
qwen/qwen3-4b-fp8
API Overview
Qwen3-4B-FP8 is a lightweight model with 4 billion parameters launched by Alibaba. Its core purpose is to serve as an ultra-efficient edge inference engine, optimized specifically for edge devices such as smartphones and IoT devices, while balancing performance and low power consumption.
- Lightweight Benchmark: With only 4 billion parameters, it delivers performance on par with Qwen2.5-72B (a 72-billion-parameter model), leading in accuracy among models of similar size.
- FP8 Black Technology: Leveraging FP8 mixed-precision quantization, the model’s size is compressed to about 500 MB, boosting inference speed by three times and reducing power consumption by 60%.
- Long-Text Support: Natively supports a 128K context length, making it easy to handle tasks such as long-document summarization and code-base analysis.
- Multi-Language Coverage: Supports 119 languages (including Chinese dialects), meeting the needs of global applications.
- Out-of-the-Box Compatibility: Compatible with mainstream inference frameworks such as ONNX Runtime and TensorRT, allowing deployment to Raspberry Pi or mobile devices within just 5 minutes.
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Core Capabilities
⚡ Ultra-Fast Inference: FP8 quantization technology achieves “zero-loss” compression, delivering an inference speed of 25 tokens per second on Raspberry Pi 5 with latency below 50 ms.
📱 All-Purpose Edge Computing: The 4-billion-parameter model requires only 1.2 GB of memory to run on mobile devices, enabling real-time speech translation, offline summarization, and other scenarios—completely freeing users from cloud dependency.
🌐 Language Without Boundaries: Equipped with a built-in multilingual adaptation layer, it achieves over 92% accuracy in recognizing dialects such as Cantonese and Minnan, breaking down barriers for AI applications in minority languages.
🔧 Frictionless Ecosystem: Offers Android/iOS SDKs and lightweight Python APIs that can be called with just one line of code, perfectly compatible with cross-platform frameworks like Flutter and React Native.
Playground
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