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Qwen3.5 9b Fp8 model by Hyper Ai
⭐ 54.9
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Model

Qwen3.5 9b Fp8

by Hyper Ai hyper-ai/qwen3.5-9b-fp8
Free2AITools Nexus Index
54.9
S: Semantic 50

Query-time baseline · scored live at search

A: Authority 33
P: Popularity 51
R: Recency 98
Q: Quality 65
Tech Context
9.65 Params
32.768K Ctx
Vital Performance
31.3K DL / 30D
Source β†’
Low FNI signal 54.9 FNI Score
9.65B Params
32k Context
31.3K Downloads
24G GPU ~10GB Est. VRAM
Dense QWEN3_5FORCONDITIONALGENERATION Architecture
Commercial APACHE License
Model Information Summary
Entity Passport
Registry ID hyper-ai/qwen3.5-9b-fp8
License Apache-2.0
Provider huggingface
πŸ’Ύ

Compute Threshold

~9.7GB VRAM

Interactive
Estimate fit
β–Ό

* Static estimation for 4-Bit Quantization.

πŸ“œ

Cite this model

Academic & Research Attribution

BibTeX 
@misc{hyper_ai_qwen3_5_9b_fp8,
  author = {Hyper Ai},
  title = {Qwen3.5 9b Fp8 Model},
  year = {2026},
  howpublished = {\url{https://huggingface.co/Hyper-AI/Qwen3.5-9B-fp8}},
  note = {Accessed via Free2AITools.}
}
APA Style
Hyper Ai. (2026). Qwen3.5 9b Fp8 [Model]. Free2AITools. https://huggingface.co/Hyper-AI/Qwen3.5-9B-fp8

πŸ”¬Technical Deep Dive

Full Specifications [+]

Quick Commands

πŸ¦™ Ollama Run
ollama run qwen3.5-9b-fp8
πŸ€— HF Download
huggingface-cli download hyper-ai/qwen3.5-9b-fp8
πŸ“¦ Install Lib
pip install -U transformers

βš–οΈ Free2AITools Nexus Index V2.0

Methodology How FNI works
Semantic (S) 50

Query-time baseline · scored live at search

Authority (A) 33
Popularity (P) 51
Recency (R) 98
Quality (Q) 65

πŸ’¬ Index Insight

FNI V2.0 for Qwen3.5 9b Fp8: Authority (A:33), Popularity (P:51), Recency (R:98), 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
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Deployment reference

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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.
  • ⚠ License Unknown: Verify licensing terms before commercial use.

Social Proof

HuggingFace Hub
31.3KDownloads
Hub Discussions
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--hyper-ai--qwen3.5-9b-fp8
slug
hyper-ai--qwen3.5-9b-fp8
source
huggingface
author
Hyper Ai
license
Apache-2.0
tags
transformers, safetensors, qwen3_5, image-text-to-text, vlm, fp8, quant, lightvl, qwen3.5, conversational, base_model:qwen/qwen3.5-9b-base, base_model:quantized:qwen/qwen3.5-9b-base, license:apache-2.0, endpoints_compatible, compressed-tensors, region:us

βš™οΈ Technical Specs

architecture
Qwen3_5ForConditionalGeneration
params billions
9.65
context length
32,768
pipeline tag
image-text-to-text
vram gb
9.7
vram is estimated
true
vram formula
VRAM β‰ˆ (params * 0.75) + 2GB (KV) + 0.5GB (OS)

πŸ“Š Engagement & Metrics

downloads
31,342
stars
null
forks
null

Data indexed from public sources. Updated daily.