What are the hardware requirements for Smol Llama 220M Openhermes?

Smol Llama 220M Openhermes requires approximately 0.4 GB of VRAM and supports a context window of 2K tokens. Quantized variants may run on less VRAM; see the Quantized Models section on this page.

Who developed Smol Llama 220M Openhermes and how large is it?

Smol Llama 220M Openhermes is developed by BEE-spoke-data, a model with 220m parameters. The model is published as open weights on Hugging Face and indexed on LLM Explorer with full benchmark history.

How does Smol Llama 220M Openhermes perform on standard benchmarks?

Smol Llama 220M Openhermes has the following published scores: MMLU 26.17. Compare against reference models on this page or on the LLM Explorer leaderboards.

Smol Llama 220M Openhermes by BEE-spoke-data — VRAM 0.4GB, 2K context

Name: Smol Llama 220M Openhermes
Author: BEE-spoke-data

Smol Llama 220M Openhermes is an open-source language model by BEE-spoke-data. Features: 220m LLM, VRAM: 0.4GB, Context: 2K, License: apache-2.0, LLM Explorer Score: 0.16, Arc: 25.2, HellaSwag: 29, MMLU: 26.2, GSM8K: 0.6.

Base model:bee-spoke-data/smol... Base model:finetune:bee-spoke-... Dataset:teknium/openhermes Endpoints compatible Llama Model-index Region:us Safetensors

Model Card on HF 🤗: https://huggingface.co/BEE-spoke-data/smol_llama-220M-openhermes

Smol Llama 220M Openhermes Parameters and Internals

Model Type

text-generation

Additional Notes

This is an experimental model with limitations due to its smaller size.

Training Details

Data Sources:

teknium/openhermes

LLM Name	Smol Llama 220M Openhermes
Repository 🤗	https://huggingface.co/BEE-spoke-data/smol_llama-220M-openhermes
Base Model(s)	Smol Llama 220M GQA BEE-spoke-data/smol_llama-220M-GQA
Model Size	220m
Required VRAM	0.4 GB
Updated	2026-08-13
Maintainer	BEE-spoke-data
Model Type	llama
Model Files	0.4 GB
Model Architecture	LlamaForCausalLM
License	apache-2.0
Context Length	2048
Model Max Length	2048
Transformers Version	4.36.2
Tokenizer Class	LlamaTokenizer
Padding Token	</s>
Vocabulary Size	32128
Torch Data Type	bfloat16

Rank the Smol Llama 220M Openhermes 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 Smol Llama 220M Openhermes

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...l Llama 220M GQA 32K Theta Sft	32K / 0.4 GB	6	2
Smol Llama 220M GQA 32K Theta	32K / 0.4 GB	8	1
Nuevamol 220M Base	8K / 0.4 GB	6	0
Saily 220B	4K / 417 GB	96	20
Smol Llama 220M GQA	2K / 0.4 GB	326	13
Smol Llama 220M Open Instruct	2K / 0.4 GB	6	2
...mol Llama 220M GQA Fineweb Edu	2K / 0.4 GB	14	1
Smol Llama 220M Bees Internal	2K / 0.4 GB	6	1
Beecoder 220M Python	2K / 0.4 GB	12	3
Saily 220B GPTQ	4K / 105.2 GB	4	1

Note: green Score (e.g. "73.2") means that the model is better than BEE-spoke-data/smol_llama-220M-openhermes.