What are the hardware requirements for SmollerLM 63M Instruct Base?

SmollerLM 63M Instruct Base requires approximately 0.1 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 SmollerLM 63M Instruct Base and how large is it?

SmollerLM 63M Instruct Base is developed by mehmetkeremturkcan, a model with 63m 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 SmollerLM 63M Instruct Base?

SmollerLM 63M Instruct Base is hosted on Hugging Face and linked from this page. LLM Explorer also lists quantized variants and similar alternatives if available.

SmollerLM 63M Instruct Base by mehmetkeremturkcan — VRAM 0.1GB, 8K context

Name: SmollerLM 63M Instruct Base
Author: mehmetkeremturkcan

SmollerLM 63M Instruct Base is an open-source language model by mehmetkeremturkcan. Features: 63m LLM, VRAM: 0.1GB, Context: 8K, License: apache-2.0, Instruction-Based, LLM Explorer Score: 0.16.

Instruct Llama Region:us Safetensors

Model Card on HF 🤗: https://huggingface.co/mehmetkeremturkcan/SmollerLM-63M-Instruct-Base

SmollerLM 63M Instruct Base Parameters and Internals

LLM Name	SmollerLM 63M Instruct Base
Repository 🤗	https://huggingface.co/mehmetkeremturkcan/SmollerLM-63M-Instruct-Base
Model Size	63m
Required VRAM	0.1 GB
Updated	2026-06-11
Maintainer	mehmetkeremturkcan
Model Type	llama
Instruction-Based	Yes
Model Files	0.1 GB
Model Architecture	LlamaForCausalLM
License	apache-2.0
Context Length	8192
Model Max Length	8192
Transformers Version	4.46.2
Tokenizer Class	GPT2Tokenizer
Padding Token	<\|im_end\|>
Vocabulary Size	49152
Torch Data Type	float16
Errors	replace

Rank the SmollerLM 63M Instruct Base 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 SmollerLM 63M Instruct Base

Best Alternatives	Context / RAM	Downloads	Likes
SmollerLM 48M Instruct Ft Sft	8K / 0.2 GB	6	2

Note: green Score (e.g. "73.2") means that the model is better than mehmetkeremturkcan/SmollerLM-63M-Instruct-Base.