Qwen3 VL 235B A22B Instruct Pricing
FastQwen · 262K tokens context
Qwen3 VL 235B A22B Instruct from Qwen costs $0.200 per 1 million input tokens and $0.880 per 1 million output tokens as of June 2026 (live OpenRouter data). The model supports a 262,144-token context window (approximately 196,608 words) with a 16K-token maximum output. A typical 1,000-token request costs $0.0002 in input charges; a 10,000-token request costs $0.0020.
| Input price | $0.200 / 1M tokens |
|---|---|
| Output price | $0.880 / 1M tokens |
| Output / input ratio | 4.4× |
| Context window | 262,144 tokens (~196,608 words) |
| Maximum output | 16,384 tokens |
| Cost per 1K tokens (input) | $0.0002 |
| Tier | Fast |
| Last verified |
Qwen3-VL-235B-A22B Instruct is an open-weight multimodal model that unifies strong text generation with visual understanding across images and video. The Instruct model targets general vision-language use (VQA, document parsing, chart/table...
Input Price
$0.200
per 1 million tokens
Output Price
$0.880
per 1 million tokens
Context Window
262K tokens
max 16K output
Cost Examples
| Request Type | Tokens | Input Cost | Output Cost |
|---|---|---|---|
| 1,000 word article | 1,333 | $0.000267 | $0.000352 |
| 10-page document (2,500 words) | 3,333 | $0.000667 | $0.00088 |
| 1,000 lines of code | 5,000 | $0.001 | $0.00132 |
| 100K token document | 100,000 | $0.02 | $0.0264 |
Output cost estimated at 30% of input token count. Use the calculator for exact figures.
Strengths
- ✓Extremely cheap at $0.200/1M input tokens
- ✓Large 262K-token context window
- ✓Low latency for high-throughput workloads
- ✓Multimodal: understands images as well as text
Limitations
- –Less capable than flagship models on complex reasoning
- –Quality and availability can vary by hosting provider
Best Use Cases
Calculate Qwen3 VL 235B A22B Instruct Costs
Use the TokenRate calculator to convert any budget, token count, or text into exact Qwen3 VL 235B A22B Instruct costs — and compare across all models.
Open Calculator →Qwen3 VL 235B A22B Instruct — FAQ
Related Models
Related Guides