What are the hardware requirements for Dolphin 2.7 Mixtral 8x7b AWQ?

Dolphin 2.7 Mixtral 8x7b AWQ requires approximately 24.7 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 Dolphin 2.7 Mixtral 8x7b AWQ and how large is it?

Dolphin 2.7 Mixtral 8x7b AWQ is developed by TheBloke, a model with 46.7b 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 2.7 Mixtral 8x7b AWQ?

Dolphin 2.7 Mixtral 8x7b AWQ is hosted on Hugging Face and linked from this page. LLM Explorer also lists quantized variants and similar alternatives if available.

Dolphin 2.7 Mixtral 8x7b AWQ by TheBloke — VRAM 24.7GB, 32K context

Name: Dolphin 2.7 Mixtral 8x7b AWQ
Author: TheBloke

Dolphin 2.7 Mixtral 8x7b AWQ is an open-source language model by TheBloke. Features: 46.7b LLM, VRAM: 24.7GB, Context: 32K, License: apache-2.0, MoE, Quantized, Instruction-Based, LLM Explorer Score: 0.12.

4-bit Awq Base model:dphn/dolphin-2.7-mi... Base model:quantized:dphn/dolp... Conversational Dataset:ehartford/dolphin Dataset:ehartford/dolphin-code... Dataset:ise-uiuc/magicoder-evo... Dataset:ise-uiuc/magicoder-oss... Dataset:jondurbin/airoboros-2.... Dataset:ldjnr/capybara Dataset:teknium/openhermes Deploy:azure En Instruct Mixtral Moe Quantized Region:us Safetensors Sharded Tensorflow

Model Card on HF 🤗: https://huggingface.co/TheBloke/dolphin-2.7-mixtral-8x7b-AWQ

Dolphin 2.7 Mixtral 8x7b AWQ Parameters and Internals

Model Type

mixtral

Additional Notes

This model, being uncensored and highly compliant, requires user-advised alignment handling before deployment as a service. It has undergone retraining with specific fixes aiming to improve performance.

Training Details

Data Sources:

ehartford/dolphin, jondurbin/airoboros-2.2.1, ehartford/dolphin-coder, teknium/openhermes, ise-uiuc/Magicoder-OSS-Instruct-75K, ise-uiuc/Magicoder-Evol-Instruct-110K, LDJnr/Capybara

Context Length:

32768

Hardware Used:

4x A100s

Model Architecture:

Mixtral-8x7b

LLM Name	Dolphin 2.7 Mixtral 8x7b AWQ
Repository 🤗	https://huggingface.co/TheBloke/dolphin-2.7-mixtral-8x7b-AWQ
Model Name	Dolphin 2.7 Mixtral 8X7B
Model Creator	Cognitive Computations
Base Model(s)	cognitivecomputations/dolphin-2.7-mixtral-8x7b cognitivecomputations/dolphin-2.7-mixtral-8x7b
Model Size	46.7b
Required VRAM	24.7 GB
Updated	2026-07-31
Maintainer	TheBloke
Model Type	mixtral
Instruction-Based	Yes
Model Files	10.0 GB: 1-of-3 10.0 GB: 2-of-3 4.7 GB: 3-of-3
Supported Languages	en
AWQ Quantization	Yes
Quantization Type	awq
Model Architecture	MixtralForCausalLM
License	apache-2.0
Context Length	32768
Model Max Length	32768
Transformers Version	4.37.0.dev0
Tokenizer Class	LlamaTokenizer
Padding Token	</s>
Vocabulary Size	32002
Torch Data Type	float16

Rank the Dolphin 2.7 Mixtral 8x7b 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 2.7 Mixtral 8x7b AWQ

Best Alternatives	Context / RAM	Downloads	Likes
Mixtral 8x7B Instruct V0.1 AWQ	32K / 24.7 GB	5	0
Mixtral Instruct AWQ	32K / 24.7 GB	2333	43
Mixtral 8x7B Instruct V0.1 AWQ	32K / 24.7 GB	1045	59
Mixtral 8x7B Instruct V0.1 AWQ	32K / 24.7 GB	1248	16
...xtral Instruct AWQ Clone Dec23	32K / 24.7 GB	9	0
...ixtral Instruct 8x7b Zloss AWQ	32K / 24.7 GB	0	2
...0.1 LimaRP ZLoss DARE TIES AWQ	32K / 24.7 GB	3	3
...Instruct V0.1 LimaRP ZLoss AWQ	32K / 24.7 GB	8	1
...utLM Mixtral 8x7B Instruct AWQ	32K / 24.7 GB	61	2
Dolphin 2.6 Mixtral 8x7b AWQ	32K / 24.7 GB	32	12

Note: green Score (e.g. "73.2") means that the model is better than TheBloke/dolphin-2.7-mixtral-8x7b-AWQ.