Qwen3 VL 235B A22B Instruct vs Qwen3 VL 32B Thinking
Qwen3 VL 32B Thinking has a slight edge in benchmark performance.
Alibaba Cloud / Qwen Team · Alibaba Cloud / Qwen Team · Updated for 2026
Which is better?
Qwen3 VL 235B A22B Instruct outperforms in 18 benchmarks (AI2D, Arena-Hard v2, BLINK, CharadesSTA, Creative Writing v3, DocVQAtest, Include, LiveBench 20241125, LVBench, MMLU, MMLU-ProX, MMLU-Redux, OCRBench, OSWorld, RealWorldQA, ScreenSpot Pro, SuperGPQA, VideoMME w/o sub.), while Qwen3 VL 32B Thinking is better at 20 benchmarks (AIME 2025, BFCL-v3, CharXiv-R, ERQA, Hallusion Bench, LiveCodeBench v6, MathVision, MathVista-Mini, MMBench-V1.1, MMLU-Pro, MM-MT-Bench, MMStar, MuirBench, Multi-IF, OCRBench-V2 (en), OCRBench-V2 (zh), ScreenSpot, SimpleQA, VideoMMMU, WritingBench). Qwen3 VL 32B Thinking has a slight edge in benchmark performance.
Based on current benchmark, pricing, and model metadata for 2026.
Choose Qwen3 VL 235B A22B Instruct
- you want predictable pricing at $0.30/M input and $1.49/M output
Choose Qwen3 VL 32B Thinking
- you want the strongest raw capability — it leads on 24 of 42 shared benchmarks
At a glance
The differences that matter most.
Performance Benchmarks
Comparative analysis across standard metrics
Qwen3 VL 235B A22B Instruct outperforms in 18 benchmarks (AI2D, Arena-Hard v2, BLINK, CharadesSTA, Creative Writing v3, DocVQAtest, Include, LiveBench 20241125, LVBench, MMLU, MMLU-ProX, MMLU-Redux, OCRBench, OSWorld, RealWorldQA, ScreenSpot Pro, SuperGPQA, VideoMME w/o sub.), while Qwen3 VL 32B Thinking is better at 20 benchmarks (AIME 2025, BFCL-v3, CharXiv-R, ERQA, Hallusion Bench, LiveCodeBench v6, MathVision, MathVista-Mini, MMBench-V1.1, MMLU-Pro, MM-MT-Bench, MMStar, MuirBench, Multi-IF, OCRBench-V2 (en), OCRBench-V2 (zh), ScreenSpot, SimpleQA, VideoMMMU, WritingBench).
Qwen3 VL 32B Thinking has a slight edge in benchmark performance.
Arena Performance
Playground indexes and blind preference scores
Model Size
Parameter count comparison
Qwen3 VL 235B A22B Instruct has 203.0B more parameters than Qwen3 VL 32B Thinking, making it 615.2% larger.
Context Window
Maximum input and output token capacity
Only Qwen3 VL 235B A22B Instruct specifies input context (262,144 tokens). Only Qwen3 VL 235B A22B Instruct specifies output context (262,144 tokens).
Input Capabilities
Supported data types and modalities
Both Qwen3 VL 235B A22B Instruct and Qwen3 VL 32B Thinking support multimodal inputs.
They are both capable of processing various types of data, offering versatility in application.
Qwen3 VL 235B A22B Instruct
Qwen3 VL 32B Thinking
License
Usage and distribution terms
Both models are licensed under Apache 2.0.
Both models share the same licensing terms, providing consistent usage rights.
Apache 2.0
Open weights
Apache 2.0
Open weights
Release Timeline
When each model was launched
Both models were released on 2025-09-22.
They likely represent similar generations of model development.
Sep 22, 2025
11 months ago
Sep 22, 2025
11 months ago
Knowledge Cutoff
When training data ends
Neither model specifies a knowledge cutoff date.
Unable to compare the recency of their training data.
Outputs Comparison
Judge for yourself.
Run your own prompts against Qwen3 VL 235B A22B Instruct and Qwen3 VL 32B Thinking side-by-side, then vote on the output you prefer.
FAQ
Common questions about Qwen3 VL 235B A22B Instruct vs Qwen3 VL 32B Thinking.