Qwen3 235B A22B-2507 on W&B Inference
Price per 1M tokens
$0.10 (input)
$0.10 (output)
Parameters
22B (active)
235B (total)
Context window
262K
Release date
July 2025
Qwen3 235B A22B-2507 inference details
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 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.
Created by: Alibaba
License: apache-2.0
🤗 model card: Qwen3-235B-A22B-Instruct-2507
import openai
import weave
# Weave autopatches OpenAI to log LLM calls to W&B
weave.init("<team>/<project>")
client = openai.OpenAI(
# The custom base URL points to W&B Inference
base_url='https://api.inference.wandb.ai/v1',
# Get your API key from https://wandb.ai/authorize
# Consider setting it in the environment as OPENAI_API_KEY instead for safety
api_key="<your-apikey>",
# Team and project are required for usage tracking
project="<team>/<project>",
)
response = client.chat.completions.create(
model="Qwen/Qwen3-235B-A22B-Instruct-2507",
messages=[
{"role": "system", "content": "You are a helpful assistant."},
{"role": "user", "content": "Tell me a joke."}
],
)
print(response.choices[0].message.content)
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