What are the hardware requirements for SmolLM2 1.7B R1 Distilled?

SmolLM2 1.7B R1 Distilled 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 R1 Distilled and how large is it?

SmolLM2 1.7B R1 Distilled is developed by rbgo, 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 R1 Distilled?

SmolLM2 1.7B R1 Distilled is hosted on Hugging Face and linked from this page. LLM Explorer also lists quantized variants and similar alternatives if available.

SmolLM2 1.7B R1 Distilled by rbgo — VRAM 3.4GB, 8K context

Name: SmolLM2 1.7B R1 Distilled
Author: rbgo

SmolLM2 1.7B R1 Distilled is an open-source language model by rbgo. Features: 1.7b LLM, VRAM: 3.4GB, Context: 8K, Instruction-Based, LLM Explorer Score: 0.17.

Arxiv:1910.09700 Conversational Endpoints compatible Instruct Llama Region:us Safetensors Sft Trl

Model Card on HF 🤗: https://huggingface.co/rbgo/SmolLM2-1.7B-R1-Distilled

SmolLM2 1.7B R1 Distilled Parameters and Internals

LLM Name	SmolLM2 1.7B R1 Distilled
Repository 🤗	https://huggingface.co/rbgo/SmolLM2-1.7B-R1-Distilled
Model Size	1.7b
Required VRAM	3.4 GB
Updated	2026-07-07
Maintainer	rbgo
Model Type	llama
Instruction-Based	Yes
Model Files	3.4 GB
Model Architecture	LlamaForCausalLM
Context Length	8192
Model Max Length	8192
Transformers Version	4.49.0
Tokenizer Class	GPT2Tokenizer
Padding Token	<\|im_end\|>
Vocabulary Size	49154
Torch Data Type	float16

Rank the SmolLM2 1.7B R1 Distilled 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

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SmolLM2 1.7B Instruct 16K	16K / 3.4 GB	103	10
SmolLM2 1.7B Instruct	8K / 3.4 GB	154013	742
Yoru	8K / 3.4 GB	309	0
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...ygnis Alpha 1.7B V0.1 Instruct	8K / 3.4 GB	11	2
SmolTulu 1.7B Reinforced	8K / 3.4 GB	12	5
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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

Note: green Score (e.g. "73.2") means that the model is better than rbgo/SmolLM2-1.7B-R1-Distilled.