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Qwen/operational

Qwen: Qwen3 235B A22B Instruct 2507

Qwen3-235B-A22B-Instruct-2507 is a multilingual, instruction-tuned mixture-of-experts language model based on the Qwen3-235B architecture, with 22B active parameters per forward pass. It is optimized for general-purpose text generation, including instruction following,...

Input / output per 1M

$0.09/$0.55

Get an API key
function-callingopen weights

262K

Context window

tokens

16K

Max output

tokens per reply

74ms

Time to first token

p50, EU region

$0.55

Output price

per 1M tokens

Fit

Where this model earns its place

function calling

Tool use and structured output — dependable JSON for agent loops, RAG pipelines, and workflow automation.

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/qwen3-235b-a22b-2507
Provider
Qwen
Context length
262K
Max output
16K
Modality
text
Licence
Open Weight

Commercial

Input
$0.09
Output
$0.55
Cached input
—
Deployment
serverless
Availability
operational
Last updated
2026-10-26

Cost

What a month actually costs

WorkloadInput tokensOutput tokensMonthly cost
Prototype1.0M250K$0.23
Production50.0M12.0M$11.10
At scale500.0M120.0M$111.00

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/qwen3-235b-a22b-2507",
    "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/qwen3-235b-a22b-2507",
  messages: [{ role: "user", content: "Hello!" }],
});

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