Skip to content
AI Atlas
ArtifactquantizationFP8Open weightsof step-3.5-flash

stepfun-ai/Step-3.5-Flash-FP8

published by StepFunhuggingface.co/stepfun-ai/Step-3.5-Flash-FP8

This is a quantization of step-3.5-flash, not an independent model. Parameters, benchmarks, prices and lineage are recorded on the canonical model. Open step-3.5-flash

Updated 2 h ago · first seen 12 Sept 2026

artifact_01M2AS5MA7QWXXZ8MM11EVMTJM

File size
Format
Downloads
Published

Artifact facts

Quantization format

Source:Hugging Face Hub (public pages, model cards, papers)T2observed 2 h agomedium

Weights dtype

Source:Hugging Face Hub (public pages, model cards, papers)T2observed 2 h agomedium

File size

Source:Hugging Face Hub (public pages, model cards, papers)T2observed 2 h agomedium

Downloads

Source:Hugging Face Hub (public pages, model cards, papers)T2observed 2 h agomedium

Likes

Source:Hugging Face Hub (public pages, model cards, papers)T2observed 2 h agomedium

Hugging Face repo

Source:Hugging Face Hub (public pages, model cards, papers)T2observed 3 h agomedium

Base model

Source:Hugging Face Hub (public pages, model cards, papers)T2observed 2 h agomedium

Pipeline tag

Source:Hugging Face Hub (public pages, model cards, papers)T2observed 3 h agomedium

Library name

Source:Hugging Face Hub (public pages, model cards, papers)T2observed 2 h agomedium

Access

Source:Hugging Face Hub (public pages, model cards, papers)T2observed 3 h agomedium

License

Source:Hugging Face Hub (public pages, model cards, papers)T2observed 2 h agomedium

Release date

Source:Hugging Face Hub (public pages, model cards, papers)T2observed 2 h agomedium

Last modified

Source:Hugging Face Hub (public pages, model cards, papers)T2observed 3 h agomedium

Tags

Source:Hugging Face Hub (public pages, model cards, papers)T2observed 2 h agomedium

Hardware fit (this packaging)

Estimated

15 of 37 device × quantization combinations fit.

Run locally: your machine →
Estimated hardware fit
HardwareQuantizationDevice memoryEst. memoryFits
Apple M3 Ultra4bit115.2 GB est.Yes
Mac Studio (Apple M5 Ultra)4bit115.2 GB est.Yes
Apple M2 Ultra4bit115.2 GB est.Yes
Apple M1 Ultra4bit115.2 GB est.Yes
Apple M3 Max4bit115.2 GB est.Yes
Apple M4 Max4bit115.2 GB est.Yes
Mac Studio (Apple M5 Max)4bit115.2 GB est.Yes
MacBook Pro (Apple M5 Max)4bit115.2 GB est.Yes
NVIDIA DGX Spark4bit128 GB115.2 GB est.Yes
NVIDIA H2004bit141 GB115.2 GB est.Yes
NVIDIA H200 NVL4bit141 GB115.2 GB est.Yes
NVIDIA B2004bit180 GB115.2 GB est.Yes
AMD Instinct MI300X4bit192 GB115.2 GB est.Yes
AMD Instinct MI325X4bit256 GB115.2 GB est.Yes
NVIDIA DGX B2004bit1,440 GB115.2 GB est.Yes
Apple M2 Max4bit115.2 GB est.No
Apple M1 Max4bit115.2 GB est.No
Apple M4 Pro4bit115.2 GB est.No
Mac mini (Apple M5 Pro)4bit115.2 GB est.No
MacBook Pro (Apple M5 Pro)4bit115.2 GB est.No
Apple M3 Pro4bit115.2 GB est.No
Apple M1 Pro4bit115.2 GB est.No
Apple M2 Pro4bit115.2 GB est.No
Apple M44bit115.2 GB est.No
iMac (Apple M4)4bit115.2 GB est.No
Mac mini (Apple M6)4bit115.2 GB est.No
MacBook Air (Apple M5)4bit115.2 GB est.No
MacBook Pro (Apple M5)4bit115.2 GB est.No
Apple M24bit115.2 GB est.No
Apple M34bit115.2 GB est.No
Apple M14bit115.2 GB est.No
NVIDIA GeForce RTX 30904bit24 GB115.2 GB est.No
NVIDIA GeForce RTX 40904bit24 GB115.2 GB est.No
NVIDIA GeForce RTX 50904bit32 GB115.2 GB est.No
NVIDIA A100 80GB4bit80 GB115.2 GB est.No
NVIDIA H100 SXM4bit80 GB115.2 GB est.No
NVIDIA H100 NVL4bit94 GB115.2 GB est.No
Assumptions (7)
  • Estimated, not measured: weights = parameters × bytes/param × 1.15 runtime overhead (or the observed artifact file size when one is recorded).
  • bytes/param: 4bit = 0.5, 8bit = 1.0, fp16 = 2.0 (uniform quantization, no per-layer exceptions).
  • KV cache: 2 × layers × kv_heads × head_dim × 2 bytes × context × batch when the architecture is known; otherwise 0.5 GB per 8 192 tokens (× batch), 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).
  • Multi-GPU: device memories are summed; interconnect bandwidth, tensor-parallel replication and pipeline bubbles are not modelled.

Timeline

Full timeline →

Provenance

Attributed facts

28

Source tiers

T228

Freshest observation

2 h ago

Conflicts

None

Source documents
SourceDocumentTypeTierLast observedSnapshots
Hugging Face Hub (public pages, model cards, papers)huggingface.co/stepfun-ai/Step-3.5-Flash-FP8 model_pageT2· Quality secondary2 h ago1
Hugging Face Hub (public pages, model cards, papers)huggingface.co/models?author=stepfun-ai&p=0&sort=downloads listingT2· Quality secondary3 h ago2

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