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

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

Kimiko Mistral 7B Fp16 is developed by TheBloke, 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 Kimiko Mistral 7B Fp16?

Kimiko Mistral 7B Fp16 is hosted on Hugging Face and linked from this page. LLM Explorer also lists quantized variants and similar alternatives if available.

Kimiko Mistral 7B Fp16 by TheBloke — VRAM 14.4GB, 32K context

Name: Kimiko Mistral 7B Fp16
Author: TheBloke

Kimiko Mistral 7B Fp16 is an open-source language model by TheBloke. Features: 7b LLM, VRAM: 14.4GB, Context: 32K, License: apache-2.0, Quantized, LLM Explorer Score: 0.09.

Base model:chat-error/kimiko-m... Base model:finetune:chat-error... Fp16 Generated from trainer Mistral Pytorch Quantized Region:us Sharded

Model Card on HF 🤗: https://huggingface.co/TheBloke/Kimiko-Mistral-7B-fp16

Kimiko Mistral 7B Fp16 Parameters and Internals

Model Type

mistral

Use Cases

Applications:

Roleplay, Assistant

Additional Notes

The model was finetuned as a new 7B model; not trained on V3 dataset.

Training Details

Data Sources:

Kimiko dataset

Methodology:

Fine-tuned version on the new 7B model

Input Output

Input Format:

You are a helpful AI assistant. USER: {prompt} ASSISTANT:

LLM Name	Kimiko Mistral 7B Fp16
Repository 🤗	https://huggingface.co/TheBloke/Kimiko-Mistral-7B-fp16
Model Name	Kimiko Mistral 7B
Model Creator	nRuaif
Base Model(s)	nRuaif/Kimiko-Mistral-7B nRuaif/Kimiko-Mistral-7B
Model Size	7b
Required VRAM	14.4 GB
Updated	2026-07-30
Maintainer	TheBloke
Model Type	mistral
Model Files	9.9 GB: 1-of-2 4.5 GB: 2-of-2
Quantization Type	fp16
Model Architecture	MistralForCausalLM
License	apache-2.0
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 Kimiko Mistral 7B 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

Best Alternatives to Kimiko Mistral 7B Fp16

Best Alternatives	Context / RAM	Downloads	Likes
...t 3.5 0106 128K 4.0bpw H6 EXL2	128K / 3.9 GB	4	1
...t 3.5 0106 128K 8.0bpw H8 EXL2	128K / 7.4 GB	1	1
Mistral 7B 4bit 1C MLX	32K / 4.1 GB	156	1
Mistral 7B V0.3 Bnb 4bit	32K / 4.1 GB	381323	22
...aude Sonnet Mistral 7B It V0.3	32K / 14.5 GB	7	2
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

Note: green Score (e.g. "73.2") means that the model is better than TheBloke/Kimiko-Mistral-7B-fp16.