Qwen3.8-27B-CodeForge-3xMerge

Qwen3.8-27B-CodeForge-3xMerge

Writes and explains code and works through reasoning problems, from a weighted merge of three Qwen3.8-27B fine-tunes. For developers who want one general-purpose model for coding and chat.

Made by xtools-at on Hugging Face. These notes are Mindket's, written from its model page and model card; the model's own files and license are on Hugging Face.

About

What it is: This model blends three separately fine-tuned versions of Qwen3.8-27B into one set of weights. One contributor adds coding and efficient reasoning, one adds conversational knowledge distilled from Fable data, and one adds coding and agent skills. The aim is a general-purpose model that handles code, hard problems and instructions without leaning on a single specialty.

Who it suits: Developers who want one self-hosted model for programming help and everyday questions, and people who like to compare merged models.

Industry | Who uses it | How they use it | Example
Software | Developers | Ask for code, explanations and debugging help from a local model | A function written and explained in one reply
AI research | Model tinkerers | Study how a weighted merge of three fine-tunes behaves | Compare it against each of the three contributors
Education | Coding teachers | Walk through problems step by step with a reasoning model | A worked answer to a programming exercise
Support | Internal tooling teams | Run a general-purpose chat model on their own hardware | An assistant that answers technical questions

You can skip it if you need a small model, since the weights are about 55.6 GB in BF16, or if you want the top result in one narrow specialty.

Where to use it: It is a transformers model in Safetensors format, so it runs in Python on a machine with enough memory.

• Python with the transformers library on Windows, macOS or Linux
• Quantized and GGUF copies made by other people, which the card links through a Hugging Face search
• Local coding and chat tools that load transformers models

Use case | Who | What they get back
Code writing | Developers | Working code with an explanation
Problem solving | Students and engineers | A reasoned answer without extra rambling
General chat | Anyone self-hosting | Answers in English or Chinese, the languages the record lists

How to set it up: You need Python with pip and disk space for the weights, about 55.6 GB in BF16 or about 13.9 GB at 4-bit as an estimate.

• Python with pip
• About 55.6 GB of free disk space for the BF16 weights
• Enough GPU or system memory to load a 27.8B parameter model

1. Install the Hugging Face download tool.
2. Download the model files to your computer.
3. Load the downloaded folder with the transformers library.

pip install -U huggingface_hub
hf download xtools-at/Qwen3.8-27B-CodeForge-3xMerge

How to use it: The card shows no run command of its own. Load the model through transformers like any other chat model from the Qwen3.8 family, then send it a coding question or a reasoning task.

Tool | What it does
transformers | Loads the Safetensors weights for text generation
hf download | Fetches the model files to your computer
Quantized copies | Smaller builds by other people for lighter hardware

Example: Ask it to write a function that parses a CSV file and to explain its approach. You should get code plus a step-by-step explanation, since the card says the merge targets writing code and working through problems.

For newcomers and experts: A merged model averages the weights of several fine-tuned models, so you get a mix of their strengths without training anything new. A first small try is to download the model and ask it a short coding question.

For experts, the merge coefficients are 1.00 for the Coder390 EfficientThink checkpoint, 0.85 for Fable Distill and 0.70 for Qwopus Coder Flash. The card stresses that these numbers only scale each model during the merge. They do not show how much data each saw or what each adds to a skill. All three share the Qwen3.8-27B base, so their weights sit in a compatible space, and the trade is a blend with no single clear specialty.

Start with three Qwen3.8-27B fine-tunes
Weight each one with a merge coefficient
Merge them into one set of weights
Load the merged model with transformers
Ask for code or reasoning

Good to know: The merge mixes work from three authors, and each contributor has its own model card for its training details.

• Task label: The Hugging Face record lists the task as image text to text, while the card describes coding and chat.
• Merge weights: They are coefficients in the merge, not percentages.
• Size: It has 27.8B parameters and ships as Safetensors.

Title: Merge weight of each contributor
Coder390 EfficientThink: 1.00 weight
Fable Distill: 0.85 weight
Qwopus Coder Flash: 0.70 weight

• License: Apache 2.0.
• Cost to run: none named, the source lists no API key, account or paid service, though the weights need a machine with plenty of memory.
• Data it reaches: only the prompts you give it, plus the model files you download.
• Not for: the best result in one narrow specialty, since the card describes a blend of three models.

On Hugging Face, 13 November 2026

• Task: image text to text
• Library: transformers
• Parameters: 27.8B
• Weights: about 55.6 GB in BF16; about 13.9 GB at 4-bit (estimate)
• Formats: Safetensors
• Downloads in the last 30 days: 113
• Likes: 5
• License: apache-2.0
• Languages: en, zh
• Based on: Qwen/Qwen3.8-27B
• Quantized versions: 2
• Fine-tunes: 1
• Tags: transformers, safetensors, qwen3_5, image-text-to-text, qwen3.8, qwen3_8, merge, coding, code-generation, reasoning, efficient-thinking, agentic

Links

• Model: https://huggingface.co/xtools-at/Qwen3.8-27B-CodeForge-3xMerge
• Files: https://huggingface.co/xtools-at/Qwen3.8-27B-CodeForge-3xMerge/tree/main

Get the model

Download its files with Hugging Face's command line:

pip install -U huggingface_hub
hf download xtools-at/Qwen3.8-27B-CodeForge-3xMerge

Then follow the usage in its model card. Nothing in this kit runs by itself.