Alibaba (Qwen)

Qwen 2.5

Estimated pricingMedium memory

Qwen 2.5 is Alibaba (Qwen)'s medium-memory model. This page shows current pricing, an interactive cost calculator, and a side-by-side with similar models.

Input

$0.50/1M tokens

Output

$1.50/1M tokens

Cached

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Batch

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Interactive

Calculate your Qwen 2.5 bill.

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What would Qwen 2.5 cost you?

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1,00010,00050,000250,0001M10M

Technical specifications

Qwen 2.5 at a glance.

Memory

131,072

tokens

Max reply

8,192

tokens

Memory tier

Medium

a long report or a codebase file

Tokenizer

qwen

Released

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Training cutoff

—

Availability

Estimated

Status

active

What it can do

Capabilities & limits.

  • Understands images
  • Deep step-by-step thinking
  • Uses tools / calls functions
  • Strict JSON output
  • Streams replies
  • Fine-tunable on your data

When to pick Qwen 2.5

  • High-volume workloads where unit cost matters.
  • Code generation, review, or refactoring.

When to look elsewhere

  • Your workload involves images — pick a vision-capable model instead.
  • You need tool-use / function calling for agent workflows.

Alternatives

Similar models to compare.

FAQ

Qwen 2.5 — the questions we see most.

Pricing, capabilities, alternatives — generated from the same data that powers the calculator above.

Get instant answers from our AI agent

At a typical workload of 50,000 conversations a month with 1,500-token prompts and 800-token replies, Qwen 2.5 costs roughly $98 per month. Input is $0.50 /1M tokens and output is $1.50 /1M tokens.
Qwen 2.5 has a 131,072-token context window (medium memory — a long report or a codebase file). That means you can fit about 24,576 words of input and history in a single call.
Models in a similar class include DeepSeek V3.2, DeepSeek V3, GPT-5. The "Similar models" section below this FAQ links into each.
Open-weight model — price from a common hosting provider (Together, Fireworks, Replicate). We source estimates from the cheapest public hosting provider for that model and note it on the page.

Still unsure?

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