Qwen: Qwen2.5 7B Instruct

Public pricingIntelligence 72/100Medium memory도구 활용

Qwen: Qwen2.5 7B Instruct은 코딩, 디버깅, 기술 작업에 맞춘 텍스트 모델입니다. 강력한 코딩 성능, 33K tokens의 컨텍스트, 저비용 특성을 결합해 coding, debugging, and technical writing에서 안정적인 작업을 돕습니다. 특히 품질, 속도, 비용가 중요한 경우에 잘 맞으며, 안정적인 출력, 유연한 배포, 확장성을 중시하는 팀에 실용적입니다. 안정적인 응답, 넓은 문맥 처리, 그리고 시제품부터 운영까지 이어지는 유연성이 필요할 때 유용합니다. 안정적인 응답, 넓은 문맥 처리, 그리고 시제품부터 운영까지 이어지는 유연성이 필요할 때 유용합니다.

Input

$0.04/1M

Output

$0.10/1M

Cached

$0.01/1M

Batch

$0.02/1M

Calculate your Qwen2.5 7B Instruct bill.

Set your workload — see cost at your exact volume.

What would Qwen2.5 7B Instruct cost you?

Adjust the workload to see your monthly bill.

1,00010,00050,000250,0001M10M

Technical specifications

Qwen2.5 7B Instruct at a glance.

Memory

32,768

tokens

Max reply

32,768

tokens

Memory tier

Medium

a long report or a codebase file

Tokenizer

qwen

Released

Sep 2024

Training cutoff

Jun 2024

Availability

Public pricing

Status

active

Benchmarks

Quality benchmarks

Independent evaluations from public leaderboards. Higher is better.

  • mmlu

    74.2

  • humaneval

    57.9

  • math

    49.8

  • ifeval

    75.85

  • bbh

    34.89

  • mmlu_pro

    36.52

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 Qwen2.5 7B Instruct

  • Agentic workflows that call tools or APIs.
  • High-volume workloads where unit cost matters.

When to look elsewhere

  • Your workload involves images — pick a vision-capable model instead.

Alternatives

Similar models to compare.

FAQ

Qwen2.5 7B Instruct — 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, Qwen2.5 7B Instruct costs roughly $7 per month. Input is $0.04 /1M tokens and output is $0.10 /1M tokens.
Qwen2.5 7B Instruct has a 32,768-token context window (medium memory — a long report or a codebase file). That means you can fit about 6,144 words of input and history in a single call.
Beyond text generation, Qwen2.5 7B Instruct supports calling functions / tools, strict JSON output, fine-tuning on your own data. It streams replies by default.
Qwen2.5 7B Instruct was released in September 2024, with training data cut off around June 2024.
Models in a similar class include Qwen-Turbo, Qwen3 8B, Qwen3 14B. The "Similar models" section below this FAQ links into each.

Still unsure?

Compare Qwen2.5 7B Instruct against 100+ other models.

Open the full wizard — pick a use case, set your usage, and see side-by-side monthly costs in under a minute.

Open the comparison wizard