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tencent/Hy3-FP8

Tencenthuggingface.co/tencent/Hy3-FP8

Open in Graph
data quality53

Updated 5 h ago · first seen 11 Sept 2026

model_01M2950AZ8MJHJZQK7YR3DF0YE

Overview

Identity

Identity block not returned by the API for this entity.

Openness

Openness not classified yet — no sourced evidence to place this model in the ontology.

Key facts

Release date

Source:Hugging Face Hub (public pages, model cards, papers)T2observed 10 h agomedium

Model card
huggingface.co/tencent/Hy3-FP8

Source:Hugging Face Hub (public pages, model cards, papers)T2observed 11 h agomedium

Architecture

Architecture

Source:Hugging Face Hub (public pages, model cards, papers)T2observed 10 h agomedium

Model type

Source:Hugging Face Hub (public pages, model cards, papers)T2observed 10 h agomedium

Parameters

Source:Hugging Face Hub (public pages, model cards, papers)T2observed 11 h agomedium

Weights dtype

Source:Hugging Face Hub (public pages, model cards, papers)T2observed 10 h agomedium

File size

Source:Hugging Face Hub (public pages, model cards, papers)T2observed 10 h agomedium

Library name

Source:Hugging Face Hub (public pages, model cards, papers)T2observed 10 h agomedium

Pipeline tag

Source:Hugging Face Hub (public pages, model cards, papers)T2observed 11 h agomedium

Hugging Face repo

Source:Hugging Face Hub (public pages, model cards, papers)T2observed 11 h agomedium

Hardware fit37

Estimated

7 of 37 device × quantization combinations fit.

Run locally: your machine →
Estimated hardware fit
HardwareQuantizationDevice memoryEst. memoryFits
Apple M3 Ultra4bit—172.3 GB est.Yes
Mac Studio (Apple M5 Ultra)4bit—172.3 GB est.Yes
Apple M2 Ultra4bit—172.3 GB est.Yes
NVIDIA B2004bit180 GB172.3 GB est.Yes
AMD Instinct MI300X4bit192 GB172.3 GB est.Yes
AMD Instinct MI325X4bit256 GB172.3 GB est.Yes
NVIDIA DGX B2004bit1,440 GB172.3 GB est.Yes
Apple M1 Ultra4bit—172.3 GB est.No
Apple M3 Max4bit—172.3 GB est.No
Apple M4 Max4bit—172.3 GB est.No
Mac Studio (Apple M5 Max)4bit—172.3 GB est.No
MacBook Pro (Apple M5 Max)4bit—172.3 GB est.No
Apple M2 Max4bit—172.3 GB est.No
Apple M1 Max4bit—172.3 GB est.No
Apple M4 Pro4bit—172.3 GB est.No
Mac mini (Apple M5 Pro)4bit—172.3 GB est.No
MacBook Pro (Apple M5 Pro)4bit—172.3 GB est.No
Apple M3 Pro4bit—172.3 GB est.No
Apple M1 Pro4bit—172.3 GB est.No
Apple M2 Pro4bit—172.3 GB est.No
Apple M44bit—172.3 GB est.No
iMac (Apple M4)4bit—172.3 GB est.No
Mac mini (Apple M6)4bit—172.3 GB est.No
MacBook Air (Apple M5)4bit—172.3 GB est.No
MacBook Pro (Apple M5)4bit—172.3 GB est.No
Apple M24bit—172.3 GB est.No
Apple M34bit—172.3 GB est.No
Apple M14bit—172.3 GB est.No
NVIDIA GeForce RTX 30904bit24 GB172.3 GB est.No
NVIDIA GeForce RTX 40904bit24 GB172.3 GB est.No
NVIDIA GeForce RTX 50904bit32 GB172.3 GB est.No
NVIDIA A100 80GB4bit80 GB172.3 GB est.No
NVIDIA H100 SXM4bit80 GB172.3 GB est.No
NVIDIA H100 NVL4bit94 GB172.3 GB est.No
NVIDIA DGX Spark4bit128 GB172.3 GB est.No
NVIDIA H2004bit141 GB172.3 GB est.No
NVIDIA H200 NVL4bit141 GB172.3 GB est.No
Assumptions (6)
  • Estimated, not measured: weights = parameters × bytes/param × 1.15 runtime overhead.
  • bytes/param: 4bit = 0.5, 8bit = 1.0, fp16 = 2.0 (uniform quantization, no per-layer exceptions).
  • KV cache approximated at 0.5 GB per 8 192 tokens of context, independent of architecture (GQA/MLA models need less).
  • A model 'fits' when the estimate is at most the device memory minus 2 GB reserved for the OS and framework.
  • Mixture-of-experts models are estimated on total parameters (all experts must be resident); active parameters are ignored.
  • Device memory uses the largest configuration when several are listed (e.g. Apple silicon tiers).

Timeline1

Full timeline →

Change history

Temporal, append-only claims: a new observation closes the previous claim instead of overwriting it. Rewind the record with the as-of picker.
1 claims · 1 propertiesShow all properties

Is quantizedis_quantized1

Claim history for Is quantized
ValueValid from → toStatusSourceConfidenceExtractor
Yes → currentcurrentHugging Face Hub (public pages, model cards, papers)T2mediumdeterministic

Claims are temporal and append-only: a new observation closes the previous claim (valid_to) instead of overwriting it. Conflicting claims from different sources are kept side by side and flagged — never averaged. Methodology →

Provenance

Attributed facts

20

Source tiers

T220

Freshest observation

5 h ago

Conflicts

None

Source documents 3

Source documents
SourceDocumentTypeTierLast observedSnapshots
Hugging Face Hub (public pages, model cards, papers)huggingface.co/tencent/Hy3-FP8/raw/main/README.md model_cardT2· Quality secondary4 h ago1
Hugging Face Hub (public pages, model cards, papers)huggingface.co/tencent/Hy3-FP8 model_pageT2· Quality secondary5 h ago5
Hugging Face Hub (public pages, model cards, papers)huggingface.co/models?author=tencent&p=0&sort=downloads listingT2· Quality secondary5 h ago6

Tier 1 = official/primary, 2 = quality secondary, 3 = community, 4 = unverified. Every snapshot is archived; see all sources and the methodology.

Data quality (53/100) measures how well AI Atlas knows this entity — completeness, primary-source ratio, freshness, conflicts — never how good the model is. Methodology →