Qwen3 235B A22B Instruct 2507
qwen3-235b-a22b-2507Qwen3-235B-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,... Built by Qwen.
Prices updated
Input price
$0.09
per 1M tokens · Standard
Output price
$0.55
per 1M tokens · Standard
Input limit
262K
tokens
Output limit
16K
tokens
Input formats
Output formats
Qwen3 235B A22B Instruct 2507 price history
4 price records since 9/25/2026 · 2 changes
Qwen3 235B A22B Instruct 2507 cost calculator
$4.55/month
Standard pricing
Overview
What is Qwen3 235B A22B Instruct 2507?
Qwen3 235B A22B Instruct 2507 is a text & reasoning model from Qwen. 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,... Its 262K context window and $0.09 input price make it a candidate for cost-sensitive, high-throughput applications.
Rates
Qwen3 235B A22B Instruct 2507 pricing
Pricing is based on token usage. Provider-specific caching, batch, regional, and tool charges may affect the final cost.
Input · Standard
$0.09
Per 1M tokens
Cached input · Standard
$0.02
Per 1M tokens
Capabilities
Qwen3 235B A22B Instruct 2507 Tools
Tools available when using Qwen3 235B A22B Instruct 2507 through supported provider APIs.
Function calling
Supported
Structured outputs
Supported
JSON mode
Supported
Reasoning
Not supported
Built-in web search
Not supported
Log probabilities
Supported
Deterministic seed
Supported
Parallel tool calls
Not supported
Prompt caching
Not supported
Strengths and limitations
Strengths
- Low input cost at $0.09 per million tokens suits high-volume workloads.
- 262K context supports large documents, repositories and extended conversations.
- Supports text & reasoning workloads in one model.
Limitations
- Generated tokens cost 6× more than input tokens, which matters for verbose responses.
- Large context capacity does not guarantee consistent retrieval across the entire prompt.
- Arena Elo and MMLU-Pro are directional; test accuracy, latency and reliability on your own workload before committing.
Arena Elo, MMLU-Pro and pricing figures are illustrative; validate current vendor terms before purchase.
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