What are the hardware requirements for Kimi K2 Thinking?

Kimi K2 Thinking requires approximately 158.2 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 Kimi K2 Thinking and how large is it?

Kimi K2 Thinking is developed by mlx-community, a model with 1026.4b 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 Kimi K2 Thinking?

Kimi K2 Thinking is hosted on Hugging Face and linked from this page. LLM Explorer also lists quantized variants and similar alternatives if available.

Kimi K2 Thinking by mlx-community — VRAM 158.2GB, 256K context

Name: Kimi K2 Thinking
Author: mlx-community

Kimi K2 Thinking is an open-source language model by mlx-community. Features: 1026.4b LLM, VRAM: 158.2GB, Context: 256K, License: other, LLM Explorer Score: 0.25.

4-bit Base model:moonshotai/kimi-k2-... Base model:quantized:moonshota... Conversational Custom code Kimi k2 Mlx Region:us Safetensors Sharded Tensorflow

Model Card on HF 🤗: https://huggingface.co/mlx-community/Kimi-K2-Thinking

Kimi K2 Thinking Parameters and Internals

LLM Name	Kimi K2 Thinking
Repository 🤗	https://huggingface.co/mlx-community/Kimi-K2-Thinking
Base Model(s)	Kimi K2 Thinking moonshotai/Kimi-K2-Thinking
Model Size	1026.4b
Required VRAM	158.2 GB
Updated	2026-07-21
Maintainer	mlx-community
Model Type	kimi_k2
Model Files	3.5 GB: 1-of-182 3.5 GB: 2-of-182 3.5 GB: 3-of-182 3.8 GB: 4-of-182 3.5 GB: 5-of-182 3.5 GB: 6-of-182 3.8 GB: 7-of-182 3.5 GB: 8-of-182 3.5 GB: 9-of-182 3.8 GB: 10-of-182 3.5 GB: 11-of-182 3.5 GB: 12-of-182 3.8 GB: 13-of-182 3.5 GB: 14-of-182 3.5 GB: 15-of-182 3.8 GB: 16-of-182 3.5 GB: 17-of-182 3.5 GB: 18-of-182 3.8 GB: 19-of-182 3.5 GB: 20-of-182 3.5 GB: 21-of-182 3.8 GB: 22-of-182 3.5 GB: 23-of-182 3.5 GB: 24-of-182 3.8 GB: 25-of-182 3.5 GB: 26-of-182 3.5 GB: 27-of-182 3.8 GB: 28-of-182 3.5 GB: 29-of-182 3.5 GB: 30-of-182 3.8 GB: 31-of-182 3.5 GB: 32-of-182 3.5 GB: 33-of-182 3.8 GB: 34-of-182 3.5 GB: 35-of-182 3.5 GB: 36-of-182 3.8 GB: 37-of-182 3.5 GB: 38-of-182 3.5 GB: 39-of-182 3.8 GB: 40-of-182 3.5 GB: 41-of-182 3.5 GB: 42-of-182 3.8 GB: 43-of-182 3.5 GB: 44-of-182
Model Architecture	DeepseekV3ForCausalLM
License	other
Context Length	262144
Model Max Length	262144
Transformers Version	4.51.3
Vocabulary Size	163840
Torch Data Type	bfloat16

Rank the Kimi K2 Thinking 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 Kimi K2 Thinking

Best Alternatives	Context / RAM	Downloads	Likes
...i K2 Instruct 0905 Mlx DQ3 K M	256K / 204.6 GB	2234	12
Kimi K2 Instruct 0905 BF16	256K / 1399.1 GB	31	4
Kimi K2 Instruct BF16	128K / 1367.3 GB	20	4
Kimi K2 Base BF16	128K / 1367.3 GB	27	1
Kimi K2 Thinking 4bit	256K / 151.2 GB	589	9
Kimi K2 Thinking 3bit	256K / 219.3 GB	140	1
Kimi K2 Instruct 4bit	128K / 143.2 GB	5265	13

Note: green Score (e.g. "73.2") means that the model is better than mlx-community/Kimi-K2-Thinking.