Model reference · open weights

ARACHNE-FOUNDATION

Available as managed deployment Video MagistrTheOne · community Text→video 1 variants 596 dl/mo

ARACHNE-FOUNDATION is an open-weight video model from MagistrTheOne. AxForge deploys and operates it for you on dedicated EU-owned hardware — with the licence handled where one is required.

Available as managed deployment — configured and operated for you on dedicated EU hardware, quoted per deployment.

What it is

Released byMagistrTheOne
TypeVideo models
TaskText→video
Parameters (lead)50.3B
Runs withdiffusers
Released2026-05-27
Popularity596 downloads / month
LicenceOpen weights

About

What ARACHNE-FOUNDATION is

Foundation-scale video diffusion backbone engineered for the next generation of realtime AI systems.

ARACHNE-FOUNDATION-50B is an experimental large-scale DiT foundation checkpoint developed by NULLXES as part of the ARACHNE runtime ecosystem.

This repository represents an early foundation transition stage of the ARACHNE lineage: from operational realtime avatar/video systems toward a sovereign large-scale multimodal video backbone optimized for realtime inference, streaming generation, identity stability, and future native audio-video architectures.


Read the full model card

Overview

ARACHNE-FOUNDATION-50B is currently a:

  • depth-expanded initialization checkpoint
  • architectural research foundation
  • pretraining-ready DiT topology
  • runtime-compatible experimental backbone

This release is NOT a fully trained production model.

The checkpoint was surgically expanded from:

using internal topology scaling procedures and initialization surgery.


Current Status

ComponentStatus
Depth expansion✅ Complete
Diffusers compatibility✅ Complete
Safetensors export✅ Complete
Smoke forward validation✅ Complete
Runtime compatibility✅ Complete
Full pretraining⏳ Pending
Native audio generation⏳ Planned
Benchmark evaluation⏳ Pending
Production deployment❌ Not ready

Architecture

PropertyValue
Model TypeDiffusion Transformer (DiT)
Scale~50B parameters
Depth178 transformer blocks
FormatDiffusers
WeightsSafetensors
Runtime TargetARACHNE Runtime Stack
Intended DirectionRealtime multimodal generation

Design Philosophy

Unlike cinematic-first video generators, ARACHNE-FOUNDATION is being developed around:

  • realtime inference architecture
  • operational latency constraints
  • streaming generation
  • identity persistence
  • chunk-aware generation
  • deterministic runtime behavior
  • future digital employee systems

The long-term goal is not only high-quality video synthesis, but stable realtime operational generation inside enterprise-grade AI runtime systems.


Important Notice

This repository currently contains an initialization-stage checkpoint.

The released weights:

  • have NOT undergone large-scale continuation pretraining
  • are NOT benchmarked against production-grade video models
  • should NOT be considered final quality weights
  • are intended for architecture research, runtime experimentation, and future scaling work

At this stage, this repository should be viewed as:

a foundation topology transition checkpoint, not a finished frontier model.


Training Data

Current smoke/evaluation dataset:

Future large-scale pretraining datasets are not yet publicly released.


Runtime Ecosystem

ARACHNE-FOUNDATION is part of the broader NULLXES runtime ecosystem:

LayerRole
ASTERIASDeterministic reasoning layer
ARACHNE-XRealtime avatar/video runtime
FOUNDATIONLarge-scale backbone research
Session WorkersOperational orchestration
NULLXESEnterprise AI infrastructure

Repository Structure

/config.json
/diffusion_pytorch_model-*.safetensors
/model_index.json
/README.md

Roadmap

Phase 1 — Foundation Transition

  • topology scaling
  • runtime stabilization
  • compatibility verification

Phase 2 — Foundation Pretraining

  • temporal coherence learning
  • motion priors
  • identity consistency
  • multimodal alignment

Phase 3 — Realtime Optimization

  • chunk-aware distillation
  • low-latency inference
  • KV-cache optimization
  • streaming-native generation

Phase 4 — Native Multimodal Runtime

  • integrated audio/video generation
  • realtime duplex interaction
  • operational digital employee systems

Authors

NULLXES LLC CEO & Architect: @MagistrTheOne

Contact:

  • ceo@nullxes.com
  • Telegram: @MagistrTheOne

Final Note

ARACHNE-FOUNDATION is not being developed as a consumer entertainment model.

Its direction is toward:

realtime operational AI infrastructure for next-generation digital workforce systems.

From the published model card. Full card on the HuggingFace links in the sidebar.

Using it via the API

Call it like any OpenAI endpoint

Once AxForge deploys arachne-foundation for you, it answers on the OpenAI-compatible API — the same base URL and keys as every other model. (arachne-foundation below is illustrative; you get the exact model name on deployment.)

$ curl -sS https://api.axforge.ai/v1/videos/generations \
  -H "Authorization: Bearer $AXFORGE_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{"model":"arachne-foundation","prompt":"a drone shot over a forest"}'

Create an account — your API key is available in the console. 3M free tokens every 30 days with every new account.

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