Model comparison
Qwen3 235B-A22B vs Solar Pro4
Qwen3 235B-A22B is the stronger model overall, scoring 43.2 to 41.5 on the Noometry Index. Solar Pro4 costs 2.3× less per token, which makes it the better buy when Qwen3 235B-A22B's lead doesn't matter for your workload.
Last verified . 17 shared benchmarks.
Summary
- They share 17 benchmarks with published results for both. Qwen3 235B-A22B scores higher in 6 categories and Solar Pro4 in 2 categories; 7 gaps are clear of the uncertainty.
- The widest gap is in math, where Qwen3 235B-A22B leads 48.5 to 36.1.
- Solar Pro4 is cheaper at $0.30 / $1.20 per million input/output tokens, against $0.70 / $2.80 for Qwen3 235B-A22B.
- Solar Pro4 accepts more context: 524K tokens versus 131K.
- Qwen3 235B-A22B has downloadable open weights; the other is API-only.
Side by side
| Qwen3 235B-A22B | Solar Pro4 | |
|---|---|---|
| Provider | Alibaba (Qwen) | Upstage |
| Noometry Index | 43.2 | 41.5 |
| Released | 2025-04 | 2026-08-06 |
| Weights | Open | Proprietary |
| Context window | 131K | 524K |
| Max output | 16K | 131K |
| Input $ / M tokens | $0.70 | $0.30 |
| Output $ / M tokens | $2.80 | $1.20 |
| Results tracked | 49 | 18 |
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Category by category
Coding Qwen3 235B-A22B leads
Qwen3 235B-A22B: 43.8 (#72), Solar Pro4: 39.9 (#135)
| Benchmark | Qwen3 235B-A22B | Solar Pro4 |
|---|---|---|
| LMArena Coding | 1445 | 1439 |
| Aider Polyglot | 59.6% | — |
| LMArena WebDev | — | 1371 |
| SciCode | 42.4% | — |
| WeirdML | 41% | — |
Agentic & Tool Use Not comparable
Qwen3 235B-A22B: 33.7 (#48), Solar Pro4: —
| Benchmark | Qwen3 235B-A22B | Solar Pro4 |
|---|---|---|
| Berkeley Function Calling Leaderboard | 52.1% | — |
| Vending-Bench 2 | -11.34 | — |
Reasoning Solar Pro4 leads
Qwen3 235B-A22B: 15.8 (#302), Solar Pro4: 27.3 (#107)
| Benchmark | Qwen3 235B-A22B | Solar Pro4 |
|---|---|---|
| LMArena Hard Prompts | 1433 | 1398 |
| ARC-AGI-2 | 1.3% | — |
| SimpleBench | 31% | — |
| Kagi LLM Benchmark | 69.4% | — |
| ARC-AGI-1 | 11% | — |
| CritPt | 0% | — |
| Chess Puzzles | 12% | — |
| Mystery Game Puzzles | 9% | — |
| DTBench | 80.3% | — |
| LMCA | 29.3% | — |
| Epoch Capabilities Index | 143.87 | — |
| ForecastBench | 59.7 | — |
Math Qwen3 235B-A22B leads
Qwen3 235B-A22B: 48.5 (#51), Solar Pro4: 36.1 (#129)
| Benchmark | Qwen3 235B-A22B | Solar Pro4 |
|---|---|---|
| LMArena Math | 1431 | 1418 |
| OTIS Mock AIME 2024-2025 | 86.7% | — |
| Omni-MATH | 71.8% | — |
| MATH Level 5 | 68.9% | — |
| FrontierMath (Feb 2025 set) | 8.5% | — |
| FrontierMath Tier 4 (v1) | 0% | — |
Knowledge Qwen3 235B-A22B leads
Qwen3 235B-A22B: 49.5 (#67), Solar Pro4: 39.0 (#128)
| Benchmark | Qwen3 235B-A22B | Solar Pro4 |
|---|---|---|
| LMArena Expert | 1460 | 1421 |
| GPQA Diamond | 80.1% | — |
| SimpleQA Verified | 40.4% | — |
| MMLU-Pro | 84.4% | — |
| Confabulations | 15.6% | — |
| Vectara Hallucination Rate | 9.3% | — |
| GPQA (HELM) | 72.7% | — |
Multilingual Qwen3 235B-A22B leads
Qwen3 235B-A22B: 52.5 (#84), Solar Pro4: 49.0 (#134)
| Benchmark | Qwen3 235B-A22B | Solar Pro4 |
|---|---|---|
| LMArena Non-English | 1410 | 1362 |
| LMArena Chinese | 1481 | 1417 |
| LMArena French | 1445 | 1403 |
| LMArena German | 1432 | 1351 |
| LMArena Japanese | 1400 | 1300 |
| LMArena Korean | 1391 | 1383 |
| LMArena Russian | 1411 | 1360 |
| LMArena Spanish | 1429 | 1408 |
Instruction Following Too close to call
Qwen3 235B-A22B: 72.8 (#132), Solar Pro4: 72.8 (#128)
| Benchmark | Qwen3 235B-A22B | Solar Pro4 |
|---|---|---|
| LMArena Instruction Following | 1408 | 1376 |
| IFEval | 83.5% | — |
Long Context Qwen3 235B-A22B leads
Qwen3 235B-A22B: 46.1 (#25), Solar Pro4: 42.0 (#125)
| Benchmark | Qwen3 235B-A22B | Solar Pro4 |
|---|---|---|
| LMArena Longer Query | 1426 | 1379 |
| Fiction.LiveBench | 75% | — |
Writing & Preference Qwen3 235B-A22B leads
Qwen3 235B-A22B: 59.8 (#103), Solar Pro4: 56.7 (#133)
| Benchmark | Qwen3 235B-A22B | Solar Pro4 |
|---|---|---|
| LMArena Text | 1419 | 1386 |
| LMArena Creative Writing | 1384 | 1313 |
| LMArena Multi-Turn | 1432 | 1391 |
| Short-Story Creative Writing | 83% | — |
| EQ-Bench Creative Writing | 1366 | — |
| WildBench | 86.6% | — |
Frequently asked questions
Is Qwen3 235B-A22B better than Solar Pro4?
Qwen3 235B-A22B is the stronger model overall, scoring 43.2 to 41.5 on the Noometry Index. Solar Pro4 costs 2.3× less per token, which makes it the better buy when Qwen3 235B-A22B's lead doesn't matter for your workload.
Which is cheaper, Qwen3 235B-A22B or Solar Pro4?
Solar Pro4 is cheaper. It lists at $0.30 per million input tokens and $1.20 per million output tokens; Qwen3 235B-A22B lists at $0.70 and $2.80.
Is Qwen3 235B-A22B or Solar Pro4 better for coding?
Qwen3 235B-A22B scores higher on coding benchmarks: 43.8 versus 39.9 in the Noometry coding category.
Which has the bigger context window?
Solar Pro4 does, with 524K tokens against 131K.
How many benchmarks do Qwen3 235B-A22B and Solar Pro4 share?
17 benchmarks have published results for both models. Qwen3 235B-A22B has 49 scored results on Noometry and Solar Pro4 has 18.