What are the hardware requirements for Prem 1B Chat?

Prem 1B Chat requires approximately 2.2 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 Prem 1B Chat and how large is it?

Prem 1B Chat is developed by premai-io, a model with 1b 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 Prem 1B Chat?

Prem 1B Chat is hosted on Hugging Face and linked from this page. LLM Explorer also lists quantized variants and similar alternatives if available.

Prem 1B Chat by premai-io — VRAM 2.2GB, 8K context

Name: Prem 1B Chat
Author: premai-io

Prem 1B Chat is an open-source language model by premai-io. Features: 1b LLM, VRAM: 2.2GB, Context: 8K, License: apache-2.0, Instruction-Based, Merged, LLM Explorer Score: 0.12.

Merged Model Autotrain compatible Conversational Dataset:alexredna/oasst2 dpo p... Dataset:argilla/ultrafeedback-... Dataset:cerebras/slimpajama-62... Dataset:cognitivecomputations/... Dataset:hkust-nlp/deita-10k-v0 Dataset:huggingfaceh4/capybara Dataset:huggingfaceh4/ultracha... Dataset:intel/orca dpo pairs Dataset:meta-math/metamathqa Dataset:open-orca/slimorca-ded... Endpoints compatible Instruct Llama Region:us Safetensors

Model Card on HF 🤗: https://huggingface.co/premai-io/prem-1B-chat

Prem 1B Chat Parameters and Internals

Model Type

SLM, RAG

Use Cases

Areas:

commercial applications, research

Primary Use Cases:

conversational interactions, natural language generation

Limitations:

must not be used in violation of applicable laws

Considerations:

Developers must comply with the Prem-1B Community License and the Acceptable Use Policy.

Supported Languages

English (Native)

Training Details

Data Sources:

cerebras/SlimPajama-627B, HuggingFaceH4/ultrachat_200k, hkust-nlp/deita-10k-v0, Open-Orca/SlimOrca-Dedup, cognitivecomputations/WizardLM_evol_instruct_V2_196k_unfiltered_merged_split, HuggingFaceH4/capybara, meta-math/MetaMathQA, argilla/ultrafeedback-binarized-preferences-cleaned, Intel/orca_dpo_pairs, alexredna/oasst2_dpo_pairs

Context Length:

8192

Hardware Used:

16-H100 GPUs

Model Architecture:

Llama

Input Output

Accepted Modalities:

text

LLM Name	Prem 1B Chat
Repository 🤗	https://huggingface.co/premai-io/prem-1B-chat
Merged Model	Yes
Model Size	1b
Required VRAM	2.2 GB
Updated	2025-09-01
Maintainer	premai-io
Model Type	llama
Instruction-Based	Yes
Model Files	2.2 GB
Model Architecture	LlamaForCausalLM
License	apache-2.0
Context Length	8192
Model Max Length	8192
Transformers Version	4.38.2
Tokenizer Class	LlamaTokenizer
Padding Token	[PAD]
Vocabulary Size	32004
Torch Data Type	bfloat16

Rank the Prem 1B Chat 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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...1B Claude Opus Fable5 Thinking	128K / 2.2 GB	6165	166
Llama 3.2 1B Instruct	128K / 2.5 GB	10114634	1549
LlaMa3.2 1B Instruct	128K / 4.9 GB	14	0
Llama 3.2 1B Instruct Bf16	128K / 2.5 GB	510	5
Llama 3.2 1B Instruct	128K / 2.5 GB	20	0
Llama3.2 1B Manumit V1	128K / 2.5 GB	132	0
...Claude Opus Fable5 V2 Thinking	128K / 2.2 GB	288	4
Llama 3.2 Mavrick.Spark 1B	128K / 2.5 GB	258	2
Type O1 Mini Instruct	128K / 2.5 GB	232	0

Note: green Score (e.g. "73.2") means that the model is better than premai-io/prem-1B-chat.