Qwen/operational

Qwen2.5 Coder 32B Instruct

Qwen2.5-Coder is the latest series of Code-Specific Qwen large language models (formerly known as CodeQwen). Qwen2.5-Coder brings the following improvements upon CodeQwen1.5: - Significantly improvements in **code generation**, **code reasoning**...

Input / output per 1M

$0.66/$1.00

Get an API key

codereasoningopen weights

33K

Context window

tokens

29K

Max output

tokens per reply

60ms

Time to first token

p50, EU region

$1.00

Output price

per 1M tokens

Fit

Where this model earns its place

code

Code generation and refactoring across large repositories, including multi-file changes.

reasoning

Multi-step reasoning — planning, quantitative analysis, and problems that need deliberation rather than recall.

Data handling

Requests are processed in the EU. Prompts are not used for training, and logs follow the retention period in your contract — zero-retention is available on request.

Specifications

Model

Model ID: qwen/qwen-2.5-coder-32b-instruct
Provider: Qwen
Context length: 33K
Max output: 29K
Modality: text
Licence: Open Weight

Commercial

Input: $0.66
Output: $1.00
Cached input: —
Deployment: serverless
Availability: operational
Last updated: 2026-10-26

Cost

What a month actually costs

Workload	Input tokens	Output tokens	Monthly cost
Prototype	1.0M	250K	$0.91
Production	50.0M	12.0M	$45.00
At scale	500.0M	120.0M	$450.00

Illustrative volumes at list price, excluding cached-input discounts and any committed-use agreement. Your invoice shows the same rates, itemised per key.

Cheaper by caching

Repeated prompts — system instructions, retrieved context, few-shot examples — are billed at the cached-input rate where the model supports it. On long system prompts this is typically the largest single line-item saving.

API

Same SDK, different base URL

cURL

curl https://api.itciphtech.com/v1/chat/completions \
  -H "Authorization: Bearer $CIPHER_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{
    "model": "qwen/qwen-2.5-coder-32b-instruct",
    "messages": [{"role": "user", "content": "Hello!"}]
  }'

TypeScript

import OpenAI from "openai";

const client = new OpenAI({
  baseURL: "https://api.itciphtech.com/v1",
  apiKey: process.env.CIPHER_API_KEY,
});

const res = await client.chat.completions.create({
  model: "qwen/qwen-2.5-coder-32b-instruct",
  messages: [{ role: "user", content: "Hello!" }],
});

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