🧠
Llama 3.2 1b Instruct Q4 K M Layers model by meshllm
⭐ 39
🧠
Model

Llama 3.2 1b Instruct Q4 K M Layers

by meshllm meshllm/llama-3.2-1b-instruct-q4_k_m-layers
Free2AITools Nexus Index
39.0
S: Semantic 50

Query-time baseline · scored live at search

A: Authority 0
P: Popularity 0
R: Recency 97
Q: Quality 65
Tech Context
1 Params
4.096K Ctx
Vital Performance —
Source β†’

Task categories from upstream metadata

πŸ’¬Chat & Dialogue

Technical Constraints

Experimental / High Latency
Low FNI signal 39 FNI Score
Tiny 1B Params
4k Context
0 Downloads
8G GPU ~2GB Est. VRAM
Restricted LLAMA3.2 License
Model Information Summary
Entity Passport
Registry ID meshllm/llama-3.2-1b-instruct-q4_k_m-layers
License llama3.2
Provider huggingface
πŸ’Ύ

Compute Threshold

~2GB VRAM

Interactive
Estimate fit
β–Ό

* Static estimation for 4-Bit Quantization.

πŸ“œ

Cite this model

Academic & Research Attribution

BibTeX 
@misc{meshllm_llama_3_2_1b_instruct_q4_k_m_layers,
  author = {meshllm},
  title = {Llama 3.2 1b Instruct Q4 K M Layers Model},
  year = {2026},
  howpublished = {\url{https://huggingface.co/meshllm/Llama-3.2-1B-Instruct-Q4_K_M-layers}},
  note = {Accessed via Free2AITools.}
}
APA Style
meshllm. (2026). Llama 3.2 1b Instruct Q4 K M Layers [Model]. Free2AITools. https://huggingface.co/meshllm/Llama-3.2-1B-Instruct-Q4_K_M-layers

πŸ”¬Technical Deep Dive

Full Specifications [+]

Quick Commands

πŸ¦™ Ollama Run
ollama run llama-3.2-1b-instruct-q4_k_m-layers
πŸ€— HF Download
huggingface-cli download meshllm/llama-3.2-1b-instruct-q4_k_m-layers

βš–οΈ Free2AITools Nexus Index V2.0

Methodology How FNI works
Semantic (S) 50

Query-time baseline · scored live at search

Authority (A) 0
Popularity (P) 0
Recency (R) 97
Quality (Q) 65

πŸ’¬ Index Insight

FNI V2.0 for Llama 3.2 1b Instruct Q4 K M Layers: Authority (A:0), Popularity (P:0), Recency (R:97), Quality (Q:65). Semantic (S) is a query-time baseline scored live at search.

Free2AITools Nexus Index

Data Sources / Provenance

HuggingFace API GitHub Metadata Arxiv Citation DB Methodology
Open data Updated: Live data
---

πŸš€ What's Next?

πŸ“Š

Models in this category

Browse models in the same category

⚑

Deployment reference

Understand deployment options

Technical Deep Dive

⚠️ Incomplete Data

Some information about this model is not available. Use with Caution - Verify details from the original source before relying on this data.

View Original Source β†’

πŸ“ Limitations & Considerations

  • β€’ Benchmark scores may vary based on evaluation methodology and hardware configuration.
  • β€’ VRAM requirements are estimates; actual usage depends on quantization and batch size.
  • β€’ FNI scores are relative rankings and may change as new models are added.
πŸ€— Data Source: Hugging Face β†—
πŸ”„ Updated daily

Source summary: Based on Hugging Face metadata. Not a recommendation.

πŸ“Š FNI Methodology πŸ“š Knowledge Baseℹ️ Verify with original source

πŸ›‘οΈ Model Transparency Report

Technical metadata sourced from upstream repositories.

Open Metadata

πŸ†” Identity & Source

id
hf-model--meshllm--llama-3.2-1b-instruct-q4_k_m-layers
slug
meshllm--llama-3.2-1b-instruct-q4_k_m-layers
source
huggingface
author
meshllm
license
llama3.2
tags
mesh-llm, gguf, layer-package, skippy, distributed-inference, local-inference, openai-compatible, text-generation, base_model:unsloth/llama-3.2-1b-instruct-gguf, license:llama3.2, endpoints_compatible, region:us, imatrix, conversational

βš™οΈ Technical Specs

params billions
1
context length
4,096
pipeline tag
text-generation
vram gb
2
vram is estimated
true
vram formula
VRAM β‰ˆ (params * 0.75) + 0.8GB (KV) + 0.5GB (OS)

πŸ“Š Engagement & Metrics

downloads
0

Data indexed from public sources. Updated daily.