What are the hardware requirements for Gemma Ko 7B Instruct V0.62?

Gemma Ko 7B Instruct V0.62 requires approximately 17 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 Gemma Ko 7B Instruct V0.62 and how large is it?

Gemma Ko 7B Instruct V0.62 is developed by lemon-mint, 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 Gemma Ko 7B Instruct V0.62 perform on standard benchmarks?

Gemma Ko 7B Instruct V0.62 has the following published scores: MMLU 64.39. Compare against reference models on this page or on the LLM Explorer leaderboards.

Gemma Ko 7B Instruct V0.62 by lemon-mint — VRAM 17GB, 8K context

Name: Gemma Ko 7B Instruct V0.62
Author: lemon-mint

Gemma Ko 7B Instruct V0.62 is an open-source language model by lemon-mint. Features: 7b LLM, VRAM: 17GB, Context: 8K, License: other, Instruction-Based, LLM Explorer Score: 0.13, Arc: 63.3, HellaSwag: 79.6, MMLU: 64.4, GSM8K: 71.6.

Base model:finetune:openchat/o... Base model:openchat/openchat-3... Conversational En Endpoints compatible Gemma Instruct Ko Korean Pytorch Region:us Safetensors Sharded Tensorflow

Model Card on HF 🤗: https://huggingface.co/lemon-mint/gemma-ko-7b-instruct-v0.62

Gemma Ko 7B Instruct V0.62 Parameters and Internals

Model Type

text generation

Use Cases

Areas:

natural language processing

Applications:

language translation, text summarization, question answering, conversation generation

Limitations:

Bias from extensive web data, Possible generation of errors or incorrect information

Considerations:

Refer to the model's output with caution.

Additional Notes

The model is particularly well-suited for applications requiring high-quality, coherent, and contextually relevant Korean text generation.

Supported Languages

Korean (advanced), English (unknown proficiency)

LLM Name	Gemma Ko 7B Instruct V0.62
Repository 🤗	https://huggingface.co/lemon-mint/gemma-ko-7b-instruct-v0.62
Base Model(s)	openchat/openchat-3.5-0106-gemma openchat/openchat-3.5-0106-gemma
Model Size	7b
Required VRAM	17 GB
Updated	2026-07-22
Maintainer	lemon-mint
Model Type	gemma
Instruction-Based	Yes
Model Files	2.9 GB: 1-of-6 2.9 GB: 2-of-6 3.0 GB: 3-of-6 2.9 GB: 4-of-6 2.9 GB: 5-of-6 2.4 GB: 6-of-6
Supported Languages	ko en
Model Architecture	GemmaForCausalLM
License	other
Context Length	8192
Model Max Length	8192
Transformers Version	4.40.0.dev0
Tokenizer Class	GemmaTokenizer
Padding Token	<pad>
Vocabulary Size	256000
Torch Data Type	bfloat16

Rank the Gemma Ko 7B Instruct V0.62 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 Gemma Ko 7B Instruct V0.62

Best Alternatives	Context / RAM	Downloads	Likes
...emma 7B It Legal Refugiados Es	8K / 34 GB	5	0
... 7B Finetuned Sft Navarasa 2.0	8K / 34 GB	412	25
Gemma Ko 7B Instruct V0.71	8K / 17 GB	3	1
X Instruction 7B Ta	8K / 17.1 GB	6	0
X Instruction 7B Id	8K / 17.1 GB	6	0
RoGemma 7B Instruct	8K / 17.1 GB	43	1
X Instruction 7B 10langs	8K / 17.1 GB	7	0
Zephyr Gemma 7B Telugu	8K / 17.1 GB	13	3
Gemma Ko 7B Instruct V0.52	8K / 17 GB	8	0
Gemma Ko 7B Instruct V0.50	8K / 17 GB	5	0

Note: green Score (e.g. "73.2") means that the model is better than lemon-mint/gemma-ko-7b-instruct-v0.62.