
A standalone PowerShell module provides the fastest route to local installation.
Please follow the instructions listed below to get started.
The client handles the setup, pulling gigabytes of data automatically.
To save you time, the system will automatically determine efficient resource allocation.
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💾 File hash: 45877c5fa5dcff1b74d3dd7f5e561e35 (Update date: 2026-06-29)
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The **Qwen3.5-4B-GGUF** model delivers strong performance for a range of natural language tasks while maintaining a compact footprint. Built with 4B parameters and optimized for the GGUF quantization format, it balances speed and accuracy for both research and production environments. It supports a context window of up to 8192 tokens, enabling detailed reasoning and multi‑step problem solving without sacrificing latency. Benchmarks show the model achieves competitive perplexity scores on standard benchmarks while consuming less than 5 GB of GPU memory during inference. The integrated
| Parameters | 4 B |
| Context Length | 8192 tokens |
| Quantization | GGUF |
| Memory Usage (inference) | <5 GB |