abenzerps / K2-Horizon-7B-GGUF

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Total runs: 7.9K
24-hour runs: 49
7-day runs: 225
30-day runs: 7.2K
Model's Last Updated: September 04 2026
text-generation

Introduction of K2-Horizon-7B-GGUF

Model Details of K2-Horizon-7B-GGUF

K2-Horizon-7B GGUF

GGUF quantizations of IFM/K2-Horizon-7B , a 7B dense decoder-only model for reasoning, coding, long-context work, and tool use. The source checkpoint supports a native context length of 524,288 tokens (512K) .

Benchmarks

K2-Horizon-7B benchmark results

Benchmark results reported by IFM for the original K2-Horizon-7B checkpoint.

GGUF files
Quantization File Size
Q4_0 K2-Horizon-7B-Q4_0.gguf 5.34 GB
Q4_K_M K2-Horizon-7B-Q4_K_M.gguf 5.59 GB
Q5_K_M K2-Horizon-7B-Q5_K_M.gguf 6.47 GB
Q6_K K2-Horizon-7B-Q6_K.gguf 7.39 GB
Q8_0 K2-Horizon-7B-Q8_0.gguf 9.57 GB

The files are text-only GGUFs; no vision projector is required. An upstream chat_template.jinja is included for clients that need an external chat template. SHA-256 checksums are provided in SHA256SUMS.txt .

Usage

Use a current llama.cpp build. The example below uses a practical 128K context; -c 524288 can be used when the available memory is sufficient.

llama-cli \
  -m K2-Horizon-7B-Q4_K_M.gguf \
  -c 131072 -cnv \
  --temp 1.0 --top-p 0.95
Source

Runs of abenzerps K2-Horizon-7B-GGUF on huggingface.co

7.9K
Total runs
49
24-hour runs
114
3-day runs
225
7-day runs
7.2K
30-day runs

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