What are the hardware requirements for SmolLM2 1.7B Instruct 16K?

SmolLM2 1.7B Instruct 16K requires approximately 3.4 GB of VRAM and supports a context window of 16K tokens. Quantized variants may run on less VRAM; see the Quantized Models section on this page.

Who developed SmolLM2 1.7B Instruct 16K and how large is it?

SmolLM2 1.7B Instruct 16K is developed by HuggingFaceTB, 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 Instruct 16K?

SmolLM2 1.7B Instruct 16K is hosted on Hugging Face and linked from this page. LLM Explorer also lists quantized variants and similar alternatives if available.

SmolLM2 1.7B Instruct 16K by HuggingFaceTB — VRAM 3.4GB, 16K context

Name: SmolLM2 1.7B Instruct 16K
Author: HuggingFaceTB

SmolLM2 1.7B Instruct 16K is an open-source language model by HuggingFaceTB. Features: 1.7b LLM, VRAM: 3.4GB, Context: 16K, License: apache-2.0, Instruction-Based, LLM Explorer Score: 0.17.

Arxiv:2502.02737 Base model:finetune:huggingfac... Base model:huggingfacetb/smoll... Conversational En Endpoints compatible Instruct Llama Region:us Safetensors

Model Card on HF 🤗: https://huggingface.co/HuggingFaceTB/SmolLM2-1.7B-Instruct-16k

SmolLM2 1.7B Instruct 16K Parameters and Internals

LLM Name	SmolLM2 1.7B Instruct 16K
Repository 🤗	https://huggingface.co/HuggingFaceTB/SmolLM2-1.7B-Instruct-16k
Base Model(s)	HuggingFaceTB/SmolLM2-1.7B-Instruct-16k HuggingFaceTB/SmolLM2-1.7B-Instruct-16k
Model Size	1.7b
Required VRAM	3.4 GB
Updated	2026-08-06
Maintainer	HuggingFaceTB
Model Type	llama
Instruction-Based	Yes
Model Files	3.4 GB 0.0 GB
Supported Languages	en
Model Architecture	LlamaForCausalLM
License	apache-2.0
Context Length	16384
Model Max Length	16384
Transformers Version	4.48.1
Tokenizer Class	GPT2Tokenizer
Padding Token	<\|im_end\|>
Vocabulary Size	49152
Torch Data Type	bfloat16

Rank the SmolLM2 1.7B Instruct 16K 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 SmolLM2 1.7B Instruct 16K

Best Alternatives	Context / RAM	Downloads	Likes
SmolLM2 1.7B Instruct	8K / 3.4 GB	154013	742
Yoru	8K / 3.4 GB	309	0
SmolLM2 1.7B Instruct	8K / 3.4 GB	4909	6
...ygnis Alpha 1.7B V0.1 Instruct	8K / 3.4 GB	11	2
SmolTulu 1.7B Reinforced	8K / 3.4 GB	12	5
SmolLM2 1.7 Persona	8K / 3.5 GB	7	0
Superthoughts Lite V1	8K / 3.4 GB	92	3
Penny 1.7B	8K / 6.9 GB	18	24
...ghts Lite 1.8B Experimental O1	8K / 3.6 GB	11	2
Cllm 1.0.0 340000 Instruct	8K / 3.5 GB	5	0

Note: green Score (e.g. "73.2") means that the model is better than HuggingFaceTB/SmolLM2-1.7B-Instruct-16k.