What are the hardware requirements for MIXdevAI Qwen?

MIXdevAI Qwen requires approximately 8 GB of VRAM and supports a context window of 256K tokens. Quantized variants may run on less VRAM; see the Quantized Models section on this page.

Who developed MIXdevAI Qwen and how large is it?

MIXdevAI Qwen is developed by Kolyadual, a model with 4b parameters. The model is published as open weights on Hugging Face and indexed on LLM Explorer with full benchmark history.

Where can I download or evaluate MIXdevAI Qwen?

MIXdevAI Qwen is hosted on Hugging Face and linked from this page. LLM Explorer also lists quantized variants and similar alternatives if available.

MIXdevAI Qwen by Kolyadual — VRAM 8GB, 256K context

Name: MIXdevAI Qwen
Author: Kolyadual

MIXdevAI Qwen is an open-source language model by Kolyadual. Features: 4b LLM, VRAM: 8GB, Context: 256K, Merged, LLM Explorer Score: 0.22.

Merged Model Conversational Endpoints compatible Newtonbotfamilytree Qwen3 Region:us Safetensors Sharded Tensorflow

Model Card on HF 🤗: https://huggingface.co/Kolyadual/MIXdevAI-qwen

MIXdevAI Qwen Parameters and Internals

LLM Name	MIXdevAI Qwen
Repository 🤗	https://huggingface.co/Kolyadual/MIXdevAI-qwen
Merged Model	Yes
Model Size	4b
Required VRAM	8 GB
Updated	2026-08-02
Maintainer	Kolyadual
Model Type	qwen3
Model Files	5.0 GB: 1-of-2 3.0 GB: 2-of-2
Model Architecture	Qwen3ForCausalLM
Context Length	262144
Model Max Length	262144
Transformers Version	4.57.3
Tokenizer Class	Qwen2Tokenizer
Padding Token	<\|endoftext\|>
Vocabulary Size	151936
Errors	replace

Rank the MIXdevAI Qwen capabilities

Have you tried this model? Rate its performance — this feedback helps the ML community find the right model for their needs.

Instruction Following and Task Automation
Factuality and Completeness of Knowledge
Censorship and Alignment
Data Analysis and Insight Generation
Text Generation
Text Summarization and Feature Extraction
Code Generation
Multi-Language Support and Translation

Best Alternatives to MIXdevAI Qwen

Best Alternatives	Context / RAM	Downloads	Likes
FastContext 1.0 4B SFT	256K / 8.1 GB	5735	357
GRPO 4 70	256K / 8.1 GB	12	0
Qwen3 4B Instruct 2507	256K / 8.1 GB	3109972	911
Fable Traces	256K / 8.1 GB	412	210
Lightning 4B	256K / 8.1 GB	13	6
FastContext 1.0 4B RL	256K / 8.1 GB	4559	61
Qwen3 4B Thinking 2507	256K / 8.1 GB	291023	606
...pt Full Qwen3 4b Instruct 2507	256K / 8 GB	365	1
...PT Gpt5.1 Thinking Safetensors	256K / 8.1 GB	122	2
Qwen3 4B Instruct 2507 FP8	256K / 5.2 GB	1100744	78

Note: green Score (e.g. "73.2") means that the model is better than Kolyadual/MIXdevAI-qwen.