What are the hardware requirements for Mixtral Ep64 200M?

Mixtral Ep64 200M requires a context window of 128K tokens. Quantized variants may run on less VRAM; see the Quantized Models section on this page.

Who developed Mixtral Ep64 200M and how large is it?

Mixtral Ep64 200M is developed by ylf1017, a model with 200m 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 Mixtral Ep64 200M?

Mixtral Ep64 200M is hosted on Hugging Face and linked from this page. LLM Explorer also lists quantized variants and similar alternatives if available.

Mixtral Ep64 200M by ylf1017 — 128K context

Name: Mixtral Ep64 200M
Author: ylf1017

Mixtral Ep64 200M is an open-source language model by ylf1017. Features: 200m LLM, Context: 128K, LLM Explorer Score: 0.1.

Endpoints compatible Mixtral Region:us

Model Card on HF 🤗: https://huggingface.co/ylf1017/mixtral-ep64-200m

Mixtral Ep64 200M Parameters and Internals

LLM Name	Mixtral Ep64 200M
Repository 🤗	https://huggingface.co/ylf1017/mixtral-ep64-200m
Model Size	200m
Updated	2026-06-02
Maintainer	ylf1017
Model Type	mixtral
Model Architecture	MixtralForCausalLM
Context Length	131072
Model Max Length	131072
Transformers Version	4.36.0.dev0
Vocabulary Size	32000

Rank the Mixtral Ep64 200M capabilities

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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 Mixtral Ep64 200M

Best Alternatives	Context / RAM	Downloads	Likes
TinyMoE 200M 2x16	1K / 0 GB	960	6

Note: green Score (e.g. "73.2") means that the model is better than ylf1017/mixtral-ep64-200m.