What are the hardware requirements for Candle Mistral 7B Instruct V0.2?

Candle Mistral 7B Instruct V0.2 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 Candle Mistral 7B Instruct V0.2 and how large is it?

Candle Mistral 7B Instruct V0.2 is developed by DanielClough, 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 Candle Mistral 7B Instruct V0.2 perform on standard benchmarks?

Candle Mistral 7B Instruct V0.2 has the following published scores: MMLU 59.1, LMSYS ELO 1072. Compare against reference models on this page or on the LLM Explorer leaderboards.

Candle Mistral 7B Instruct V0.2 by DanielClough — VRAM 14.4GB, 32K context

Name: Candle Mistral 7B Instruct V0.2
Author: DanielClough

Candle Mistral 7B Instruct V0.2 is an open-source language model by DanielClough. Features: 7b LLM, VRAM: 14.4GB, Context: 32K, License: apache-2.0, Quantized, Instruction-Based, LLM Explorer Score: 0.23, ELO: 1072, Arc: 56.7, HellaSwag: 80.8, MMLU: 59.1, GSM8K: 37.6.

Dataset:mistralai/mistral-7b-i... En Endpoints compatible Gguf Instruct Mistral Q4 Quantized Region:us Sharded Tensorflow

Model Card on HF 🤗: https://huggingface.co/DanielClough/Candle_Mistral-7B-Instruct-v0.2

Candle Mistral 7B Instruct V0.2 Benchmarks

LMSys ELO 1072 vs 1272 (so35) -15.7%

^nn.n% — How the model compares to the reference models: Anthropic Sonnet 3.5 ("so35"), GPT-4o ("gpt4o") or GPT-4 ("gpt4").

What is the LLM Explorer Rank (Score)

Candle Mistral 7B Instruct V0.2 Parameters and Internals

LLM Name	Candle Mistral 7B Instruct V0.2
Repository 🤗	https://huggingface.co/DanielClough/Candle_Mistral-7B-Instruct-v0.2
Base Model(s)	Mistral 7B Orca DPO 2h SC56/Mistral-7B-orca-dpo-2h
Model Size	7b
Required VRAM	14.4 GB
Updated	2026-09-07
Maintainer	DanielClough
Model Type	mistral
Instruction-Based	Yes
Model Files	14.5 GB 2.4 GB 3.1 GB 4.1 GB 4.5 GB 4.1 GB 5.0 GB 5.4 GB 5.0 GB 5.9 GB 7.7 GB 8.2 GB 8.3 GB 4.9 GB: 1-of-3 5.0 GB: 2-of-3 4.5 GB: 3-of-3
Supported Languages	en
GGUF Quantization	Yes
Quantization Type	q4\|gguf
Model Architecture	MistralForCausalLM
License	apache-2.0
Context Length	32768
Model Max Length	32768
Transformers Version	4.36.0
Vocabulary Size	32000
Torch Data Type	bfloat16

Rank the Candle Mistral 7B Instruct V0.2 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 Candle Mistral 7B Instruct V0.2

Best Alternatives	Context / RAM	Downloads	Likes
Mistral 7B Instruct V0.2.gguf	32K / 14.5 GB	17	3
Mistral 7B Instruct V0.2 GGUF	32K / 4.4 GB	26	2
Tamil Mistral 7B Instruct V0.1	32K / 14.8 GB	350	14
Mistral V0.3 7B Cybersecurity	32K / 14.5 GB	52	1
BioMistralMerged	32K / 14.4 GB	54	2
...andle Mistral 7B Instruct V0.1	32K / 14.4 GB	1298	3
Mistral 7B Instruct V0.3 GGUF	32K / 2.7 GB	189	1
Mistral 7B Instruct V0.3 GGUF	32K / 2.7 GB	156	1
...stral 7B V0.3 Chinese Chat F16	32K / 14.5 GB	51	1
...tral 7B V0.3 Chinese Chat 4bit	32K / 4.1 GB	45	2

Note: green Score (e.g. "73.2") means that the model is better than DanielClough/Candle_Mistral-7B-Instruct-v0.2.