LLM Reference

Qwen3 VL 32B Instruct

Released
2025-09-18
Last refreshed
2026-05-14
Status
Researched 28d ago
Open SourceCommercial use allowedMultimodalRAGAgentsLong contextVisionJSON / Tool use

Qwen3 VL 32B Instruct has model metadata, but missing tracked provider pricing keeps it from being a default production pick.

Use it for

  • Teams evaluating rag, agents, and long context
  • Workloads that can use a 128k context window

Do not use it for

  • Cost-sensitive launches that need sourced token pricing
  • Teams that need a tracked hosted API route today
Specifications
Family
Qwen3-VL
Released
2025-09-18
Context
128k
Parameters
32B
Architecture
Decoder Only
Specialization
general
Openness
Open source
License
Apache 2.0(OSI)Commercial use allowed
Training
pretrained
Created by

AI research institute of Alibaba Group.

Hangzhou, Zhejiang, China
Founded 2017
Website
Pricing

No tracked provider token pricing is available yet.

About

Qwen3-VL-32B-Instruct is a 32B multimodal vision-language model from Alibaba's Qwen3-VL series, delivering high-precision image understanding and reasoning at 128K context.

Qwen3 VL 32B Instruct is an open-source model in the Qwen3-VL family. The structured metadata tracks a 128k-token context window, multimodal input, function calling, tool use, and structured outputs. Headline tracked benchmarks include MMMU Pro 68.1.

Top use-case fit: coding, agents, and build tasks

RAG

Included by capability and metadata signals in the decision map.

Agents

Included by capability and metadata signals in the decision map.

Long context

Included by capability and metadata signals in the decision map.

Provider price ladder

No tracked provider token pricing is available for this model yet.

Capabilities

VisionMultimodalFunction CallingTool UseStructured Outputs

Benchmark peer barsfor RAG

No task-mapped benchmark peers are available for this model yet.

Benchmark scores(1)

Scores are benchmark-specific and are direction-aware: the same numeric gap can mean very different outcomes across suites. Use the leaderboard context and this model's provider route to decide whether the winning margin is meaningful for your workload.
BenchmarkScoreVersionSource
MMMU Pro68.1LLM-Stats aggregator, thinking mode (highest)https://llm-stats.com/benchmarks/mmmu-pro

Migration checks

No linked migration route is available for this model yet.