 Qwen3 VL 235B A22B Instruct | ||
|---|---|---|
Model Provider The organization behind this AI's development | Qwen | |
Input Context Window Maximum input tokens this model can process at once | 131.1K tokens | 262.1K tokens |
Output Token Limit Maximum output tokens this model can generate at once | 131.1K tokens | 32.8K tokens |
Release Date When this model first became publicly available | October 13, 2025 29 days ago October 13th, 2025 | September 23, 2025 1 month ago September 23rd, 2025 |
Ling-1T | Qwen3 VL 235B A22B Instruct | |
|---|---|---|
Input Types Supported input formats | 📝Text | 📝Text🖼️Image |
Output Types Supported output formats | 📝Text | 📝Text |
Tokenizer Text encoding system | Other | Qwen3 |
Key Features Advanced capabilities | ✓Function Calling✓Structured OutputReasoning ModeContent Moderation | ✓Function Calling✓Structured OutputReasoning ModeContent Moderation |
Open Source Model availability | Available on HuggingFace → | Available on HuggingFace → |
| Qwen3 VL 235B A22B Instruct | ||
|---|---|---|
Input Token Cost Cost per million input tokens | $0.57 per million tokens | $0.22 per million tokens |
Output Token Cost Cost per million outut tokens | $2.28 per million tokens | $0.88 per million tokens |
| Qwen3 VL 235B A22B Instruct | ||
|---|---|---|
MMLU Measures knowledge across 57 subjects like law, math, history, and science | Benchmark not available. | Benchmark not available. |
MMMU Measures understanding of combined text and images across various domains | Benchmark not available. | Benchmark not available. |
HellaSwag Measures common sense reasoning by having models complete sentences about everyday situations | Benchmark not available. | Benchmark not available. |
Qwen3 VL 235B A22B Instruct by Qwen understands both text and images, can use external tools and APIs, generates structured data. It can handle standard conversations with its 262.1K token context window. Very affordable at $0.22/M input and $0.88/M output tokens. Released September 23rd, 2025.Compare your models with top performers across different categories
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