Qwen3 VL 235B A22B Thinking vs Qwen3 VL 32B Instruct
Qwen3 VL 235B A22B Thinking leads the LLM Stats Score 26.7 to 20.3.
Alibaba Cloud / Qwen Team · Alibaba Cloud / Qwen Team · Updated for 2026
Which is better?
Qwen3 VL 235B A22B Thinking leads the overall LLM Stats Score 26.7 to 20.3, ranking #152 overall.
In the 38 individual benchmarks reported for both models, Qwen3 VL 235B A22B Thinking wins 30; this is a narrower head-to-head signal than the composite indexes.
Based on current LLM Stats indexes, shared benchmarks, pricing, and model metadata for 2026.
Choose Qwen3 VL 235B A22B Thinking
- overall performance matters — it scores 26.7 and ranks #152 on LLM Stats
- your work emphasizes reasoning — it leads those capability indexes
- you value its reported benchmark strengths — it wins 30 of 38 exact shared results
Choose Qwen3 VL 32B Instruct
- you are already invested in the Alibaba Cloud / Qwen Team ecosystem
At a glance
The differences that matter most.
Capability indexes
Additional strengths measured across groups of related public benchmarks
1 more shared indexes
Individual benchmarks
67 reported for Qwen3 VL 235B A22B Thinking · 45 for Qwen3 VL 32B Instruct
Qwen3 VL 235B A22B Thinking outperforms in 30 benchmarks (AIME 2025, BFCL-v3, CC-OCR, CharadesSTA, CharXiv-R, Creative Writing v3, ERQA, Hallusion Bench, IFEval, Include, InfoVQAtest, LiveBench 20241125, LiveCodeBench v6, MathVision, MathVista-Mini, MMLU, MMLU-Pro, MMLU-ProX, MMLU-Redux, MM-MT-Bench, MMMU-Pro, MMStar, MuirBench, Multi-IF, OCRBench-V2 (zh), OSWorld, RealWorldQA, ScreenSpot Pro, SuperGPQA, WritingBench), while Qwen3 VL 32B Instruct is better at 8 benchmarks (AI2D, BLINK, DocVQAtest, LVBench, OCRBench, OCRBench-V2 (en), ODinW, ScreenSpot).
Qwen3 VL 235B A22B Thinking significantly outperforms across most benchmarks.
Human preference
Blind head-to-head votes and playground preference scores
Model Size
Parameter count comparison
Qwen3 VL 235B A22B Thinking has 203.0B more parameters than Qwen3 VL 32B Instruct, making it 615.2% larger.
Context Window
Maximum input and output token capacity
Only Qwen3 VL 235B A22B Thinking specifies input context (262,144 tokens). Only Qwen3 VL 235B A22B Thinking specifies output context (262,144 tokens).
Input capabilities
Documented input modalities across available providers
Both Qwen3 VL 235B A22B Thinking and Qwen3 VL 32B Instruct support multimodal inputs.
They are both capable of processing various types of data, offering versatility in application.
Qwen3 VL 235B A22B Thinking
Qwen3 VL 32B Instruct
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
1.0 years ago
Sep 22, 2025
1.0 years 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 Thinking and Qwen3 VL 32B Instruct side-by-side, then vote on the output you prefer.
FAQ
Common questions about Qwen3 VL 235B A22B Thinking vs Qwen3 VL 32B Instruct.