LLM EXPLORER
 LLM Explorer: A Curated Large Language Model Directory and Analytics
Dark Theme
  Agents   Benchmarks   LLM  List    LLM Hosting    LLM Leaderboards    Blog    Newsfeed    Advertise

Llama 3 15B Instruct Ft V2 AWQ by solidrust

 »  All LLMs  »  solidrust  »  Llama 3 15B Instruct Ft V2 AWQ   URL Share it on

  6   

Llama 3 15B Instruct Ft V2 AWQ is an open-source language model by solidrust. Features: 15b LLM, VRAM: 9.4GB, Context: 8K, Quantized, Instruction-Based, HF Score: 68.1, LLM Explorer Score: 0.15, Arc: 61.4, HellaSwag: 78.8, MMLU: 67.3, TruthfulQA: 52.3, WinoGrande: 76.3, GSM8K: 72.5.

  4-bit   Autotrain compatible   Awq Base model:elinas/llama-3-15b-... Base model:quantized:elinas/ll...   Conversational   Endpoints compatible   Instruct   Llama   Quantized   Region:us   Safetensors   Sharded   Tensorflow
Model Card on HF 🤗: https://huggingface.co/solidrust/Llama-3-15B-Instruct-ft-v2-AWQ 

Llama 3 15B Instruct Ft V2 AWQ Benchmarks

ARC: 61.35 vs 96.7 (so35)-36.6%
HellaSwag: 78.81 vs 95.3 (gpt4)-17.3%
MMLU: 67.31 vs 88.3 (so35)-23.8%
TruthfulQA: 52.33 vs 59 (gpt4)-11.3%
WinoGrande: 76.32 vs 87.5 (gpt4)-12.8%
GSM8K: 72.48 vs 96.4 (so35)-24.8%
LLME Score: 0.14898
nn.n% — How the model compares to the reference models: Anthropic Sonnet 3.5 ("so35"), GPT-4o ("gpt4o") or GPT-4 ("gpt4").
Llama 3 15B Instruct Ft V2 AWQ (solidrust/Llama-3-15B-Instruct-ft-v2-AWQ)
🌟 Advertise your project 🚀

Llama 3 15B Instruct Ft V2 AWQ Parameters and Internals

Model Type 
text-generation
Additional Notes 
AWQ is a low-bit weight quantization method for faster Transformers-based inference with 4-bit quantization.
Input Output 
Accepted Modalities:
text
LLM NameLlama 3 15B Instruct Ft V2 AWQ
Repository 🤗https://huggingface.co/solidrust/Llama-3-15B-Instruct-ft-v2-AWQ 
Base Model(s)  Llama 3 15B Instruct Ft V2   elinas/Llama-3-15B-Instruct-ft-v2
Model Size15b
Required VRAM9.4 GB
Updated2025-09-23
Maintainersolidrust
Model Typellama
Instruction-BasedYes
Model Files  5.0 GB: 1-of-2   4.4 GB: 2-of-2
AWQ QuantizationYes
Quantization Typeawq
Model ArchitectureLlamaForCausalLM
Context Length8192
Model Max Length8192
Transformers Version4.41.1
Tokenizer ClassPreTrainedTokenizerFast
Padding Token<|end_of_text|>
Vocabulary Size128256
Torch Data Typefloat16

Best Alternatives to Llama 3 15B Instruct Ft V2 AWQ

Best Alternatives
Context / RAM
Downloads
Likes
L3 Aethora 15B V2 EXL2 6.0bpw8K / 11.9 GB91
L3 Aethora 15B V2 EXL2 4.0bpw8K / 8.4 GB81
L3 Aethora 15B V2 EXL2 8.0bpw8K / 12.4 GB31
L3 Aethora 15B V2 EXL2 5.0bpw8K / 10.2 GB21
Hamanasu 15B Instruct16K / 29.4 GB4739
L3 Aethora 15B V28K / 30.1 GB2242
Meta Llama 3 15B Instruct8K / 23.9 GB41
OpenCrystal 15B L3 V38K / 30 GB1310
OpenCrystal L3 15B V2.18K / 30 GB35
OpenCrystal 15B L3 V28K / 30 GB36
Note: green Score (e.g. "73.2") means that the model is better than solidrust/Llama-3-15B-Instruct-ft-v2-AWQ.

Rank the Llama 3 15B Instruct Ft V2 AWQ Capabilities

🆘 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! 🌟

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.

Email us: info@extractum.io. Our Privacy Policy  | Terms and Conditions  | Suggest an improvement.
Our Social Media →  
Original data from HuggingFace, OpenCompass and various public git repos.
Check out Ag3ntum — our secure, self-hosted AI agent for server management.
Release v20260328a
  Support LLM Explorer