🧠
Model

Harvey 9b Gguf

by mradermacher mradermacher/harvey-9b-gguf
Free2AITools Nexus Index
36.3
S: Semantic 50

Query-time baseline · scored live at search

A: Authority 33
P: Popularity 20
R: Recency 75
Q: Quality 30
Tech Context
9 Params
4.096K Ctx
Vital Performance
500 DL / 30D

Technical Constraints

Experimental / High Latency
Low FNI signal 36.3 FNI Score
9B Params
4k Context
500 Downloads
24G GPU ~9GB Est. VRAM
Commercial APACHE License
Model Information Summary
Entity Passport
Registry ID mradermacher/harvey-9b-gguf
License Apache-2.0
Provider huggingface
πŸ’Ύ

Compute Threshold

~8.1GB VRAM

Interactive
Estimate fit
β–Ό

* Static estimation for 4-Bit Quantization.

πŸ“œ

Cite this model

Academic & Research Attribution

BibTeX
@misc{mradermacher_harvey_9b_gguf,
  author = {mradermacher},
  title = {Harvey 9b Gguf Model},
  year = {2026},
  howpublished = {\url{https://huggingface.co/mradermacher/Harvey-9B-GGUF}},
  note = {Accessed via Free2AITools.}
}
APA Style
mradermacher. (2026). Harvey 9b Gguf [Model]. Free2AITools. https://huggingface.co/mradermacher/Harvey-9B-GGUF

πŸ”¬Technical Deep Dive

Full Specifications [+]

Quick Commands

πŸ¦™ Ollama Run
ollama run harvey-9b-gguf
πŸ€— HF Download
huggingface-cli download mradermacher/harvey-9b-gguf
πŸ“¦ Install Lib
pip install -U transformers

βš–οΈ Free2AITools Nexus Index V2.0

Semantic (S) 50

Query-time baseline · scored live at search

Authority (A) 33
Popularity (P) 20
Recency (R) 75
Quality (Q) 30

πŸ’¬ Index Insight

FNI V2.0 for Harvey 9b Gguf: Authority (A:33), Popularity (P:20), Recency (R:75), Quality (Q:30). Semantic (S) is a query-time baseline scored live at search.

Free2AITools Nexus Index

Data Sources / Provenance

Open data Updated: Live data
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πŸš€ What's Next?

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.

Social Proof

HuggingFace Hub
500Downloads
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--mradermacher--harvey-9b-gguf
slug
mradermacher--harvey-9b-gguf
source
huggingface
author
mradermacher
license
Apache-2.0
tags
transformers, gguf, legal, el-salvador, jurisprudence, en, es, base_model:aquiles-ai/harvey-9b, base_model:quantized:aquiles-ai/harvey-9b, license:apache-2.0, endpoints_compatible, region:us, conversational

βš™οΈ Technical Specs

params billions
9
context length
4,096
vram gb
8.1
vram is estimated
true
vram formula
VRAM β‰ˆ (params * 0.75) + 0.8GB (KV) + 0.5GB (OS)

πŸ“Š Engagement & Metrics

downloads
500
stars
0
forks
0

Data indexed from public sources. Updated daily.