What are the hardware requirements for Stockmark 100B 4bit?

Stockmark 100B 4bit requires approximately 54.2 GB of VRAM and supports a context window of 4K tokens. Quantized variants may run on less VRAM; see the Quantized Models section on this page.

Who developed Stockmark 100B 4bit and how large is it?

Stockmark 100B 4bit is developed by mlx-community, 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 Stockmark 100B 4bit?

Stockmark 100B 4bit is hosted on Hugging Face and linked from this page. LLM Explorer also lists quantized variants and similar alternatives if available.

Stockmark 100B 4bit by mlx-community — VRAM 54.2GB, 4K context

Name: Stockmark 100B 4bit
Author: mlx-community

Stockmark 100B 4bit is an open-source language model by mlx-community. Features: 100b LLM, VRAM: 54.2GB, Context: 4K, License: mit, Quantized, LLM Explorer Score: 0.12.

4bit En Endpoints compatible Ja Llama Mlx Quantized Region:us Safetensors Sharded Tensorflow

Model Card on HF 🤗: https://huggingface.co/mlx-community/stockmark-100b-4bit

Stockmark 100B 4bit Parameters and Internals

Model Type

text generation

Additional Notes

This model was converted to MLX format.

Supported Languages

en (proficient), ja (proficient)

LLM Name	Stockmark 100B 4bit
Repository 🤗	https://huggingface.co/mlx-community/stockmark-100b-4bit
Model Size	100b
Required VRAM	54.2 GB
Updated	2026-07-20
Maintainer	mlx-community
Model Type	llama
Model Files	5.3 GB: 1-of-11 5.4 GB: 2-of-11 5.3 GB: 3-of-11 5.3 GB: 4-of-11 5.3 GB: 5-of-11 5.4 GB: 6-of-11 5.3 GB: 7-of-11 5.3 GB: 8-of-11 5.3 GB: 9-of-11 5.4 GB: 10-of-11 0.9 GB: 11-of-11
Supported Languages	ja en
Quantization Type	4bit
Model Architecture	LlamaForCausalLM
License	mit
Context Length	4096
Model Max Length	4096
Transformers Version	4.40.1
Tokenizer Class	LlamaTokenizer
Padding Token	<pad>
Vocabulary Size	60416
Torch Data Type	bfloat16

Rank the Stockmark 100B 4bit 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

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Best Alternatives	Context / RAM	Downloads	Likes
SmollerLM2 100M Instruct Sft	8K / 0.3 GB	9	1
SmollerLM2 100M	8K / 0.2 GB	5	0
Stockmark 2 100B Instruct Beta	4K / 192.9 GB	13	12
Stockmark 100B	4K / 191.9 GB	9	34
Saily 100b	4K / 235.5 GB	60	7
Plankton 100M	4K / 0.4 GB	8	0
Toam 100M V0.1	2K / 0.1 GB	207	2
Webcoder 100M Html Css Js	2K / 0.4 GB	487	0
...Climbmix Dolmino Midtrain 100B	2K / 1.5 GB	450	0
...lisLM 100M Layer Hidden Pruned	2K / 0.2 GB	820	0

Note: green Score (e.g. "73.2") means that the model is better than mlx-community/stockmark-100b-4bit.