Qwen3 Max Thinking
qwen3-max-thinkingQwen3-Max-Thinking is the flagship reasoning model in the Qwen3 series, designed for high-stakes cognitive tasks that require deep, multi-step reasoning. By significantly scaling model capacity and reinforcement learning compute, it... Built by Qwen.
Prices updated
Input price
$0.78
per 1M tokens · Standard
Output price
$3.90
per 1M tokens · Standard
Input limit
262K
tokens
Output limit
66K
tokens
Input formats
Output formats
Qwen3 Max Thinking price history
2 price records since 9/25/2026
Qwen3 Max Thinking cost calculator
$35/month
Standard pricing
Overview
What is Qwen3 Max Thinking?
Qwen3 Max Thinking is a text & reasoning model from Qwen. Qwen3-Max-Thinking is the flagship reasoning model in the Qwen3 series, designed for high-stakes cognitive tasks that require deep, multi-step reasoning. By significantly scaling model capacity and reinforcement learning compute, it... Its 262K context window and $0.78 input price make it a candidate for quality-focused production applications.
Benchmarks
Qwen3 Max Thinking benchmarks & speed
How Qwen3 Max Thinking scores on standardized evaluations, and where it lands among every model we track.
21.3
Intelligence Index
Reasoning
GPQA Diamond
86.1%
Graduate-level scientific reasoning · top 37%
HLE
28.0%
Humanity's Last Exam · top 40%
Independent scores from Artificial Analysis and DesignArena · updated 10/5/2026. Higher is better; ranks compare against every model we track with that score.
Rates
Qwen3 Max Thinking pricing
Pricing is based on token usage. Provider-specific caching, batch, regional, and tool charges may affect the final cost.
Input · Standard
$0.78
Per 1M tokens
Cached input · Standard
Not available
No listed cached-input rate
Capabilities
Qwen3 Max Thinking Tools
Tools available when using Qwen3 Max Thinking through supported provider APIs.
Function calling
Supported
Structured outputs
Supported
JSON mode
Supported
Reasoning
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
- Measured results (AA Intelligence 21.3) position it for demanding production work.
- 262K context supports large documents, repositories and extended conversations.
- Supports text & reasoning workloads in one model.
Limitations
- Generated tokens cost 5× 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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