To install this model locally in the shortest time, opt for a direct curl execution.
Use the instructions provided below to complete the setup.
The download manager will automatically pull several gigabytes of data.
The configuration wizard runs silently to set up the model for peak performance.
The KVzap-mlp-Qwen3-8B model is an optimized variant of the Qwen3 architecture, designed for fast inference and low memory footprint. It leverages a multi-layer perceptron (MLP) bottleneck to compress token representations while preserving contextual richness. With approximately 8 billion parameters, the model achieves competitive performance on benchmarks such as MMLU and GSM8K. A custom quantization scheme reduces the model size to under 16 GB on standard GPUs, enabling deployment in resource‑constrained environments. The integrated KV‑cache optimization improves token generation speed by up to 30 % compared to the base Qwen3 model.
| Spec | Value |
|---|---|
| Parameters | 8 B |
| Architecture | Qwen3 + MLP bottleneck |
| Quantization | 8‑bit integer |
| GPU memory | < 16 GB |
| MMLU score | 71.3% |
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