What are the hardware requirements for Rho Math 7B V0.1?

Rho Math 7B V0.1 requires approximately 14.4 GB of VRAM and supports a context window of 32K tokens. Quantized variants may run on less VRAM; see the Quantized Models section on this page.

Who developed Rho Math 7B V0.1 and how large is it?

Rho Math 7B V0.1 is developed by microsoft, 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 Rho Math 7B V0.1?

Rho Math 7B V0.1 is hosted on Hugging Face and linked from this page. LLM Explorer also lists quantized variants and similar alternatives if available.

Rho Math 7B V0.1 by microsoft — VRAM 14.4GB, 32K context

Name: Rho Math 7B V0.1
Author: microsoft

Rho Math 7B V0.1 is an open-source language model by microsoft. Features: 7b LLM, VRAM: 14.4GB, Context: 32K, License: mit, LLM Explorer Score: 0.12.

Arxiv:2404.07965 En Endpoints compatible Math Mistral Region:us Safetensors Sharded Tensorflow

Model Card on HF 🤗: https://huggingface.co/microsoft/rho-math-7b-v0.1

Rho Math 7B V0.1 Parameters and Internals

Model Type

text-generation

Additional Notes

Rho-1 base models employ Selective Language Modeling (SLM) for pretraining. Models released include Rho-Math-1B and Rho-Math-7B with improvements in few-shot accuracy on the MATH dataset.

Supported Languages

en (Level not specified)

LLM Name	Rho Math 7B V0.1
Repository 🤗	https://huggingface.co/microsoft/rho-math-7b-v0.1
Model Size	7b
Required VRAM	14.4 GB
Updated	2026-04-11
Maintainer	microsoft
Model Type	mistral
Model Files	4.9 GB: 1-of-3 5.0 GB: 2-of-3 4.5 GB: 3-of-3
Supported Languages	en
Model Architecture	MistralForCausalLM
License	mit
Context Length	32768
Model Max Length	32768
Transformers Version	4.38.2
Tokenizer Class	LlamaTokenizer
Vocabulary Size	32000
Torch Data Type	bfloat16

Rank the Rho Math 7B V0.1 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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...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	3779	16
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

Note: green Score (e.g. "73.2") means that the model is better than microsoft/rho-math-7b-v0.1.