qwen/qwen3-235b-a22b-fp8

Qwen3-235B-A22B-FP8 is the FP8-quantized version of the ultra-large-scale Mixture-of-Experts (MoE) language model released by Alibaba’s Tongyi Lab, primarily positioned as a high-performance enterprise-grade foundation model that delivers “extreme inference efficiency combined with top-tier general capabilities.”

• Flagship MoE Architecture: With a total parameter count of 235 billion and only 22 billion active parameters, it achieves state-of-the-art (SOTA) performance in authoritative benchmarks such as MMLU, GSM8K, and HumanEval.
• FP8 Quantization Acceleration: Adopting FP8 precision for both storage and computation, it achieves 2–3 times higher inference throughput on hardware platforms like NVIDIA H100 and A100, significantly reducing latency and costs.
• Long Context Support: Natively supports context lengths of up to 128,000 tokens, making it ideal for long-document summarization, complex task decomposition, and multi-turn deep dialogues.
• Multi-language and Code Enhancement: Covers dozens of languages including Chinese, English, Japanese, and French, and excels in specialized tasks such as code generation and mathematical reasoning.

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Core Capabilities

⚡ High Throughput and Low Latency Inference: FP8 quantization dramatically reduces memory usage and computational overhead, enabling a single GPU to support highly concurrent enterprise-level applications.

🧠 Strong Logical Reasoning and Generalization Abilities: Maintains high accuracy and stability in scenarios such as complex instruction following, multi-hop question answering, and tool invocation.

🌍 Global Language Support: Delivers natural and fluent outputs while taking into account cultural contexts and specialized terminology, making it suitable for international business and localized scenarios.

🛡️ Secure, Controllable, and Auditable: Supports content filtering, sensitive word interception, and logging of inference processes, meeting compliance requirements in sectors such as finance and government services.