What are the hardware requirements for KLM 1.6?

KLM 1.6 requires approximately 0.4 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 KLM 1.6 and how large is it?

KLM 1.6 is developed by MinimaLabs, a model with 100b 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 KLM 1.6?

KLM 1.6 is hosted on Hugging Face and linked from this page. LLM Explorer also lists quantized variants and similar alternatives if available.

KLM 1.6 by MinimaLabs — VRAM 0.4GB, 2K context

Name: KLM 1.6
Author: MinimaLabs

KLM 1.6 is an open-source language model by MinimaLabs. Features: 100b LLM, VRAM: 0.4GB, Context: 2K, License: apache-2.0, LLM Explorer Score: 0.46.

Arxiv:2603.15031 Arxiv:2605.06546 Base Custom code Dataset:allenai/dolma3 dolmino... Dataset:huggingfacetb/cosmoped... Dataset:huggingfacetb/smollm-c... Dataset:ifm/math-reasoning Dataset:ifm/pretrain-behaviors Dataset:ifm/txt360-v2 Dataset:mlfoundations/dclm-bas... Dataset:nvidia/nemotron-climbm... Dataset:nvidia/openmathinstruc... Dataset:openbmb/ultradata-math Dataset:openbmb/ultrax-preview En Gated-deltanet Hybrid Klm Pretrained Region:us Safetensors Small-language-model

Model Card on HF 🤗: https://huggingface.co/MinimaLabs/KLM-1.6

KLM 1.6 Parameters and Internals

LLM Name	KLM 1.6
Repository 🤗	https://huggingface.co/MinimaLabs/KLM-1.6
Model Size	100b
Required VRAM	0.4 GB
Updated	2026-11-11
Maintainer	MinimaLabs
Model Type	klm
Model Files	0.4 GB
Supported Languages	en
Model Architecture	KLMForCausalLM
License	apache-2.0
Context Length	2048
Model Max Length	2048
Transformers Version	5.20.2
Tokenizer Class	PreTrainedTokenizerFast
Padding Token	<pad>
Vocabulary Size	4160

Rank the KLM 1.6 capabilities

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

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