What are the hardware requirements for Small Mixtral Ja Llm Jp Tk Instruction?

Small Mixtral Ja Llm Jp Tk Instruction requires approximately 2.9 GB of VRAM and supports a context window of 2K tokens. Quantized variants may run on less VRAM; see the Quantized Models section on this page.

Who developed Small Mixtral Ja Llm Jp Tk Instruction and how large is it?

Small Mixtral Ja Llm Jp Tk Instruction is developed by if001, a model with 100m 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 Small Mixtral Ja Llm Jp Tk Instruction?

Small Mixtral Ja Llm Jp Tk Instruction is hosted on Hugging Face and linked from this page. LLM Explorer also lists quantized variants and similar alternatives if available.

Small Mixtral Ja Llm Jp Tk Instruction by if001 — VRAM 2.9GB, 2K context

Name: Small Mixtral Ja Llm Jp Tk Instruction
Author: if001

Small Mixtral Ja Llm Jp Tk Instruction is an open-source language model by if001. Features: 100m LLM, VRAM: 2.9GB, Context: 2K, License: apache-2.0, Instruction-Based, LLM Explorer Score: 0.11.

Endpoints compatible Instruct Mixtral Region:us Safetensors

Model Card on HF 🤗: https://huggingface.co/if001/small_mixtral_ja_llm_jp_tk_instruction

Small Mixtral Ja Llm Jp Tk Instruction Parameters and Internals

LLM Name	Small Mixtral Ja Llm Jp Tk Instruction
Repository 🤗	https://huggingface.co/if001/small_mixtral_ja_llm_jp_tk_instruction
Model Size	100m
Required VRAM	2.9 GB
Updated	2026-07-23
Maintainer	if001
Model Type	mixtral
Instruction-Based	Yes
Model Files	2.9 GB
Model Architecture	MixtralForCausalLM
License	apache-2.0
Context Length	2048
Model Max Length	2048
Transformers Version	4.38.2
Vocabulary Size	50570
Torch Data Type	float32

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Instruction Following and Task Automation
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Text Generation
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