What are the hardware requirements for Mistral 7B Platypus Fp16?

Mistral 7B Platypus Fp16 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 Mistral 7B Platypus Fp16 and how large is it?

Mistral 7B Platypus Fp16 is developed by bhenrym14, a model with 7b parameters. The model is published as open weights on Hugging Face and indexed on LLM Explorer with full benchmark history.

How does Mistral 7B Platypus Fp16 perform on standard benchmarks?

Mistral 7B Platypus Fp16 has the following published scores: MMLU 63.16. Compare against reference models on this page or on the LLM Explorer leaderboards.

Mistral 7B Platypus Fp16 by bhenrym14 — VRAM 14.4GB, 32K context

Name: Mistral 7B Platypus Fp16
Author: bhenrym14

Mistral 7B Platypus Fp16 is an open-source language model by bhenrym14. Features: 7b LLM, VRAM: 14.4GB, Context: 32K, Quantized, LLM Explorer Score: 0.11, Arc: 61.6, HellaSwag: 82.9, MMLU: 63.2, GSM8K: 16.4.

Dataset:garage-baind/open-plat... Endpoints compatible Fp16 Mistral Quantized Region:us Safetensors Sharded Tensorflow

Model Card on HF 🤗: https://huggingface.co/bhenrym14/mistral-7b-platypus-fp16

Mistral 7B Platypus Fp16 Parameters and Internals

Model Type

instruction tuned, fine-tuned

Training Details

Data Sources:

garage-bAInd/Open-Platypus

Methodology:

QLoRA fine-tune

Training Time:

~9 hours

Hardware Used:

1x RTX 6000 Ada

Model Architecture:

Mistral

Input Output

Performance Tips:

The `Mistral` architecture requires installation of `transformers` from source.

LLM Name	Mistral 7B Platypus Fp16
Repository 🤗	https://huggingface.co/bhenrym14/mistral-7b-platypus-fp16
Base Model(s)	Mistral 7B Platypus1k lgaalves/mistral-7b-platypus1k
Model Size	7b
Required VRAM	14.4 GB
Updated	2026-08-06
Maintainer	bhenrym14
Model Type	mistral
Model Files	9.9 GB: 1-of-2 4.5 GB: 2-of-2
Quantization Type	fp16
Model Architecture	MistralForCausalLM
Context Length	32768
Model Max Length	32768
Transformers Version	4.34.0.dev0
Tokenizer Class	LlamaTokenizer
Vocabulary Size	32000
Torch Data Type	float16

Rank the Mistral 7B Platypus Fp16 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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Mistral 7B Instruct V0.2 Fp16	32K / 14.4 GB	26	0
Mistral 7B V0.3 Bnb 4bit	32K / 4.1 GB	381323	22
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...tral 7B Instruct V0.3 Bnb 4bit	32K / 4.1 GB	34633	42
Mistral 7B Instruct V0.2 8bit	32K / 7.6 GB	5	1
...tral 7B Instruct V0.2 Bnb 4bit	32K / 4.1 GB	7160	35
Mixtral V0.3 Full 16bit	32K / 14.5 GB	12	0

Note: green Score (e.g. "73.2") means that the model is better than bhenrym14/mistral-7b-platypus-fp16.