Question 1

What is the cost of Qwen3 235B A22B Thinking 2507 TEE by Chutes?

Accepted Answer

Qwen3 235B A22B Thinking 2507 TEE by Chutes costs $0.30 per 1M input tokens and $1.20 per 1M output tokens. Cached reads cost $0.03 per 1M tokens.

Question 2

What is the context window of Qwen3 235B A22B Thinking 2507 TEE by Chutes?

Accepted Answer

Qwen3 235B A22B Thinking 2507 TEE by Chutes has a context window of 262K tokens. It supports up to 262K input tokens and can generate up to 262K output tokens.

Question 3

What are the capabilities of Qwen3 235B A22B Thinking 2507 TEE by Chutes?

Accepted Answer

Qwen3 235B A22B Thinking 2507 TEE by Chutes supports advanced reasoning, tool calling/function calling, structured output, adjustable temperature. It has open weights.

Question 4

What input and output types does Qwen3 235B A22B Thinking 2507 TEE support?

Accepted Answer

Qwen3 235B A22B Thinking 2507 TEE by Chutes accepts text as input and can generate text as output.

Question 5

Does Qwen3 235B A22B Thinking 2507 TEE by Chutes support reasoning?

Accepted Answer

Yes, Qwen3 235B A22B Thinking 2507 TEE by Chutes supports advanced reasoning capabilities.

Question 6

Is Qwen3 235B A22B Thinking 2507 TEE by Chutes open source?

Accepted Answer

Yes, Qwen3 235B A22B Thinking 2507 TEE by Chutes has open weights, meaning the model weights are publicly available for download and self-hosting.

Question 7

Does Qwen3 235B A22B Thinking 2507 TEE support function calling?

Accepted Answer

Yes, Qwen3 235B A22B Thinking 2507 TEE by Chutes supports tool calling (also known as function calling), allowing it to interact with external tools and APIs during conversations.

Question 8

What is the knowledge cutoff date for Qwen3 235B A22B Thinking 2507 TEE?

Accepted Answer

Qwen3 235B A22B Thinking 2507 TEE by Chutes has a knowledge cutoff date of 2025-04. This means the model was trained on data available up until that date.

Qwen3 235B A22B Thinking 2507 TEE API

Input Modalities

Output Modalities

Standard (per 1M tokens)

Caching (per 1M tokens)