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Qwen · Open weights

Qwen 2.5 Coder 32b

Added Jul 3, 2025Open weights

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Use in the app

The latest series of Code-Specific Qwen large language models.

Input
Text
Output
Text
Discovery tier
Open weights

Pricing

USD per 1M tokens
Input
$0.20
Output
$0.20

Reference prices as published by the model provider. API example

Specifications

Context window
32K
Max output
8.2K

Side by side

Qwen 2.5 Coder 32b compared

Specifications, prices, speed and benchmark scores next to each other. Benchmarks below show every compared model too.

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Qwen 2.5 Coder 32bQwenThis modelGemma 3 4B ITGoogleRemove
ProviderQwenGoogle
Discovery tierOpen weightsOpen weights
AddedJul 3, 2025Jan 1, 2024
Limits
Context window32K128KBest
Max output8.19K8.19K
Average output—115 tokens
Pricing, USD per 1M tokens
Input$0.20$0.20
Output$0.20$0.20
Performance
Request success (24h)—100.0%
Benchmark indexes
Intelligence Index—4.8
Coding Index—2.7
Math Index—12.7
Capabilities
PDF inputNoYes
Reasoning effort——

Public evaluations

Benchmarks

Independent evaluation results, with how each score ranks among the models in the Noumen catalog.

  • Qwen 2.5 Coder 32b
  • Gemma 3 4B IT

Intelligence Index

  • Qwen 2.5 Coder 32b—
  • Gemma 3 4B IT4.8
3.8Catalog models by score55.1

Indexes

  • Coding Index

    Composite of the coding evaluations

    • Qwen 2.5 Coder 32b: —
    • Gemma 3 4B IT: 2.7

  • Math Index

    Composite of the math evaluations

    • Qwen 2.5 Coder 32b: —
    • Gemma 3 4B IT: 12.7

Document reasoning

  • AA-LCRv1.1

    Reasoning across long documents

    • Qwen 2.5 Coder 32b: —
    • Gemma 3 4B IT: 6.7%

Reasoning and knowledge

  • Humanity’s Last Exam

    Expert-level questions across academic fields

    • Qwen 2.5 Coder 32b: —
    • Gemma 3 4B IT: 5.3%

  • GPQA Diamond

    Graduate-level science questions

    • Qwen 2.5 Coder 32b: —
    • Gemma 3 4B IT: 29.1%

  • MMLU-Pro

    Multi-subject knowledge and reasoning

    • Qwen 2.5 Coder 32b: —
    • Gemma 3 4B IT: 41.7%

  • IFBench

    Following precise output instructions

    • Qwen 2.5 Coder 32b: —
    • Gemma 3 4B IT: 28.3%

Coding

  • LiveCodeBench

    Recent competitive programming problems

    • Qwen 2.5 Coder 32b: —
    • Gemma 3 4B IT: 11.2%

Math

  • AIME 2025

    Competition mathematics, 2025 problems

    • Qwen 2.5 Coder 32b: —
    • Gemma 3 4B IT: 12.7%

  • AIME

    Competition mathematics

    • Qwen 2.5 Coder 32b: —
    • Gemma 3 4B IT: 6.3%

  • MATH-500

    Competition math problems

    • Qwen 2.5 Coder 32b: —
    • Gemma 3 4B IT: 76.6%

Legacy evaluations

  • Terminal-Bench Hard

    Earlier terminal task suite

    • Qwen 2.5 Coder 32b: —
    • Gemma 3 4B IT: 0.8%

  • τ²-Bench Telecom

    Tool use in a customer-support simulation

    • Qwen 2.5 Coder 32b: —
    • Gemma 3 4B IT: 5.0%

  • AA-LCR (unversioned)

    Long-context reasoning, earlier grading

    • Qwen 2.5 Coder 32b: —
    • Gemma 3 4B IT: 6.7%

Scores from Artificial Analysis, updated Oct 26, 2026. Artificial Analysis

Developers

Use it through the API

Noumen’s API is OpenAI-compatible: any Chat Completions client works with a base URL and a key.

Read the quickstart
curl https://www.noumen.xyz/api/v1/chat/completions \
  -H "Authorization: Bearer $NOUMEN_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{
    "model": "qwen/qwen2.5-coder-32b-instruct",
    "messages": [{ "role": "user", "content": "Explain this stack trace." }]
  }'
import os
from openai import OpenAI

client = OpenAI(base_url="https://www.noumen.xyz/api/v1", api_key=os.environ["NOUMEN_API_KEY"])
reply = client.chat.completions.create(
    model="qwen/qwen2.5-coder-32b-instruct",
    messages=[{"role": "user", "content": "Explain this stack trace."}],
)
print(reply.choices[0].message.content)

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