What are the hardware requirements for Mistral Sharegpt90k Merged 16bit?

Mistral Sharegpt90k Merged 16bit 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 Sharegpt90k Merged 16bit and how large is it?

Mistral Sharegpt90k Merged 16bit is developed by pacozaa, 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 Sharegpt90k Merged 16bit perform on standard benchmarks?

Mistral Sharegpt90k Merged 16bit has the following published scores: MMLU 62.96. Compare against reference models on this page or on the LLM Explorer leaderboards.

Mistral Sharegpt90k Merged 16bit by pacozaa — VRAM 14.4GB, 32K context

Name: Mistral Sharegpt90k Merged 16bit
Author: pacozaa

Mistral Sharegpt90k Merged 16bit is an open-source language model by pacozaa. Features: 7b LLM, VRAM: 14.4GB, Context: 32K, License: apache-2.0, Quantized, Merged, LLM Explorer Score: 0.14, Arc: 59.3, HellaSwag: 82.9, MMLU: 63, GSM8K: 35.1.

Merged Model 4bit Base model:finetune:unsloth/mi... Base model:unsloth/mistral-7b-... Conversational Dataset:liyucheng/sharegpt90k En Endpoints compatible Mistral Ollama Pytorch Quantized Region:us Safetensors Sharded Tensorflow Trl Unsloth

Model Card on HF 🤗: https://huggingface.co/pacozaa/mistral-sharegpt90k-merged_16bit

Mistral Sharegpt90k Merged 16bit Parameters and Internals

Model Type

text-generation-inference, transformers

Additional Notes

This mistral model was trained 2x faster with Unsloth and Huggingface's TRL library.

Supported Languages

en (English)

LLM Name	Mistral Sharegpt90k Merged 16bit
Repository 🤗	https://huggingface.co/pacozaa/mistral-sharegpt90k-merged_16bit
Base Model(s)	Mistral 7B Bnb 4bit unsloth/mistral-7b-bnb-4bit
Merged Model	Yes
Model Size	7b
Required VRAM	14.4 GB
Updated	2026-08-05
Maintainer	pacozaa
Model Type	mistral
Model Files	4.9 GB: 1-of-3 5.0 GB: 2-of-3 4.5 GB: 3-of-3 4.9 GB: 1-of-3 5.0 GB: 2-of-3 4.5 GB: 3-of-3
Supported Languages	en
Quantization Type	4bit
Model Architecture	MistralForCausalLM
License	apache-2.0
Context Length	32768
Model Max Length	32768
Transformers Version	4.38.2
Tokenizer Class	LlamaTokenizer
Padding Token	<unk>
Vocabulary Size	32000
Torch Data Type	float16

Rank the Mistral Sharegpt90k Merged 16bit 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

Best Alternatives to Mistral Sharegpt90k Merged 16bit

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...t 3.5 0106 128K 4.0bpw H6 EXL2	128K / 3.9 GB	4	1
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...aude Sonnet Mistral 7B It V0.3	32K / 14.5 GB	7	2
Mistral 7B V0.3 Bnb 4bit	32K / 4.1 GB	381323	22
Mistral 7B Instruct V0.2 Fp16	32K / 14.4 GB	26	0
Mistral 7B Instruct V0.2 4bit	32K / 4.3 GB	79	1
...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	5	0

Note: green Score (e.g. "73.2") means that the model is better than pacozaa/mistral-sharegpt90k-merged_16bit.