MODEL PROFILE

Qwen3-235B-A22B-Thinking-2507-FP8

阿里巴巴 · Qwen · Qwen3-235B-A22B-Thinking-2507-FP8

Over the past three months, we have continued to scale the **thinking capability** of Qwen3-235B-A22B, improving both the **quality and depth** of reasoning. We are pleased to introduce **Qwen3-235B-A22B-Thinking-2507-FP8**, featuring the following key enhancements: - **Significantly improved performance** on reasoning tasks, including logical reasoning, mathematics, science, coding, and academic benchmarks that typically require human expertise — achieving **state-of-the-art results among open-source thinking models**. - **Markedly better general capabilities**, such as instruction following, tool usage, text generation, and alignment with human preferences. - **Enhanced 256K long-context understanding** capabilities. **NOTE**: This version has an increased thinking length. We strongly recommend its use in highly complex reasoning tasks. This repo contains the FP8 version of **Qwen3-235B-A22B-Thinking-2507**, which has the following features: - Type: Causal Language Models - Training Stage: Pretraining & Post-training - Number of Parameters: 235B in total and 22B activated - Number of Paramaters (Non-Embedding): 234B - Number of Layers: 94 - Number of Attention Heads (GQA): 64 for Q and 4 for KV - Number of Experts: 128 - Number of Activated Experts: 8 - Context Length: **262,144 natively**.

Text generationlicense:apache-2.0
Context window262,144 Token
Input → OutputText → Text
Model weightsNot verified
Profile updated2026/10/30 21:44:40
OVERVIEW

Model overview

Over the past three months, we have continued to scale the **thinking capability** of Qwen3-235B-A22B, improving both the **quality and depth** of reasoning. We are pleased to introduce **Qwen3-235B-A22B-Thinking-2507-FP8**, featuring the following key enhancements: - **Significantly improved performance** on reasoning tasks, including logical reasoning, mathematics, science, coding, and academic benchmarks that typically require human expertise — achieving **state-of-the-art results among open-source thinking models**. - **Markedly better general capabilities**, such as instruction following, tool usage, text generation, and alignment with human preferences. - **Enhanced 256K long-context understanding** capabilities. **NOTE**: This version has an increased thinking length. We strongly recommend its use in highly complex reasoning tasks. This repo contains the FP8 version of **Qwen3-235B-A22B-Thinking-2507**, which has the following features: - Type: Causal Language Models - Training Stage: Pretraining & Post-training - Number of Parameters: 235B in total and 22B activated - Number of Paramaters (Non-Embedding): 234B - Number of Layers: 94 - Number of Attention Heads (GQA): 64 for Q and 4 for KV - Number of Experts: 128 - Number of Activated Experts: 8 - Context Length: **262,144 natively**.

Key features

特点摘要待依据来源补齐,不凭模型名称推断能力。

Limitations & considerations

Sources are insufficient to establish specific limitations. Verify task performance, latency, data policies, licensing and version lifecycle.

PRICING & COST

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Estimate monthly base token costs

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INDEPENDENT BENCHMARKS

Public benchmarks & run configuration

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Frequently asked questions

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Sources & traceability

许可证:apache-2.0。模型介绍与第三方评测均以原来源的具体版本和方法为准。