What are the hardware requirements for Llama Spark?

Llama Spark requires approximately 32.1 GB of VRAM and supports a context window of 128K tokens. Quantized variants may run on less VRAM; see the Quantized Models section on this page.

Who developed Llama Spark and how large is it?

Llama Spark is developed by arcee-ai, a model with 8b 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 Llama Spark?

Llama Spark is hosted on Hugging Face and linked from this page. LLM Explorer also lists quantized variants and similar alternatives if available.

Llama Spark by arcee-ai — VRAM 32.1GB, 128K context

Name: Llama Spark
Author: arcee-ai

Llama Spark is an open-source language model by arcee-ai. Features: 8b LLM, VRAM: 32.1GB, Context: 128K, License: llama3, LLM Explorer Score: 0.21.

Conversational Endpoints compatible Llama Region:us Safetensors Sharded Tensorflow

Model Card on HF 🤗: https://huggingface.co/arcee-ai/Llama-Spark

Llama Spark Parameters and Internals

Model Type

Conversational AI

Use Cases

Areas:

Conversational AI

Applications:

chatbots, virtual assistants, dialogue systems

Additional Notes

Successor to the original Arcee-Spark, improved to maintain leadership in the 6-9B parameter range.

Training Details

Data Sources:

Tome Dataset

Methodology:

Fine-tuned and merged with Llama-3.1-8B-Instruct

LLM Name	Llama Spark
Repository 🤗	https://huggingface.co/arcee-ai/Llama-Spark
Model Size	8b
Required VRAM	32.1 GB
Updated	2026-07-31
Maintainer	arcee-ai
Model Type	llama
Model Files	4.9 GB: 1-of-7 4.8 GB: 2-of-7 5.0 GB: 3-of-7 5.0 GB: 4-of-7 4.8 GB: 5-of-7 5.0 GB: 6-of-7 2.6 GB: 7-of-7
Model Architecture	LlamaForCausalLM
License	llama3
Context Length	131072
Model Max Length	131072
Transformers Version	4.43.1
Tokenizer Class	PreTrainedTokenizerFast
Padding Token	<\|end_of_text\|>
Vocabulary Size	128256
Torch Data Type	float32

Rank the Llama Spark 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 Llama Spark

Best Alternatives	Context / RAM	Downloads	Likes
...otron 8B UltraLong 4M Instruct	4192K / 32.1 GB	1135	125
UltraLong Thinking	4192K / 16.1 GB	2	3
...a 3.1 8B UltraLong 4M Instruct	4192K / 32.1 GB	176	24
...a 3.1 8B UltraLong 2M Instruct	2096K / 32.1 GB	875	9
...otron 8B UltraLong 2M Instruct	2096K / 32.1 GB	124	18
Cthulhu 8B V1.4	1048K / 16.1 GB	10	10
...raLong 1M Instruct Abliterated	1048K / 32.1 GB	4	9
...a 3.1 8B UltraLong 1M Instruct	1048K / 32.1 GB	1387	29
...otron 8B UltraLong 1M Instruct	1048K / 32.1 GB	702	59
...xis Bookwriter Llama3.1 8B Sft	1048K / 16.1 GB	25	4

Note: green Score (e.g. "73.2") means that the model is better than arcee-ai/Llama-Spark.