LLM Reference

Qwen2-VL-72B-Instruct

Released
2025-01-01
Last refreshed
2026-05-19
Status
Researched 44d ago
Open sourceCommercial use: permittedMultimodalVision

Qwen2-VL-72B-Instruct is worth evaluating for vision when its provider route and context window match the workload.

Use it for

  • Teams evaluating vision
  • Workloads that can use a 32k context window
  • Buyers comparing 1 tracked provider route

Do not use it for

  • Strict JSON or tool-calling flows
Specifications
Family
Qwen2-VL
Released
2025-01-01
Context
32k
Parameters
72B
Architecture
Decoder Only
Knowledge cutoff
2023-06
Specialization
multimodal
Openness
Open source
License
Apache 2.0OSI-approvedCommercial use: permitted
Training
Pretrained
Created by

AI research institute of Alibaba Group.

Hangzhou, Zhejiang, China
Founded 2017
Website
Pricing
Output / 1M
$0.900
Input / 1M
$0.900

Cheapest of 1 route · Fireworks AI

About

Qwen2-VL-72B-Instruct is Alibaba's Qwen2-VL model focused on multimodal input across text, image, and beyond. It offers a 32K-token context window.

Qwen2-VL-72B-Instruct is an open-source model in the Qwen2-VL family. The structured metadata tracks a 32k-token context window and multimodal input. This page tracks provider routes through Fireworks AI, with the cheapest tracked route listed at $0.9 input and $0.9 output per 1M tokens. Headline tracked benchmarks include Massive Multi-discipline Multimodal Understanding 64.5 and MMMU Pro 59.3.

Top use-case fit

Vision

Q/$ B

1 relevant benchmark in the decision map.

Provider price ladder

Compare API pricing across 1 providers for input and output tokens, batch, and cached reads when available.

ProviderInput / 1MOutput / 1MRoute
Fireworks AI$0.900$0.900
Serverless

Available via routers & gateways(1)

Capabilities

VisionMultimodal

Benchmark peer barsfor Vision

Benchmark scores(2)

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
Massive Multi-discipline Multimodal Understanding64.5https://mmmu-benchmark.github.io/
MMMU Pro59.3standard 4-option (original paper harness)https://arxiv.org/html/2409.02813v3

Migration checks

No linked migration route is available for this model yet.

Compare Qwen2-VL-72B-Instruct with other models

Frequently asked questions

What is the context window of Qwen2-VL-72B-Instruct?

Qwen2-VL-72B-Instruct has a context window of 32k tokens.

How much does Qwen2-VL-72B-Instruct cost?

Qwen2-VL-72B-Instruct is available at $0.9/1M input tokens through Fireworks AI.

When was Qwen2-VL-72B-Instruct released?

Qwen2-VL-72B-Instruct was released on 2025-01-01.

Which providers offer Qwen2-VL-72B-Instruct?

Qwen2-VL-72B-Instruct is available from 1 provider: Fireworks AI.

What benchmarks has Qwen2-VL-72B-Instruct been tested on?

Qwen2-VL-72B-Instruct has been evaluated on 2 benchmarks, including Massive Multi-discipline Multimodal Understanding, MMMU Pro.