What are the hardware requirements for SAM AWQ?

SAM AWQ requires approximately 4.2 GB of VRAM and supports a context window of 32K tokens. Quantized variants may run on less VRAM; see the Quantized Models section on this page.

Who developed SAM AWQ and how large is it?

SAM AWQ is developed by TheBloke, a model with 7.2b 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 SAM AWQ?

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

SAM AWQ by TheBloke — VRAM 4.2GB, 32K context

Name: SAM AWQ
Author: TheBloke

SAM AWQ is an open-source language model by TheBloke. Features: 7.2b LLM, VRAM: 4.2GB, Context: 32K, License: apache-2.0, Quantized, LLM Explorer Score: 0.1.

4-bit Awq Base model:quantized:superagi/... Base model:superagi/sam En Mistral Quantized Region:us Safetensors

Model Card on HF 🤗: https://huggingface.co/TheBloke/SAM-AWQ

SAM AWQ Parameters and Internals

Model Type

mistral

Use Cases

Primary Use Cases:

Reasoning, task breakdown

Limitations:

Not suitable for conversations and simple Q&A; lacks moderation mechanisms

Considerations:

Not suitable for production due to lack of guardrails for toxicity and societal bias.

Additional Notes

Demonstrates improved reasoning with less but high-quality data.

Supported Languages

en (Proficient)

Training Details

Data Volume:

97% smaller than standard

Methodology:

Less but high-quality data generated using OpenSource LLMs

Hardware Used:

NVIDIA 6 x H100 SxM (80GB)

Model Architecture:

Mistral 7B

Input Output

Input Format:

[INST] {prompt} [/INST]

Accepted Modalities:

text

Performance Tips:

Temperature=0.3 for optimal performance

LLM Name	SAM AWQ
Repository 🤗	https://huggingface.co/TheBloke/SAM-AWQ
Model Name	SAM
Model Creator	SuperAGI
Base Model(s)	SAM SuperAGI/SAM
Model Size	7.2b
Required VRAM	4.2 GB
Updated	2026-08-04
Maintainer	TheBloke
Model Type	mistral
Model Files	4.2 GB
Supported Languages	en
AWQ Quantization	Yes
Quantization Type	awq
Model Architecture	MistralForCausalLM
License	apache-2.0
Context Length	32768
Model Max Length	32768
Transformers Version	4.35.2
Tokenizer Class	LlamaTokenizer
Vocabulary Size	32000
Torch Data Type	float16

Rank the SAM AWQ 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 SAM AWQ

Best Alternatives	Context / RAM	Downloads	Likes
Feedback Wizard 4bit AWQ	32K / 4.2 GB	6	0
Ryze AWQ 4bit	32K / 4.2 GB	5	0
...V3 Plot Chat Roleplay Chat AWQ	32K / 4.2 GB	7	0
...lot Engine Step Json Short AWQ	32K / 4.2 GB	5	0
MistralLite AWQ	32K / 4.2 GB	27	6
LemonadeRP 4.5.3 AWQ	32K / 4.2 GB	5	0
Functionary Small V2.4 AWQ	32K / 4.2 GB	1	1
Hc Mistral Alpaca Merged AWQ	32K / 4.2 GB	5	0
Garrulus AWQ	32K / 4.2 GB	7	2
HamSter 0.1 AWQ	32K / 4.2 GB	5	2

Note: green Score (e.g. "73.2") means that the model is better than TheBloke/SAM-AWQ.