What are the hardware requirements for StrangeMerges 10 7B Slerp?

StrangeMerges 10 7B Slerp 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 StrangeMerges 10 7B Slerp and how large is it?

StrangeMerges 10 7B Slerp is developed by Gille, 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 StrangeMerges 10 7B Slerp perform on standard benchmarks?

StrangeMerges 10 7B Slerp has the following published scores: MMLU 64.87. Compare against reference models on this page or on the LLM Explorer leaderboards.

StrangeMerges 10 7B Slerp by Gille — VRAM 14.4GB, 32K context

Name: StrangeMerges 10 7B Slerp
Author: Gille

StrangeMerges 10 7B Slerp is an open-source language model by Gille. Features: 7b LLM, VRAM: 14.4GB, Context: 32K, License: apache-2.0, Merged, LLM Explorer Score: 0.11, Arc: 72.4, HellaSwag: 88.3, MMLU: 64.9, GSM8K: 70.1.

Merged Model Base model:flemmingmiguel/mbx-... Endpoints compatible Flemmingmiguel/mbx-7b-v3 Mistral Model-index Region:us Safetensors Sharded Tensorflow

Model Card on HF 🤗: https://huggingface.co/Gille/StrangeMerges_10-7B-slerp

StrangeMerges 10 7B Slerp Parameters and Internals

Model Type

text-generation

Additional Notes

Model is a merge of flemmingmiguel/MBX-7B-v3 and Gille/StrangeMerges_9-7B-dare_ties using LazyMergekit.

Input Output

Accepted Modalities:

text

Output Format:

text

LLM Name	StrangeMerges 10 7B Slerp
Repository 🤗	https://huggingface.co/Gille/StrangeMerges_10-7B-slerp
Base Model(s)	MBX 7B V3 StrangeMerges 9 7B Dare Ties flemmingmiguel/MBX-7B-v3 Gille/StrangeMerges_9-7B-dare_ties
Merged Model	Yes
Model Size	7b
Required VRAM	14.4 GB
Updated	2026-08-06
Maintainer	Gille
Model Type	mistral
Model Files	9.9 GB: 1-of-2 4.5 GB: 2-of-2
Model Architecture	MistralForCausalLM
License	apache-2.0
Context Length	32768
Model Max Length	32768
Transformers Version	4.35.2
Tokenizer Class	LlamaTokenizer
Vocabulary Size	32000
Torch Data Type	bfloat16

Rank the StrangeMerges 10 7B Slerp 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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MegaBeam Mistral 7B 300K	282K / 14.4 GB	3779	16
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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 Gille/StrangeMerges_10-7B-slerp.