---
base_model: IQuestLab/IQuest-Coder-V1-40B-Instruct
base_model_relation: quantized
language:
  - en
library_name: gguf
license: other
license_name: iquestcoder
license_link: https://huggingface.co/IQuestLab/IQuest-Coder-V1-40B-Instruct/blob/main/LICENSE
pipeline_tag: text-generation
tags:
  - text-generation-inference
  - code
  - agent
  - swe-bench
  - gguf
---

# IQuest-Coder-V1-40B-Instruct-GGUF

![Logo](https://huggingface.co/IQuestLab/IQuest-Coder-V1-40B-Instruct/resolve/main/papers/iquest-coder-v1-logo.png)

## Description

This repository contains **GGUF** format model files for [IQuestLab's IQuest-Coder-V1-40B-Instruct](https://huggingface.co/IQuestLab/IQuest-Coder-V1-40B-Instruct).

**IQuest-Coder-V1** is a state-of-the-art coding model built on a "code-flow" training paradigm. It captures the dynamic evolution of software logic, delivering exceptional performance on benchmarks like SWE-Bench Verified (81.4%) and BigCodeBench. This model natively supports a **128K context window**.

## Evaluation Results

![Evaluation Results](https://cdn-uploads.huggingface.co/production/uploads/64e1a459ff3fd4fd8eedb456/kQviRhaP0v6C5Z2rhYFoa.png)

## Files & Quantization

To see the available files, please verify the **Files and versions** tab.

## How to Run (llama.cpp)

**Recommended Parameters:**
For coding tasks, a lower temperature is generally recommended for precision.
*   **Temperature:** `0.2` (for code generation) or `0.7` (for creative explanations)
*   **Context:** `-c` (Adjust based on your VRAM/RAM. The model supports up to 128k).

### CLI Example

```bash
./llama-cli -m IQuest-Coder-V1-40B-Instruct.Q4_K_M.gguf \
  -c 8192 \
  --temp 0.2 \
  -p "User: Write a Python function to calculate the Fibonacci sequence using dynamic programming.\nAssistant:" \
  -cnv
```

### Server Example

```bash
./llama-server -m IQuest-Coder-V1-40B-Instruct.Q4_K_M.gguf \
  --port 8080 \
  --host 0.0.0.0 \
  -c 16384 \
  -ngl 99
```