What are the hardware requirements for Mixtral 8x22B Instruct V0.1 FP8 V1?

Mixtral 8x22B Instruct V0.1 FP8 V1 requires approximately 140.9 GB of VRAM and supports a context window of 64K tokens. Quantized variants may run on less VRAM; see the Quantized Models section on this page.

Who developed Mixtral 8x22B Instruct V0.1 FP8 V1 and how large is it?

Mixtral 8x22B Instruct V0.1 FP8 V1 is developed by comaniac, a model with 140.6b 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 Mixtral 8x22B Instruct V0.1 FP8 V1?

Mixtral 8x22B Instruct V0.1 FP8 V1 is hosted on Hugging Face and linked from this page. LLM Explorer also lists quantized variants and similar alternatives if available.

Mixtral 8x22B Instruct V0.1 FP8 V1 by comaniac — VRAM 140.9GB, 64K context

Name: Mixtral 8x22B Instruct V0.1 FP8 V1
Author: comaniac

Mixtral 8x22B Instruct V0.1 FP8 V1 is an open-source language model by comaniac. Features: 140.6b LLM, VRAM: 140.9GB, Context: 64K, MoE, Instruction-Based, LLM Explorer Score: 0.12.

Conversational Endpoints compatible Fp8 Instruct Mixtral Moe Region:us Safetensors Sharded Tensorflow

Model Card on HF 🤗: https://huggingface.co/comaniac/Mixtral-8x22B-Instruct-v0.1-FP8-v1

Mixtral 8x22B Instruct V0.1 FP8 V1 Parameters and Internals

Training Details

Data Sources:

Ultrachat (mgoin/ultrachat_2k)

Context Length:

8192

Model Architecture:

Weights and activations are per-tensor quantized to float8_e4m3; Quantization with AutoFP8

LLM Name	Mixtral 8x22B Instruct V0.1 FP8 V1
Repository 🤗	https://huggingface.co/comaniac/Mixtral-8x22B-Instruct-v0.1-FP8-v1
Model Size	140.6b
Required VRAM	140.9 GB
Updated	2026-05-31
Maintainer	comaniac
Model Type	mixtral
Instruction-Based	Yes
Model Files	4.9 GB: 1-of-29 4.9 GB: 2-of-29 4.9 GB: 3-of-29 4.9 GB: 4-of-29 4.9 GB: 5-of-29 4.9 GB: 6-of-29 4.9 GB: 7-of-29 4.9 GB: 8-of-29 4.9 GB: 9-of-29 4.9 GB: 10-of-29 4.9 GB: 11-of-29 4.9 GB: 12-of-29 4.9 GB: 13-of-29 4.9 GB: 14-of-29 4.9 GB: 15-of-29 4.9 GB: 16-of-29 4.9 GB: 17-of-29 4.9 GB: 18-of-29 4.9 GB: 19-of-29 4.9 GB: 20-of-29 5.0 GB: 21-of-29 5.0 GB: 22-of-29 5.0 GB: 23-of-29 4.9 GB: 24-of-29 4.9 GB: 25-of-29 4.9 GB: 26-of-29 4.9 GB: 27-of-29 4.9 GB: 28-of-29 3.4 GB: 29-of-29
Model Architecture	MixtralForCausalLM
Context Length	65536
Model Max Length	65536
Transformers Version	4.40.2
Tokenizer Class	LlamaTokenizer
Vocabulary Size	32768
Torch Data Type	bfloat16

Rank the Mixtral 8x22B Instruct V0.1 FP8 V1 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 Mixtral 8x22B Instruct V0.1 FP8 V1

Best Alternatives	Context / RAM	Downloads	Likes
Mixtral 8x22B Instruct V0.1	64K / 221.4 GB	71589	756
...ixtral 8x22B Instruct V0.1 FP8	64K / 140.9 GB	11259	0
...igHuggyD Grey WizardLM 2 8x22B	64K / 216.6 GB	21	4
...x22B Instruct V0.1 FP8 Dynamic	64K / 140.9 GB	22	0
WizardLM 2 8x22B Beige	64K / 221.4 GB	8	4
...ral 8x22B Instruct V0.1 FP8 V2	64K / 140.9 GB	5	0
Mixtral 8x22B GO Instruct V1	64K / 280.8 GB	33	2
Mixtral 8x22b Instruct Oh	64K / 221.6 GB	7	29
Mixtral 8x22B Instruct V0.1	64K / 221.4 GB	0	1
...ralxWizardLM2 8x22B SLERP V0.2	64K / 280.8 GB	8	0

Note: green Score (e.g. "73.2") means that the model is better than comaniac/Mixtral-8x22B-Instruct-v0.1-FP8-v1.