What are the hardware requirements for Dolphin 2.9.2 Qwen2 7B AWQ?

Dolphin 2.9.2 Qwen2 7B AWQ requires approximately 5.6 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 Dolphin 2.9.2 Qwen2 7B AWQ and how large is it?

Dolphin 2.9.2 Qwen2 7B AWQ is developed by solidrust, a model with 7b 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 Dolphin 2.9.2 Qwen2 7B AWQ?

Dolphin 2.9.2 Qwen2 7B AWQ is hosted on Hugging Face and linked from this page. LLM Explorer also lists quantized variants and similar alternatives if available.

Dolphin 2.9.2 Qwen2 7B AWQ by solidrust — VRAM 5.6GB, 128K context

Name: Dolphin 2.9.2 Qwen2 7B AWQ
Author: solidrust

Dolphin 2.9.2 Qwen2 7B AWQ is an open-source language model by solidrust. Features: 7b LLM, VRAM: 5.6GB, Context: 128K, Quantized, LLM Explorer Score: 0.13.

4-bit Autotrain compatible Awq Base model:dphn/dolphin-2.9.2-... Base model:quantized:dphn/dolp... Conversational Endpoints compatible Quantized Qwen2 Region:us Safetensors Sharded Tensorflow

Model Card on HF 🤗: https://huggingface.co/solidrust/dolphin-2.9.2-qwen2-7b-AWQ

Dolphin 2.9.2 Qwen2 7B AWQ Parameters and Internals

Model Type

text-generation

Additional Notes

AWQ is an efficient, accurate and blazing-fast low-bit weight quantization method, currently supporting 4-bit quantization.

LLM Name	Dolphin 2.9.2 Qwen2 7B AWQ
Repository 🤗	https://huggingface.co/solidrust/dolphin-2.9.2-qwen2-7b-AWQ
Base Model(s)	cognitivecomputations/dolphin-2.9.2-qwen2-7b cognitivecomputations/dolphin-2.9.2-qwen2-7b
Model Size	7b
Required VRAM	5.6 GB
Updated	2026-08-04
Maintainer	solidrust
Model Type	qwen2
Model Files	4.5 GB: 1-of-2 1.1 GB: 2-of-2
AWQ Quantization	Yes
Quantization Type	awq
Model Architecture	Qwen2ForCausalLM
Context Length	131072
Model Max Length	131072
Transformers Version	4.41.1
Tokenizer Class	Qwen2Tokenizer
Padding Token	<\|endoftext\|>
Vocabulary Size	152064
Torch Data Type	float16
Errors	replace

Rank the Dolphin 2.9.2 Qwen2 7B 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 Dolphin 2.9.2 Qwen2 7B AWQ

Best Alternatives	Context / RAM	Downloads	Likes
Arcee Maestro 7B Preview AWQ	128K / 5.6 GB	12	1
Samantha Qwen2 7B AWQ	128K / 5.6 GB	10	0
CodeQwen1.5 7B Chat AWQ	64K / 5.3 GB	26	14
CodeQwen1.5 7B AWQ	64K / 5.3 GB	65	2
...nt4 Asym Bf16 Onnx Ryzen Strix	32K / GB	9	1
Qwen2.5 7B Instruct AWQ	32K / 5.6 GB	4511676	48
Qwen2.5 Coder 7B Instruct AWQ	32K / 5.7 GB	563249	1
Qwen2.5 Coder 7B Instruct AWQ	32K / 5.6 GB	316581	24
Qwen2 7B Instruct AWQ	32K / 5.6 GB	20200	23
Qwen1.5 7B Chat AWQ	32K / 5.9 GB	260	13

Note: green Score (e.g. "73.2") means that the model is better than solidrust/dolphin-2.9.2-qwen2-7b-AWQ.