K2-Horizon-0.9B — GGUF Quantizations

GGUF quantizations of IFM/K2-Horizon-0.9B, a dense 0.9B-parameter causal decoder (K2HorizonForCausalLM, model_type: k2_horizon).

Quantized by NANI-Nithin using a custom pipeline built on the MBZUAI-IFM llama.cpp fork (branch model/K2Horizon), which adds native support for the k2-horizon architecture not yet merged into upstream llama.cpp.

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Model Details

Note: These GGUFs carry the k2-horizon architecture token and require the MBZUAI-IFM fork (or upstream llama.cpp once support is merged) to run. Vanilla upstream llama.cpp (as of September 2026) does not support K2HorizonForCausalLM.

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Included Files

Standard Quantizations

IQ (Importance-Matrix) Quantizations

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Quantization Method

• Source: IFM's official BF16 GGUF is downloaded directly (no safetensors conversion needed).
• imatrix: Computed from the Salesforce/wikitext (wikitext-2-raw-v1) calibration dataset (500 rows). Applied to all K-quants below Q6 and all IQ quants for guided, higher-quality compression.
• Fork: MBZUAI-IFM/llama.cpp, branch model/K2Horizon.

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Usage

Requires the MBZUAI-IFM llama.cpp fork (model/K2Horizon branch).

# Clone and build the fork
git clone -b model/K2Horizon https://github.com/MBZUAI-IFM/llama.cpp
cd llama.cpp && cmake -B build -DGGML_CUDA=ON && cmake --build build --config Release

# Run inference
./build/bin/llama-cli \
  -m K2-Horizon-0.9B-Q4_K_M.gguf \
  -p "Hello, I am" \
  -n 128

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License

Weights are released under the same license as the original IFM/K2-Horizon-0.9B model. Please refer to the original repository for full license terms.

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Credits

• Original model: MBZUAI IFM
• Quantized by: NANI-Nithin
• Quantization tool: MBZUAI-IFM/llama.cpp