Mixtral 8x7B Instruct V0.1 AWQ by ybelkada

 ยป  All LLMs  ยป  ybelkada  ยป  Mixtral 8x7B Instruct V0.1 AWQ   URL Share it on

Mixtral 8x7B Instruct V0.1 AWQ is an open-source language model by ybelkada. Features: 6.5b LLM, VRAM: 24.7GB, Context: 32K, MoE, Quantized, Instruction-Based, LLM Explorer Score: 0.11.

  4-bit   Autotrain compatible   Awq   Conversational   Endpoints compatible   Instruct   Mixtral   Moe   Quantized   Region:us   Safetensors   Sharded   Tensorflow

Mixtral 8x7B Instruct V0.1 AWQ Benchmarks

nn.n% — How the model compares to the reference models: Anthropic Sonnet 3.5 ("so35"), GPT-4o ("gpt4o") or GPT-4 ("gpt4").
Mixtral 8x7B Instruct V0.1 AWQ (ybelkada/Mixtral-8x7B-Instruct-v0.1-AWQ)
๐ŸŒŸ Advertise your project ๐Ÿš€

Mixtral 8x7B Instruct V0.1 AWQ Parameters and Internals

LLM NameMixtral 8x7B Instruct V0.1 AWQ
Repository ๐Ÿค—https://huggingface.co/ybelkada/Mixtral-8x7B-Instruct-v0.1-AWQ 
Model Size6.5b
Required VRAM24.7 GB
Updated2025-10-17
Maintainerybelkada
Model Typemixtral
Instruction-BasedYes
Model Files  5.0 GB: 1-of-5   5.0 GB: 2-of-5   5.0 GB: 3-of-5   5.0 GB: 4-of-5   4.7 GB: 5-of-5
AWQ QuantizationYes
Quantization Typeawq
Model ArchitectureMixtralForCausalLM
Context Length32768
Model Max Length32768
Transformers Version4.36.0.dev0
Tokenizer ClassLlamaTokenizer
Vocabulary Size32000
Torch Data Typefloat16

Best Alternatives to Mixtral 8x7B Instruct V0.1 AWQ

Best Alternatives
Context / RAM
Downloads
Likes
Mixtral 8x7B Instruct V0.1 AWQ32K / 24.7 GB1181458
Mixtral 8x7B Instruct V0.1 AWQ32K / 24.7 GB60
...xtral Instruct AWQ Clone Dec2332K / 24.7 GB60
...0.1 LimaRP ZLoss DARE TIES AWQ32K / 24.7 GB73
...Instruct V0.1 LimaRP ZLoss AWQ32K / 24.7 GB141
Dolphin 2.5 Mixtral 8x7b AWQ32K / 24.7 GB616
...1 Mixtral 8x7b Instruct V3 AWQ32K / 24.7 GB61
...nstruct V0.1 AQLM 2Bit 1x16 Hf32K / 13.1 GB1218
...uct V0.1 OmniQuantv1 W4a16g12832K / 24.7 GB61
Note: green Score (e.g. "73.2") means that the model is better than ybelkada/Mixtral-8x7B-Instruct-v0.1-AWQ.

Rank the Mixtral 8x7B Instruct V0.1 AWQ Capabilities

๐Ÿ†˜ Have you tried this model? Rate its performance. This feedback would greatly assist ML community in identifying the most suitable model for their needs. Your contribution really does make a difference! ๐ŸŒŸ

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  

What open-source LLMs or SLMs are you in search of? 52721 in total.

Our Social Media →  
Original data from HuggingFace, OpenCompass and various public git repos.
Check out Ag3ntum โ€” our secure, self-hosted AI agent for server management.
Release v20260328a