Model comparison
Pixtral Large vs Qwen3.5-Flash
Qwen3.5-Flash is the stronger model overall, scoring 42.5 to 32.2 on the Noometry Index.
Last verified . 0 shared benchmarks.
Mistral AI
Alibaba (Qwen)Summary
- The widest gap is in writing & preference, where Qwen3.5-Flash leads 57.9 to 32.9.
- Qwen3.5-Flash is cheaper at $0.10 / $0.40 per million input/output tokens, against $2 / $6 for Pixtral Large.
- Qwen3.5-Flash accepts more context: 1M tokens versus 128K.
- Pixtral Large has downloadable open weights; the other is API-only.
Side by side
| Pixtral Large | Qwen3.5-Flash | |
|---|---|---|
| Provider | Mistral AI | Alibaba (Qwen) |
| Noometry Index | 32.2 | 42.5 |
| Released | 2024-11-01 | 2026-02-23 |
| Weights | Open | Proprietary |
| Context window | 128K | 1M |
| Max output | 128K | 66K |
| Input $ / M tokens | $2 | $0.10 |
| Output $ / M tokens | $6 | $0.40 |
| Results tracked | 3 | 32 |
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Category by category
Coding Not comparable
Pixtral Large: —, Qwen3.5-Flash: 34.2 (#242)
| Benchmark | Pixtral Large | Qwen3.5-Flash |
|---|---|---|
| LMArena WebDev | — | 1244 |
| LMArena Coding | — | 1412 |
| ALE-Bench | — | 221.8 |
Agentic & Tool Use Not comparable
Pixtral Large: —, Qwen3.5-Flash: —
| Benchmark | Pixtral Large | Qwen3.5-Flash |
|---|---|---|
| Vending-Bench 2 | — | 462.69 |
Reasoning Qwen3.5-Flash leads
Pixtral Large: 21.7 (#218), Qwen3.5-Flash: 33.7 (#72)
| Benchmark | Pixtral Large | Qwen3.5-Flash |
|---|---|---|
| Chess Puzzles | — | 21% |
| EnigmaEval | 0.8% | — |
| LMArena Hard Prompts | — | 1403 |
| Mystery Game Puzzles | — | 20% |
| DTBench | — | 82.9% |
| LMCA | — | 29.1% |
| Epoch Capabilities Index | — | 143.98 |
Math Not comparable
Pixtral Large: —, Qwen3.5-Flash: 37.4 (#158)
| Benchmark | Pixtral Large | Qwen3.5-Flash |
|---|---|---|
| FrontierMath (Tiers 1-3) | — | 18.2% |
| OTIS Mock AIME 2024-2025 | — | 84.4% |
| LMArena Math | — | 1407 |
| FrontierMath (Feb 2025 set) | — | 6.2% |
| FrontierMath Tier 4 (v1) | — | 0% |
Knowledge Not comparable
Pixtral Large: —, Qwen3.5-Flash: 43.2 (#93)
| Benchmark | Pixtral Large | Qwen3.5-Flash |
|---|---|---|
| GPQA Diamond | — | 82.3% |
| SimpleQA Verified | — | 20.3% |
| Vectara Hallucination Rate | — | 10.5% |
| LMArena Expert | — | 1407 |
Multimodal Not comparable
Pixtral Large: 30.6 (#111), Qwen3.5-Flash: —
| Benchmark | Pixtral Large | Qwen3.5-Flash |
|---|---|---|
| LMArena Vision | 1089 | — |
Multilingual Not comparable
Pixtral Large: —, Qwen3.5-Flash: 50.5 (#121)
| Benchmark | Pixtral Large | Qwen3.5-Flash |
|---|---|---|
| LMArena Non-English | — | 1385 |
| LMArena Chinese | — | 1446 |
| LMArena French | — | 1412 |
| LMArena German | — | 1390 |
| LMArena Japanese | — | 1368 |
| LMArena Korean | — | 1344 |
| LMArena Russian | — | 1379 |
| LMArena Spanish | — | 1400 |
Instruction Following Not comparable
Pixtral Large: —, Qwen3.5-Flash: 72.6 (#139)
| Benchmark | Pixtral Large | Qwen3.5-Flash |
|---|---|---|
| LMArena Instruction Following | — | 1374 |
Long Context Not comparable
Pixtral Large: —, Qwen3.5-Flash: 42.4 (#124)
| Benchmark | Pixtral Large | Qwen3.5-Flash |
|---|---|---|
| LMArena Longer Query | — | 1392 |
Writing & Preference Qwen3.5-Flash leads
Pixtral Large: 32.9 (#278), Qwen3.5-Flash: 57.9 (#122)
| Benchmark | Pixtral Large | Qwen3.5-Flash |
|---|---|---|
| LMArena Text | — | 1397 |
| LMArena Creative Writing | — | 1343 |
| EQ-Bench Creative Writing | 988 | — |
| LMArena Multi-Turn | — | 1393 |
Frequently asked questions
Is Pixtral Large better than Qwen3.5-Flash?
Qwen3.5-Flash is the stronger model overall, scoring 42.5 to 32.2 on the Noometry Index.
Which is cheaper, Pixtral Large or Qwen3.5-Flash?
Qwen3.5-Flash is cheaper. It lists at $0.10 per million input tokens and $0.40 per million output tokens; Pixtral Large lists at $2 and $6.
Which has the bigger context window?
Qwen3.5-Flash does, with 1M tokens against 128K.
How many benchmarks do Pixtral Large and Qwen3.5-Flash share?
0 benchmarks have published results for both models. Pixtral Large has 3 scored results on Noometry and Qwen3.5-Flash has 32.