What are the hardware requirements for Magot V2 Gemma2 8K 9B?

Magot V2 Gemma2 8K 9B requires approximately 18.6 GB of VRAM and supports a context window of 8K tokens. Quantized variants may run on less VRAM; see the Quantized Models section on this page.

Who developed Magot V2 Gemma2 8K 9B and how large is it?

Magot V2 Gemma2 8K 9B is developed by grimjim, a model with 9b 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 Magot V2 Gemma2 8K 9B?

Magot V2 Gemma2 8K 9B is hosted on Hugging Face and linked from this page. LLM Explorer also lists quantized variants and similar alternatives if available.

Magot V2 Gemma2 8K 9B by grimjim — VRAM 18.6GB, 8K context

Name: Magot V2 Gemma2 8K 9B
Author: grimjim

Magot V2 Gemma2 8K 9B is an open-source language model by grimjim. Features: 9b LLM, VRAM: 18.6GB, Context: 8K, License: gemma, Merged, LLM Explorer Score: 0.23.

Merged Model Base model:anthracite-org/magn... Base model:grimjim/kitsunebi-v... Conversational Endpoints compatible Ext 8k Gemma2 Region:us Safetensors Sharded Tensorflow

Model Card on HF 🤗: https://huggingface.co/grimjim/Magot-v2-Gemma2-8k-9B

Magot V2 Gemma2 8K 9B Parameters and Internals

Model Type

text-generation

Additional Notes

There appears to be some damage to the model from merging. Stability has been improved by retaining embed_tokens and lm_head weights from the base model. Coherence is moderately high, though not perfect. The model tends towards melodramatic motifs, indicating certain favored tropes are baked into the model.

Training Details

Context Length:

8000

LLM Name	Magot V2 Gemma2 8K 9B
Repository 🤗	https://huggingface.co/grimjim/Magot-v2-Gemma2-8k-9B
Base Model(s)	Magnum V3 9B Customgemma2 Kitsunebi V1 Gemma2 8K 9B anthracite-org/magnum-v3-9b-customgemma2 grimjim/Kitsunebi-v1-Gemma2-8k-9B
Merged Model	Yes
Model Size	9b
Required VRAM	18.6 GB
Updated	2026-06-05
Maintainer	grimjim
Model Type	gemma2
Model Files	3.9 GB: 1-of-5 4.0 GB: 2-of-5 4.0 GB: 3-of-5 4.0 GB: 4-of-5 2.7 GB: 5-of-5
Context Length	8k
Model Architecture	Gemma2ForCausalLM
License	gemma
Context Length	8192
Model Max Length	8192
Transformers Version	4.44.2
Tokenizer Class	GemmaTokenizer
Padding Token	<pad>
Vocabulary Size	256000
Torch Data Type	bfloat16

Rank the Magot V2 Gemma2 8K 9B 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 Magot V2 Gemma2 8K 9B

Best Alternatives	Context / RAM	Downloads	Likes
G2 GSHT 32K	32K / 20.4 GB	8	1
SystemGemma2 9B It	32K / 18.6 GB	5	2
Gemma 2 9B It	8K / 18.6 GB	80757	11
GWQ 9B Preview2	8K / 18.6 GB	11	10
Gemma 2 9B It	8K / 18.6 GB	6	0
Gemma 2 9B It SimPO	8K / 18.6 GB	473	173
Gemma 2 9B It	8K / 18.6 GB	323635	837
Gemma 2 9B It Blend Rebase	8K / 20.4 GB	5	0
...ty Gemma2 9b It Swift Remove20	8K / 18.6 GB	179	1
Gemma 2 9B	8K / 37.1 GB	95888	717

Note: green Score (e.g. "73.2") means that the model is better than grimjim/Magot-v2-Gemma2-8k-9B.