Text: medicine and healthcare | 1437 | 1374 | Qwen3.8 27B |
| LMArena Text: legal and government | 1447 | 1383 | Qwen3.8 27B |
| LMArena Text: business and finance | 1438 | 1381 | Qwen3.8 27B |
| Neither model has a result on the other 8 boards here | |||
Web designDirectional onlyPublic boards, shown as published, kept out of the index7 boards, none shared
| Benchmark | Qwen3.8 27B | 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 |
| LiveBench design | 75.9% | Not measured | Only Qwen3.8 27B measured |
| Neither model has a result on the other 2 boards here | |||
GeneralLike-for-likePublic boards, shown as published, kept out of the index180
| Benchmark | Qwen3.8 27B | Solar Pro 4 | Leader |
|---|---|---|---|
| LiveBench data analysis | 76.6% | Not measured | Only Qwen3.8 27B measured |
| SAGE (Vals AI) | 52.4% | Not measured | Only Qwen3.8 27B measured |
| MedScribe (Vals AI) | 83.8% | Not measured | Only Qwen3.8 27B measured |
| Long context reasoning (AA-LCR) | 82.0% | 70.7% | Qwen3.8 27B |
| DTBench | 88.0% | Not measured | Only Qwen3.8 27B measured |
| LMCA | 41.4% | Not measured | Only Qwen3.8 27B measured |
| Surface Evolver Bench | 45.0% | Not measured | Only Qwen3.8 27B measured |
| LMArena Text | 1440 | 1388 | Qwen3.8 27B |
| LMArena Text: instruction following | 1436 | 1375 | Qwen3.8 27B |
| LMArena Text: creative writing | 1383 | 1317 | Qwen3.8 27B |
| LMArena Vision | 1269 | Not measured | Only Qwen3.8 27B measured |
| LMArena Text: English | 1448 | 1414 | Qwen3.8 27B |
| LMArena Text: non-English | 1428 | 1363 | Qwen3.8 27B |
| LMArena Text: Chinese | 1501 | 1422 | Qwen3.8 27B |
| LMArena Text: German | 1443 | 1358 | Qwen3.8 27B |
| LMArena Text: Japanese | 1387 | 1320 | Qwen3.8 27B |
| LMArena Text: Korean | 1384 | 1383 | Qwen3.8 27B |
| LMArena Text: French | 1465 | 1400 | Qwen3.8 27B |
| LMArena Text: Spanish | 1449 | 1409 | Qwen3.8 27B |
| LMArena Text: Russian | 1415 | 1357 | Qwen3.8 27B |
| LMArena Text: Polish | 1439 | 1304 | Qwen3.8 27B |
| LMArena Text: multi-turn | 1440 | 1385 | Qwen3.8 27B |
| LMArena Text: longer queries | 1448 | 1382 | Qwen3.8 27B |
| LMArena Text: writing and language | 1405 | 1344 | Qwen3.8 27B |
| LMArena Text: entertainment and media | 1393 | 1332 | Qwen3.8 27B |
| LMArena Vision: English | 1267 | Not measured | Only Qwen3.8 27B measured |
| LMArena Vision: Chinese | 1326 | Not measured | Only Qwen3.8 27B measured |
| LMArena Vision: reading text | 1281 | Not measured | Only Qwen3.8 27B measured |
| LMArena Vision: humor | 1235 | Not measured | Only Qwen3.8 27B measured |
| LMArena Vision: creative writing | 1237 | Not measured | Only Qwen3.8 27B measured |
| Neither model has a result on the other 16 boards here | |||
Image generationNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
| Benchmark | Qwen3.8 27B | 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
Solar Pro 4 costs less
Repository review
50K input + 3K output tokens
Qwen3.8 27B costs less
Agent loop
200K input + 10K output tokens
Qwen3.8 27B 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 | Qwen3.8 27B | Upstage Solar Pro 4 |
|---|---|---|
| Maker | Qwen | Upstage |
| Weights | Open weights | No public weights listed |
| Released | August 14, 2026 | August 10, 2026 |
| Context window | 1M | 524K |
| Input $/Mtok | $0.04 | $0.15 |
| Output $/Mtok | $1.35 | $0.60 |
| Coding index | 73.6 | 24.4 |
| Independent measurements behind it | 2 | 1 |
| Cost per solved task | $1.26 | Not computable |
| Source | OpenRouter listing | OpenRouter listing |
Questions
Is Qwen3.8 27B better than Solar Pro 4 for coding?
Pick Qwen3.8 27B for coding: it scores 73.6 on the Vibe Coding Index against 24.4 for Solar Pro 4. Pick Solar Pro 4 when output tokens cost 2.3x less, or when the benchmark that matters is SciCode, where it leads.
Which is cheaper, Qwen3.8 27B or Solar Pro 4?
Qwen3.8 27B costs $0.04 per million input tokens and $1.35 per million output tokens; Solar Pro 4 costs $0.15 and $0.60. Cost per solved task is known for Qwen3.8 27B only.
Which has the bigger context window, Qwen3.8 27B or Solar Pro 4?
Qwen3.8 27B, with 1M tokens against 524K.
How many benchmarks is the Qwen3.8 27B vs Solar Pro 4 comparison based on?
37 benchmarks have a result for both models as of October 21, 2026. Qwen3.8 27B's coding index rests on 2 independent benchmarks and Solar Pro 4's on 1. Where only one model has a result, the page says so instead of naming a winner.