How to use from
llama.cppInstall from WinGet (Windows)
winget install llama.cpp
# Start a local OpenAI-compatible server with a web UI:
llama serve -hf nimishchaudhari/Magistral-Small-2509-IQ4_KS-GGUF# Run inference directly in the terminal:
llama cli -hf nimishchaudhari/Magistral-Small-2509-IQ4_KS-GGUFUse pre-built binary
# Download pre-built binary from:
# https://github.com/ggerganov/llama.cpp/releases# Start a local OpenAI-compatible server with a web UI:
./llama-server -hf nimishchaudhari/Magistral-Small-2509-IQ4_KS-GGUF# Run inference directly in the terminal:
./llama-cli -hf nimishchaudhari/Magistral-Small-2509-IQ4_KS-GGUFBuild from source code
git clone https://github.com/ggerganov/llama.cpp.git
cd llama.cpp
cmake -B build
cmake --build build -j --target llama-server llama-cli# Start a local OpenAI-compatible server with a web UI:
./build/bin/llama-server -hf nimishchaudhari/Magistral-Small-2509-IQ4_KS-GGUF# Run inference directly in the terminal:
./build/bin/llama-cli -hf nimishchaudhari/Magistral-Small-2509-IQ4_KS-GGUFUse Docker
docker model run hf.co/nimishchaudhari/Magistral-Small-2509-IQ4_KS-GGUFQuick Links
Magistral-Small-2509-IQ4_KS GGUF
A high-quality quantized version of mistralai/Magistral-Small-2509 using ik_llama.cpp with importance matrix optimization and custom tensor-specific quantization.
Model Details
- Base Model: mistralai/Magistral-Small-2509
- Quantization Method: Custom IQ4_KS recipe with importance matrix
- Target VRAM: 12GB for full offload
- Quantization Tool: ik_llama.cpp with imatrix calibration
Benchmark Results
Perplexity (wiki.test.raw, ctx=512)
| Metric | Value |
|---|---|
| Final PPL | 5.6245 ± 0.03312 |
| Evaluation Chunks | 594 |
| Evaluation Tokens | 304,128 |
| Context Size | 512 |
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Hardware compatibility
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Model tree for nimishchaudhari/Magistral-Small-2509-IQ4_KS-GGUF
Base model
mistralai/Mistral-Small-3.1-24B-Base-2503 Finetuned
mistralai/Magistral-Small-2509Evaluation results
- perplexity on wiki.test.rawself-reported5.625
Install (macOS, Linux)
# Start a local OpenAI-compatible server with a web UI: llama serve -hf nimishchaudhari/Magistral-Small-2509-IQ4_KS-GGUF# Run inference directly in the terminal: llama cli -hf nimishchaudhari/Magistral-Small-2509-IQ4_KS-GGUF