The fastest way to get this model running locally is via Optional Features.
Make sure to follow the instructions below.
An automated background process downloads all required large-scale files.
An automated hardware sweep ensures the system will select the best tuning parameters.
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💾 File hash: 03bfaffb3162418a7a9517e142af98e5 (Update date: 2026-06-25)
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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 |
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