Qwen3 235B A22B vs Qwen3 VL 4B Thinking
Qwen3 235B A22B and Qwen3 VL 4B Thinking are closely matched at 15.7 and 13.0 on the LLM Stats Score. Qwen3 235B A22B is 3.3x cheaper per token.
Alibaba Cloud / Qwen Team · Alibaba Cloud / Qwen Team · Updated for 2026
Which is better?
Qwen3 235B A22B and Qwen3 VL 4B Thinking are closely matched on the overall LLM Stats Score at 15.7 and 13.0.
In the 7 individual benchmarks reported for both models, Qwen3 235B A22B wins 4; this is a narrower head-to-head signal than the composite indexes.
On price, Qwen3 235B A22B is roughly 3.3x cheaper per token on a blended 3:1 input/output basis, which adds up quickly at production volume.
Qwen3 VL 4B Thinking also accepts a larger context window (262,144 input tokens), making it the stronger choice for long documents and large codebases.
Based on current LLM Stats indexes, shared benchmarks, pricing, and model metadata for 2026.
Choose Qwen3 235B A22B
- you value its reported benchmark strengths — it wins 4 of 7 exact shared results
- cost matters — it's about 3.3x cheaper per token
Choose Qwen3 VL 4B Thinking
- you process long inputs — it offers a 262,144 token context window
- you want the most recent training data — it shipped Sep 2025
At a glance
The differences that matter most.
Capability indexes
Additional strengths measured across groups of related public benchmarks
Individual benchmarks
23 reported for Qwen3 235B A22B · 48 for Qwen3 VL 4B Thinking
Qwen3 235B A22B outperforms in 4 benchmarks (AIME 2025, Include, MMLU, MMLU-Redux), while Qwen3 VL 4B Thinking is better at 3 benchmarks (GPQA, MMLU-Pro, SuperGPQA).
Qwen3 235B A22B has a slight edge in benchmark performance.
Human preference
Blind head-to-head votes and playground preference scores
Pricing Analysis
Price comparison per million tokens
For input processing, Qwen3 235B A22B ($0.10/1M tokens) costs the same as Qwen3 VL 4B Thinking ($0.10/1M tokens).
For output processing, Qwen3 235B A22B ($0.10/1M tokens) is 10.0x cheaper than Qwen3 VL 4B Thinking ($1.00/1M tokens).
In conclusion, Qwen3 VL 4B Thinking is more expensive than Qwen3 235B A22B.*
* Using a 3:1 ratio of input to output tokens
Model Size
Parameter count comparison
Qwen3 235B A22B has 231.0B more parameters than Qwen3 VL 4B Thinking, making it 5775.0% larger.
Context Window
Maximum input and output token capacity
Qwen3 VL 4B Thinking accepts 262,144 input tokens compared to Qwen3 235B A22B's 128,000 tokens. Qwen3 VL 4B Thinking can generate longer responses up to 262,144 tokens, while Qwen3 235B A22B is limited to 128,000 tokens.
Input capabilities
Documented input modalities across available providers
Qwen3 VL 4B Thinking supports multimodal inputs, whereas Qwen3 235B A22B does not.
Qwen3 VL 4B Thinking can handle both text and other forms of data like images, making it suitable for multimodal applications.
Qwen3 235B A22B
Qwen3 VL 4B 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
Qwen3 235B A22B was released on 2025-04-29, while Qwen3 VL 4B Thinking was released on 2025-09-22.
Qwen3 VL 4B Thinking is 5 months newer than Qwen3 235B A22B.
Apr 29, 2025
1.4 years ago
Sep 22, 2025
11 months ago
4mo newerKnowledge Cutoff
When training data ends
Neither model specifies a knowledge cutoff date.
Unable to compare the recency of their training data.
Provider Availability
Qwen3 235B A22B is available from Fireworks, DeepInfra, Novita, Together. Qwen3 VL 4B Thinking is available from DeepInfra.
Qwen3 235B A22B
Qwen3 VL 4B Thinking
Outputs Comparison
Judge for yourself.
Run your own prompts against Qwen3 235B A22B and Qwen3 VL 4B Thinking side-by-side, then vote on the output you prefer.
FAQ
Common questions about Qwen3 235B A22B vs Qwen3 VL 4B Thinking.