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rodrigoramosrs/
veriloop-coder-e1-gguf

Name: veriloop-coder-e1-gguf
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VeriLoop Coder-E1 · GGUF

Coding-Optimized Quantized Models

Original Model ↗ · GitHub · Apache-2.0

Overview

This repository contains GGUF quantizations of VeriLoop Coder-E1, an open-source vertical coding model built on Qwen3.6-27B. The original model introduces the Self-Harness paradigm — an evidence-bound execution substrate that turns model generation into a recursive engineering loop of falsification, exploration, and repair.

Quantized by Rodrigo Ramos.

Quantization Approach

All quants were produced with llama.cpp using a code-specialized importance matrix (imatrix). Unlike generic imatrix datasets, this one was curated from software engineering corpora — repository-level code, patches, test suites, and agentic coding traces — ensuring that quantization preserves fidelity on the distributions that matter most for coding tasks.

The result is a set of GGUF files that retain the original model's strong software-engineering capabilities while being deployable via llama.cpp, llama-cpp-python, Ollama, LM Studio, and other GGUF-compatible runtimes.

Available Quants

File	Quant Type	Notes
`LoopCoder-Qwen3.6-27B-BF16.gguf`	BF16	Full-precision reference
`LoopCoder-Qwen3.6-27B-Q8_0.gguf`	Q8_0	High quality, larger file
`LoopCoder-Qwen3.6-27B-Q6_K.gguf`	Q6_K	Excellent quality / size trade-off
`LoopCoder-Qwen3.6-27B-Q5_K_M.gguf`	Q5_K_M	Strong quality, reduced size
`LoopCoder-Qwen3.6-27B-Q4_K_M.gguf`	Q4_K_M	Balanced quality / size
`LoopCoder-Qwen3.6-27B-Q3_K_M.gguf`	Q3_K_M	Smaller, good for limited RAM
`LoopCoder-Qwen3.6-27B-IQ4_XS.gguf`	IQ4_XS	Extra-small 4-bit
`LoopCoder-Qwen3.6-27B-IQ3_XS.gguf`	IQ3_XS	Extra-small 3-bit

Usage

llama.cpp

bash

./llama-cli \
  -m LoopCoder-Qwen3.6-27B-Q4_K_M.gguf \
  -p "Your coding prompt here" \
  -n 2048 \
  -t 8

llama-cpp-python

python

from llama_cpp import Llama

llm = Llama(
    model_path="LoopCoder-Qwen3.6-27B-Q4_K_M.gguf",
    n_ctx=32768,
    n_threads=8,
)

output = llm(
    "Write a Python function to merge two sorted lists.",
    max_tokens=1024,
    temperature=0.2,
)
print(output["choices"][0]["text"])

Ollama