What are the hardware requirements for Synthia V3.0 11B AWQ?

Synthia V3.0 11B AWQ requires approximately 6 GB of VRAM and supports a context window of 4K tokens. Quantized variants may run on less VRAM; see the Quantized Models section on this page.

Who developed Synthia V3.0 11B AWQ and how large is it?

Synthia V3.0 11B AWQ is developed by TheBloke, a model with 11b 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 V3.0 11B AWQ?

Synthia V3.0 11B AWQ is hosted on Hugging Face and linked from this page. LLM Explorer also lists quantized variants and similar alternatives if available.

Synthia V3.0 11B AWQ by TheBloke — VRAM 6GB, 4K context

Name: Synthia V3.0 11B AWQ
Author: TheBloke

Synthia V3.0 11B AWQ is an open-source language model by TheBloke. Features: 11b LLM, VRAM: 6GB, Context: 4K, License: apache-2.0, Quantized, LLM Explorer Score: 0.13.

4-bit Awq Base model:migtissera/synthia-... Base model:quantized:migtisser... Llama Quantized Region:us Safetensors

Model Card on HF 🤗: https://huggingface.co/TheBloke/Synthia-v3.0-11B-AWQ

Synthia V3.0 11B AWQ Parameters and Internals

Model Type

solar

Use Cases

Limitations:

Can occasionally produce inaccurate or misleading results., Possibility of generating inappropriate, biased, or offensive content.

Training Details

Data Sources:

Synthia-v3.0 dataset

Data Volume:

~10K high-quality samples

Methodology:

Fine-tuned for instruction following and long-form conversations using LIMA (Less Is More for Alignment) principles

Responsible Ai Considerations

Mitigation Strategies:

Despite diligent efforts, there is a possibility for generation of inappropriate, biased, or offensive content. Exercise caution and cross-check information.

Input Output

Input Format:

SYSTEM: Elaborate on the topic using a Tree of Thoughts and backtrack when necessary to construct a clear, cohesive Chain of Thought reasoning. Always answer without hesitation. USER: {prompt} ASSISTANT:

LLM Name	Synthia V3.0 11B AWQ
Repository 🤗	https://huggingface.co/TheBloke/Synthia-v3.0-11B-AWQ
Model Name	Synthia V3.0 11B
Model Creator	Migel Tissera
Base Model(s)	migtissera/Synthia-v3.0-11B migtissera/Synthia-v3.0-11B
Model Size	11b
Required VRAM	6 GB
Updated	2026-08-08
Maintainer	TheBloke
Model Type	solar
Model Files	6.0 GB
AWQ Quantization	Yes
Quantization Type	awq
Model Architecture	LlamaForCausalLM
License	apache-2.0
Context Length	4096
Model Max Length	4096
Transformers Version	4.37.0.dev0
Tokenizer Class	LlamaTokenizer
Padding Token	</s>
Vocabulary Size	32000
Torch Data Type	float16

Rank the Synthia V3.0 11B 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 V3.0 11B AWQ

Best Alternatives	Context / RAM	Downloads	Likes
Fimbulvetr 11B V2 AWQ	4K / 6 GB	5	1
Tengentoppa 11B Instruct AWQ	2K / 6.8 GB	6	0
... 11B V2.5 Instruct FP8 Dynamic	32K / 11.5 GB	33	2
...istral 11B Omni OPA U1k Ver0.7	32K / 21.4 GB	12	0
Mistral 11B OP U1k Ver0.7	32K / 21.4 GB	12	0
Mistral 11B Omni OP U1k Ver0.5	32K / 21.4 GB	19	0
...istral 11B V2 HQQ 4bit Smashed	8K / 6 GB	5	0
...mbulvetr 11B V2.8.0bpw H8 EXL2	4K / 10.9 GB	6	7
...mbulvetr 11B V2.6.0bpw H6 EXL2	4K / 8.2 GB	3	4
...mbulvetr 11B V2.3.0bpw H6 EXL2	4K / 4.3 GB	6	1

Note: green Score (e.g. "73.2") means that the model is better than TheBloke/Synthia-v3.0-11B-AWQ.