LLM ReferenceLLM Reference

Qwen-VL Models by Alibaba

3 models2023Up to 32K ctxFrom $0.05/1M input

About

Qwen-VL is a family of 3 AI models by Alibaba, released in 2023.

Current Variants

Use-when guidance is derived from seed capabilities, context, release, and replacement fields.

3 in view
Qwen-VLCurrent

Use when the workload needs 32K context and 7B parameters.

2023-1132K context7B parameters

Use when the workload needs 32K context, 72B parameters, and structured outputs.

2023-1132K context72B parametersstructured outputs

Use when the workload needs structured outputs.

2023-11structured outputs

Release Timeline

1 release group
2023-11
3 current
Qwen-VL
32K context7B parameters
Current
Qwen-VL-Max
structured outputs
Current
Qwen-VL-Plus
32K context72B parametersstructured outputs
Current

Specifications(3 models)

Qwen-VL model specifications comparison
ModelReleasedContextParametersStructured Outputs
Qwen-VL2023-1132K7BNo
Qwen-VL-Plus2023-1132K72BYes
Qwen-VL-Max2023-11Yes

Available From(2 providers)

Pricing

Qwen-VL model pricing by provider
ModelProviderInput / 1MOutput / 1MType
Qwen-VLReplicate API$0.05$0.25Serverless
Qwen-VL-PlusOpenRouter$0.1365$0.4095Serverless
Qwen-VL-MaxOpenRouter$0.52$2.08Serverless

Frequently Asked Questions

What is Qwen-VL used for?
Qwen-VL is used for structured outputs. The family description and listed model capabilities point to those workloads as the best fit.
How does Qwen-VL compare to Tongyi DeepResearch?
Qwen-VL by Alibaba is strongest where you need structured outputs, while Tongyi DeepResearch by Alibaba is the closest related family to check for adjacent model selection. Qwen-VL has 3 listed variants and reaches up to 32K context, while Tongyi DeepResearch reaches up to 131K context, so compare the specs and pricing tables before choosing a production model.
Which Qwen-VL model should I use?
For the lowest listed input price, start with Qwen-VL through Replicate API at $0.05/1M input tokens. For the most capable/latest local choice, evaluate Qwen-VL-Plus with 32K context and structured outputs.

Models(3)