Model comparison
Qwen Turbo vs Qwen3.5 35B-A3B
Qwen3.5 35B-A3B is the stronger model overall, scoring 42.0 to 27.1 on the Noometry Index. Qwen Turbo costs 7.9× less per token, which makes it the better buy when Qwen3.5 35B-A3B's lead doesn't matter for your workload.
Last verified . 2 shared benchmarks.
Alibaba (Qwen)Summary
- They share 2 benchmarks with published results for both. Qwen Turbo scores higher in 0 categories and Qwen3.5 35B-A3B in 2 categories; 2 gaps are clear of the uncertainty.
- The widest gap is in knowledge, where Qwen3.5 35B-A3B leads 47.8 to 22.2.
- The biggest single-benchmark swing is OTIS Mock AIME 2024-2025: 6.1% for Qwen Turbo and 70% for Qwen3.5 35B-A3B.
- Qwen Turbo is cheaper at $0.05 / $0.20 per million input/output tokens, against $0.25 / $2 for Qwen3.5 35B-A3B.
- Qwen Turbo accepts more context: 1M tokens versus 262K.
- Qwen3.5 35B-A3B has downloadable open weights; the other is API-only.
Side by side
| Qwen Turbo | Qwen3.5 35B-A3B | |
|---|---|---|
| Provider | Alibaba (Qwen) | Alibaba (Qwen) |
| Noometry Index | 27.1 | 42.0 |
| Released | 2024-11-01 | 2026-02-01 |
| Weights | Proprietary | Open |
| Context window | 1M | 262K |
| Max output | 16K | 66K |
| Input $ / M tokens | $0.05 | $0.25 |
| Output $ / M tokens | $0.20 | $2 |
| Results tracked | 3 | 28 |
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Category by category
Coding Not comparable
Qwen Turbo: —, Qwen3.5 35B-A3B: 33.8 (#251)
| Benchmark | Qwen Turbo | Qwen3.5 35B-A3B |
|---|---|---|
| LMArena WebDev | — | 1254 |
| SciCode | — | 29.3% |
| LMArena Coding | — | 1410 |
Reasoning Not comparable
Qwen Turbo: —, Qwen3.5 35B-A3B: 24.6 (#161)
| Benchmark | Qwen Turbo | Qwen3.5 35B-A3B |
|---|---|---|
| CritPt | — | 0.6% |
| Chess Puzzles | — | 10% |
| LMArena Hard Prompts | — | 1400 |
| DTBench | — | 80% |
| LMCA | — | 29.5% |
| Epoch Capabilities Index | — | 142.52 |
Math Qwen3.5 35B-A3B leads
Qwen Turbo: 15.3 (#297), Qwen3.5 35B-A3B: 39.9 (#97)
| Benchmark | Qwen Turbo | Qwen3.5 35B-A3B |
|---|---|---|
| OTIS Mock AIME 2024-2025 | 6.1% | 70% |
| MathArena Final-Answer Competitions | — | 56% |
| LMArena Math | — | 1404 |
| MATH Level 5 | 56.2% | — |
Knowledge Qwen3.5 35B-A3B leads
Qwen Turbo: 22.2 (#272), Qwen3.5 35B-A3B: 47.8 (#79)
| Benchmark | Qwen Turbo | Qwen3.5 35B-A3B |
|---|---|---|
| GPQA Diamond | 41.8% | 83.5% |
| Vectara Hallucination Rate | — | 10.5% |
| LMArena Expert | — | 1408 |
Multilingual Not comparable
Qwen Turbo: —, Qwen3.5 35B-A3B: 50.0 (#127)
| Benchmark | Qwen Turbo | Qwen3.5 35B-A3B |
|---|---|---|
| LMArena Non-English | — | 1378 |
| LMArena Chinese | — | 1457 |
| LMArena French | — | 1412 |
| LMArena German | — | 1367 |
| LMArena Japanese | — | 1325 |
| LMArena Korean | — | 1356 |
| LMArena Russian | — | 1376 |
| LMArena Spanish | — | 1392 |
Instruction Following Not comparable
Qwen Turbo: —, Qwen3.5 35B-A3B: 72.8 (#128)
| Benchmark | Qwen Turbo | Qwen3.5 35B-A3B |
|---|---|---|
| LMArena Instruction Following | — | 1379 |
Long Context Not comparable
Qwen Turbo: —, Qwen3.5 35B-A3B: 42.4 (#127)
| Benchmark | Qwen Turbo | Qwen3.5 35B-A3B |
|---|---|---|
| LMArena Longer Query | — | 1389 |
Writing & Preference Not comparable
Qwen Turbo: —, Qwen3.5 35B-A3B: 57.9 (#124)
| Benchmark | Qwen Turbo | Qwen3.5 35B-A3B |
|---|---|---|
| LMArena Text | — | 1395 |
| LMArena Creative Writing | — | 1346 |
| LMArena Multi-Turn | — | 1390 |
Frequently asked questions
Is Qwen Turbo better than Qwen3.5 35B-A3B?
Qwen3.5 35B-A3B is the stronger model overall, scoring 42.0 to 27.1 on the Noometry Index. Qwen Turbo costs 7.9× less per token, which makes it the better buy when Qwen3.5 35B-A3B's lead doesn't matter for your workload.
Which is cheaper, Qwen Turbo or Qwen3.5 35B-A3B?
Qwen Turbo is cheaper. It lists at $0.05 per million input tokens and $0.20 per million output tokens; Qwen3.5 35B-A3B lists at $0.25 and $2.
Which has the bigger context window?
Qwen Turbo does, with 1M tokens against 262K.
How many benchmarks do Qwen Turbo and Qwen3.5 35B-A3B share?
2 benchmarks have published results for both models. Qwen Turbo has 3 scored results on Noometry and Qwen3.5 35B-A3B has 28.