What are the hardware requirements for MegaBeam Mistral 7B 300K?

MegaBeam Mistral 7B 300K requires approximately 14.4 GB of VRAM and supports a context window of 282K tokens. Quantized variants may run on less VRAM; see the Quantized Models section on this page.

Who developed MegaBeam Mistral 7B 300K and how large is it?

MegaBeam Mistral 7B 300K is developed by amazon, a model with 7b 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 MegaBeam Mistral 7B 300K?

MegaBeam Mistral 7B 300K is hosted on Hugging Face and linked from this page. LLM Explorer also lists quantized variants and similar alternatives if available.

MegaBeam Mistral 7B 300K by amazon — VRAM 14.4GB, 282K context

Name: MegaBeam Mistral 7B 300K
Author: amazon

MegaBeam Mistral 7B 300K is an open-source language model by amazon. Features: 7b LLM, VRAM: 14.4GB, Context: 282K, License: apache-2.0, LLM Explorer Score: 0.19.

Autotrain compatible Conversational Mistral Region:us Safetensors Sharded Tensorflow

Model Card on HF 🤗: https://huggingface.co/amazon/MegaBeam-Mistral-7B-300k

MegaBeam Mistral 7B 300K Parameters and Internals

Model Type

language model

Use Cases

Primary Use Cases:

processing long contexts

Limitations:

Ensure compliance with local regulations and quality standards.

Additional Notes

Ensure model use complies with local regulations and quality standards.

Training Details

Methodology:

fine-tuned

Context Length:

320000

Input Output

Input Format:

320K max position embeddings.

Accepted Modalities:

text

LLM Name	MegaBeam Mistral 7B 300K
Repository 🤗	https://huggingface.co/amazon/MegaBeam-Mistral-7B-300k
Model Size	7b
Required VRAM	14.4 GB
Updated	2025-03-19
Maintainer	amazon
Model Type	mistral
Model Files	4.9 GB: 1-of-3 5.0 GB: 2-of-3 4.5 GB: 3-of-3
Model Architecture	MistralForCausalLM
License	apache-2.0
Context Length	288800
Model Max Length	288800
Transformers Version	4.36.0
Tokenizer Class	LlamaTokenizer
Vocabulary Size	32000
Torch Data Type	bfloat16

Rank the MegaBeam Mistral 7B 300K 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

Quantized Models of the MegaBeam Mistral 7B 300K

Model	Likes	Downloads	VRAM
MegaBeam Mistral 7B 300K Gguf	3	35	5 GB

Best Alternatives to MegaBeam Mistral 7B 300K

Best Alternatives	Context / RAM	Downloads	Likes
...Nemo Instruct 2407 Abliterated	1000K / 24.5 GB	220	20
MegaBeam Mistral 7B 512K	512K / 14.4 GB	8470	54
SpydazWeb AI HumanAI RP	512K / 14.4 GB	16	1
SpydazWeb AI HumanAI 002	512K / 14.4 GB	18	1
...daz Web AI ChatML 512K Project	512K / 14.5 GB	12	0
MegaBeam Mistral 7B 300K	282K / 14.4 GB	8018	17
Hebrew Mistral 7B 200K	256K / 30 GB	23	15
Astral 256K 7B	250K / 14.4 GB	9	0
Astral 256K 7B V2	250K / 14.4 GB	8	0
Test001	128K / 14.5 GB	9	0

Note: green Score (e.g. "73.2") means that the model is better than amazon/MegaBeam-Mistral-7B-300k.