qwen/qwen3-235b-a22b-2507
262,144 context · $0.07/M input tokens · $0.10/M output tokens
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,...
Pay-per-use
No upfront costs, pay only for what you use
Use the following code examples to integrate with our API:
from openai import OpenAI
client = OpenAI(
api_key="YOUR_API_KEY",
base_url="https://llm.wavespeed.ai/v1"
)
response = client.chat.completions.create(
model="qwen/qwen3-235b-a22b-2507",
messages=[
{"role": "user", "content": "Hello!"}
]
)
print(response.choices[0].message.content)Qwen3-235B-A22B-Instruct-2507 is a multilingual, instruction-tuned mixture-of-experts language model based on the Qwen3-235B architecture, with 22B ac
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, logical reasoning, math, code, and tool usage. The model supports a native 262K context length and does not implement "thinking mode" (<think> blocks).
Compared to its base variant, this version delivers significant gains in knowledge coverage, long-context reasoning, coding benchmarks, and alignment with open-ended tasks. It is particularly strong on multilingual understanding, math reasoning (e.g., AIME, HMMT), and alignment evaluations like Arena-Hard and WritingBench.
| Specification | Value |
|---|---|
| Provider | Qwen |
| Model Type | Large Language Model (LLM) |
| Architecture | N/A |
| Context Window | 262144 tokens |
| Max Output | tokens |
| Input | Text |
| Output | Text |
| Vision | Supported |
| Function Calling | Supported |
| Token Type | Cost per Million Tokens |
|---|---|
| Input | $0.1 |
| Output | $0.1 |
Base URL: https://llm.wavespeed.ai/v1 API Endpoint: chat/completions Model ID: qwen/qwen3-235b-a22b-2507
from openai import OpenAI
client = OpenAI(
api_key="YOUR_API_KEY",
base_url="https://llm.wavespeed.ai/v1"
)
response = client.chat.completions.create(
model="qwen/qwen3-235b-a22b-2507",
messages=[
{"role": "user", "content": "Hello!"}
]
)
print(response.choices[0].message.content)
curl https://llm.wavespeed.ai/v1/chat/completions \
-H "Content-Type: application/json" \
-H "Authorization: Bearer YOUR_API_KEY" \
-d '{
"model": "qwen/qwen3-235b-a22b-2507",
"messages": [{"role": "user", "content": "Hello!"}]
}'
qwen/qwen3-235b-a22b-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
$0.071 /M
Output
$0.1 /M
Context
262K
Tool Use
Supported
Access Qwen3 235b A22b 2507 through our unified API — OpenAI-compatible, no cold starts, transparent pricing.
Pricing on WaveSpeedAI: $0.07 per million input tokens and $0.10 per million output tokens. Prompt caching and batch processing are billed separately and reduce effective cost on long, repetitive workloads.
Qwen3 235b A22b 2507 supports up to 262K tokens of context with up to — tokens of output per request.
Yes. WaveSpeedAI exposes Qwen3 235b A22b 2507 through an OpenAI-compatible endpoint at https://llm.wavespeed.ai/v1. Point the official OpenAI SDK at this base URL with your WaveSpeedAI API key — no other code changes required.
Sign in to WaveSpeedAI, create an API key in Access Keys, then send a request to https://llm.wavespeed.ai/v1/chat/completions with model id set to the value shown above. New accounts receive free credits to evaluate Qwen3 235b A22b 2507 before paying per token.