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Qwen: Qwen2.5 VL 72B Instruct

qwen/qwen2.5-vl-72b-instruct
Context window
128,000 tokens
Maximum output
115,200 tokens
Input price
$0.8 per 1M tokens
Output price
$1 per 1M tokens
Modalities
text, image

Last verified · Source ↗

Official description

Qwen2.5-VL is proficient in recognizing common objects such as flowers, birds, fish, and insects. It is also highly capable of analyzing texts, charts, icons, graphics, and layouts within images.

Read the official model reference ↗.

Where this model fits

qwen/qwen2.5-vl-72b-instruct is part of the OpenRouter API catalog. Its documented modalities are text, image. Choose it against the request format, output requirements and operational limits of your application.

The source metadata identifies support for router hosting. Confirm endpoint-specific parameters in the official reference before integrating that capability.

For a repeatable evaluation, use representative requests, inspect structured output or tool calls, and log latency and usage in your own account. Catalog metadata establishes compatibility; it does not measure answer quality on your workload. Start from the provider guide for authentication and endpoint setup.

Current pricing

Verified model prices
ModelPrice typeUSDUnitTierRegionSource
Qwen: Qwen2.5 VL 72B InstructCached Input$0.4per 1M tokensStandardSee sourceOfficial source ↗
Qwen: Qwen2.5 VL 72B InstructInput$0.8per 1M tokensStandardSee sourceOfficial source ↗
Qwen: Qwen2.5 VL 72B InstructOutput$1per 1M tokensStandardSee sourceOfficial source ↗

Last verified · Source ↗

Estimate request, daily and monthly usage in the API cost calculator.

Rate limits and availability

Published limits have not yet been verified for this selection. Check the official limits documentation and your account console.

Last verified · Source ↗

Account-specific capacity may differ. Check the provider rate-limit guide and the free-tier conditions.

Three alternatives to compare

These alternatives share a documented modality and have the closest combination of input price and context size in the current catalog. This is a specification comparison, not a quality benchmark.

Computed model alternatives
ModelProviderInput / 1M tokensContext
Qwen/Qwen3.8-27BGroq$0.8131,042
AionLabs: Aion-2.0OpenRouter$0.8131,072
Sao10K: Llama 3.1 Euryale 70B v2.2OpenRouter$0.85131,072

Use the exact identifier in Python

This identifier fragment belongs in the authenticated request described in the provider Python tutorial. The tutorial covers the correct SDK, endpoint, environment variable and response shape.

model = "qwen\/qwen2.5-vl-72b-instruct"
# Pass model to the provider-specific request in the tutorial.

Recent changes

  1. OpenRouter · Qwen: Qwen2.5 VL 72B Instruct — Amount UsdNot previously recorded → Price category: cached_input · USD: 0.4 · Unit: per 1M tokensSource ↗
  2. OpenRouter · Qwen: Qwen2.5 VL 72B Instruct — Amount UsdNot previously recorded → Price category: output · USD: 1 · Unit: per 1M tokensSource ↗
  3. OpenRouter · Qwen: Qwen2.5 VL 72B Instruct — Amount UsdNot previously recorded → Price category: input · USD: 0.8 · Unit: per 1M tokensSource ↗
  4. OpenRouter · Qwen: Qwen2.5 VL 72B Instruct — First SeenNot previously recorded → Model: Qwen: Qwen2.5 VL 72B InstructSource ↗

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Frequently asked questions

What is the exact API model identifier?
Use qwen/qwen2.5-vl-72b-instruct exactly as shown in the provider model reference. Display names are not interchangeable with API identifiers.
How much does this model cost?
The current verified prices and billing units are listed in the pricing table above. Cache, batch, tier and region conditions remain separate rows when the provider documents them.
How much input can the model accept?
The model card shows the documented context window and maximum output when available. Your request must leave room for both input and generated output, including any provider-specific reasoning allocation.
Can I use a free tier?
Check the linked provider free-tier page for eligibility and account conditions. An account credit or temporary trial does not establish a permanent free rate.
Where do these model facts come from?
Official provider references are linked beside the data and in Sources. Changes are recorded with observation times; unresolved or undocumented fields are left unavailable.

Sources

Last verified · Source ↗