Tasks and inputs
Qwen/Qwen3-VL-235B-A22B-Instruct is listed for Image-text-to-text, Text generation. It accepts image, text and produces text. Use the publisher’s input format and preprocessing for your chosen deployment.
SyncDev model directory · Profile updated Oct 13, 2026
Hugging Face repository for Image-text-to-text.
The specification score summarizes recorded features and limits. It is not a benchmark result.
Recorded modality support shows what this model can accept and produce. An undocumented modality is shown as unknown rather than assumed to be unsupported.
Accepts
Produces
Qwen/Qwen3-VL-235B-A22B-Instruct is a Hugging Face repository returned by the public Image-text-to-text task feed. Its recorded download count is 1,789,796 and it has 412 likes when the repository snapshot was collected. Popularity is useful for discovery, but it is not a performance ranking or a guarantee of suitability.
This record is categorized for Image-text-to-text. A task category describes the intended machine-learning problem; it does not prove that every version, checkpoint, quantization, or deployment method produces the same quality. Teams should read the model card and test representative inputs before choosing it.
The public repository lists transformers as its library metadata. Its recorded tags include transformers, safetensors, qwen3_vl_moe, image-text-to-text, conversational, arxiv:2505.09388, arxiv:2502.13923, arxiv:2409.12191. These source details are retained so readers can trace this directory entry back to the repository instead of relying on copied descriptions.
Use inputs that resemble deployment traffic, including difficult and out-of-domain cases. Compare output correctness, the response format, latency and memory requirements with a simple baseline under the same conditions.
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Qwen/Qwen3-VL-235B-A22B-Instruct is listed for Image-text-to-text, Text generation. It accepts image, text and produces text. Use the publisher’s input format and preprocessing for your chosen deployment.
Documented limits: 262.14K context and 8.19K maximum output. The listed route charges $0.20 input and $0.88 output per million tokens. Measure a completed task using the prompts, documents and tools your application will use. Include reasoning and retries in the result.
The weights are downloadable under the publisher’s model licence. Check runtime support and size the complete model and working context for your expected concurrency.
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