What are the hardware requirements for Kimi K3 0.40B?

Kimi K3 0.40B requires approximately 1.6 GB of VRAM. Quantized variants may run on less VRAM; see the Quantized Models section on this page.

Who developed Kimi K3 0.40B and how large is it?

Kimi K3 0.40B is developed by inference-optimization, a model with 0.40b 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 Kimi K3 0.40B?

Kimi K3 0.40B is hosted on Hugging Face and linked from this page. LLM Explorer also lists quantized variants and similar alternatives if available.

Kimi K3 0.40B by inference-optimization — VRAM 1.6GB

Name: Kimi K3 0.40B
Author: inference-optimization

Kimi K3 0.40B is an open-source language model by inference-optimization. Features: 0.40b LLM, VRAM: 1.6GB, License: mit, LLM Explorer Score: 0.36.

Base model:finetune:moonshotai... Base model:moonshotai/kimi-k3 Custom code Feature-extraction Kimi k3 Region:us Safetensors

Model Card on HF 🤗: https://huggingface.co/inference-optimization/Kimi-K3-0.40B

Kimi K3 0.40B Parameters and Internals

LLM Name	Kimi K3 0.40B
Repository 🤗	https://huggingface.co/inference-optimization/Kimi-K3-0.40B
Base Model(s)	Kimi K3 moonshotai/Kimi-K3
Model Size	0.40b
Required VRAM	1.6 GB
Updated	2026-07-30
Maintainer	inference-optimization
Model Type	kimi_k3
Model Files	1.6 GB 0.0 GB
Model Architecture	KimiK3ForConditionalGeneration
License	mit
Transformers Version	5.15.0.dev0
Tokenizer Class	TikTokenTokenizer
Padding Token	[PAD]

Rank the Kimi K3 0.40B 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

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