What are the hardware requirements for SmolLM2 1.7B Merged?

SmolLM2 1.7B Merged requires approximately 3.4 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 SmolLM2 1.7B Merged and how large is it?

SmolLM2 1.7B Merged is developed by vonjack, a model with 1.7b 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 SmolLM2 1.7B Merged?

SmolLM2 1.7B Merged is hosted on Hugging Face and linked from this page. LLM Explorer also lists quantized variants and similar alternatives if available.

SmolLM2 1.7B Merged by vonjack — VRAM 3.4GB, 8K context

Name: SmolLM2 1.7B Merged
Author: vonjack

SmolLM2 1.7B Merged is an open-source language model by vonjack. Features: 1.7b LLM, VRAM: 3.4GB, Context: 8K, Quantized, Instruction-Based, Merged, LLM Explorer Score: 0.18.

Merged Model Arxiv:2306.01708 Base model:huggingfacetb/smoll... Base model:huggingfacetb/smoll... Conversational Endpoints compatible Gguf Instruct Llama Q4 Quantized Region:us Safetensors Sharded Tensorflow

Model Card on HF 🤗: https://huggingface.co/vonjack/SmolLM2-1.7B-Merged

SmolLM2 1.7B Merged Parameters and Internals

LLM Name	SmolLM2 1.7B Merged
Repository 🤗	https://huggingface.co/vonjack/SmolLM2-1.7B-Merged
Base Model(s)	HuggingFaceTB/SmolLM2-1.7B HuggingFaceTB/SmolLM2-1.7B-Instruct HuggingFaceTB/SmolLM2-1.7B HuggingFaceTB/SmolLM2-1.7B-Instruct
Merged Model	Yes
Model Size	1.7b
Required VRAM	3.4 GB
Updated	2026-07-23
Maintainer	vonjack
Model Type	llama
Instruction-Based	Yes
Model Files	1.1 GB 3.4 GB: 1-of-1
GGUF Quantization	Yes
Quantization Type	q4\|gguf\|q4_k
Model Architecture	LlamaForCausalLM
Context Length	8192
Model Max Length	8192
Transformers Version	4.46.0
Tokenizer Class	GPT2Tokenizer
Vocabulary Size	49152
Torch Data Type	bfloat16

Rank the SmolLM2 1.7B Merged capabilities

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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 SmolLM2 1.7B Merged

Best Alternatives	Context / RAM	Downloads	Likes
TwIL LM	8K / 1.1 GB	519	10
Smolgpt Fables	8K / 1.1 GB	1341	0
SmolLM2 1.7B Instruct Q8 Mlx	8K / 1.8 GB	258	5
SmolLM2 1.7B Instruct Bnb 4bit	8K / 1 GB	407	2
SmolLM 1.7B Bnb 4bit	2K / 1 GB	34	2
SmolLM 1.7B Instruct 4bit	2K / 1 GB	70	2
SmolLM 1.7B Instruct 8bit	2K / 1.8 GB	9	1
SmolLM2 1.7B Instruct 16K	16K / 3.4 GB	103	10
SmolLM2 1.7B Instruct	8K / 3.4 GB	154013	742
SmolLM2 1.7B Instruct	8K / 3.4 GB	4909	6

Note: green Score (e.g. "73.2") means that the model is better than vonjack/SmolLM2-1.7B-Merged.