What are the hardware requirements for Synthia 70B AWQ?

Synthia 70B AWQ requires approximately 36.6 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 Synthia 70B AWQ and how large is it?

Synthia 70B AWQ is developed by TheBloke, a model with 70b 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 Synthia 70B AWQ?

Synthia 70B AWQ is hosted on Hugging Face and linked from this page. LLM Explorer also lists quantized variants and similar alternatives if available.

Synthia 70B AWQ by TheBloke — VRAM 36.6GB, 2K context

Name: Synthia 70B AWQ
Author: TheBloke

Synthia 70B AWQ is an open-source language model by TheBloke. Features: 70b LLM, VRAM: 36.6GB, Context: 2K, License: llama2, Quantized, LLM Explorer Score: 0.09.

Arxiv:2302.13971 Arxiv:2306.02707 4-bit Awq Base model:migtissera/synthia-... Base model:quantized:migtisser... En Fp16 Llama Quantized Region:us Safetensors Sharded Tensorflow

Model Card on HF 🤗: https://huggingface.co/TheBloke/Synthia-70B-AWQ

Synthia 70B AWQ Parameters and Internals

Model Type

llama

Use Cases

Primary Use Cases:

text generation, instruction following, long-form conversations

Limitations:

While this model aims for accuracy, it can occasionally produce inaccurate or misleading results., Possibility for the generation of inappropriate, biased, or offensive content.

Additional Notes

This is an uncensored model.

Input Output

Input Format:

SYSTEM: {system_message} USER: {prompt} ASSISTANT:

Accepted Modalities:

text

Output Format:

text

LLM Name	Synthia 70B AWQ
Repository 🤗	https://huggingface.co/TheBloke/Synthia-70B-AWQ
Model Name	Synthia 70B
Model Creator	Migel Tissera
Base Model(s)	Synthia 70B migtissera/Synthia-70B
Model Size	70b
Required VRAM	36.6 GB
Updated	2026-07-16
Maintainer	TheBloke
Model Type	llama
Model Files	9.9 GB: 1-of-4 9.9 GB: 2-of-4 9.9 GB: 3-of-4 6.9 GB: 4-of-4
Supported Languages	en
AWQ Quantization	Yes
Quantization Type	fp16\|awq
Model Architecture	LlamaForCausalLM
License	llama2
Context Length	2048
Model Max Length	2048
Transformers Version	4.32.0.dev0
Tokenizer Class	LlamaTokenizer
Beginning of Sentence Token	<s>
End of Sentence Token	</s>
Unk Token	<unk>
Vocabulary Size	32000
Torch Data Type	float16

Rank the Synthia 70B 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 Synthia 70B AWQ

Best Alternatives	Context / RAM	Downloads	Likes
...0B Instruct Gradient 1048K AWQ	1024K / 39.9 GB	5	1
...70B Instruct Gradient 262K AWQ	256K / 39.9 GB	5	0
Llama 3.3 70B Instruct AWQ	128K / 39.9 GB	262002	46
...lama 3.3 70B Instruct AWQ INT4	128K / 39.9 GB	82744	30
Llama 3.3 70B Instruct AWQ	128K / 39.9 GB	16090	12
... SauerkrautLM 70B Instruct AWQ	128K / 39.9 GB	5	5
MultiVerse 70B AWQ	32K / 41.3 GB	70	2
Opus V1.2 70B AWQ	32K / 36.7 GB	9	1
QuartetAnemoi 70B T0.0001 AWQ	31K / 36.7 GB	3	1
Senku 70B AWQ 4bit GEMM	31K / 36.7 GB	2	1

Note: green Score (e.g. "73.2") means that the model is better than TheBloke/Synthia-70B-AWQ.