AMAImedia/K2-Horizon-7B-GGUF
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K2-Horizon-7B — GGUF Quantizations
GGUF quantizations of IFM/K2-Horizon-7B, a dense 7B-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).
Model Details
Note: These GGUFs carry thek2-horizonarchitecture 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 supportK2HorizonForCausalLM.
Included Files
Standard Quantizations
IQ (Importance-Matrix) Quantizations
Quantization Method
- Source: IFM's official BF16 GGUF (
K2-Horizon-7B-BF16.gguf). - imatrix: Computed from Salesforce/wikitext (
wikitext-2-raw-v1, 500 rows) with 12 GPU layers offloaded on an RTX 4060 Laptop (8 GB VRAM) due to the 18 GB model size. Applied to all K-quants below Q6 and all IQ quants. - Fork: MBZUAI-IFM/llama.cpp, branch
model/K2Horizon.
Usage
Requires the MBZUAI-IFM llama.cpp fork (model/K2Horizon branch).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
./build/bin/llama-cli \
-m K2-Horizon-7B-Q4_K_M.gguf \
-p "Hello, I am" \
-n 128 \
-ngl 35License
Weights are released under the same license as the original IFM/K2-Horizon-7B model. Please refer to the original repository for full license terms.
Credits
- Original model: MBZUAI IFM
- Quantized by: NANI-Nithin
- Quantization tool: MBZUAI-IFM/llama.cpp
