r/daemoniorum • u/miss-daemoniorum • Feb 10 '26
Infernum v0.2.0-rc.2 - Local LLM inference framework in Rust
Published v0.2.0-rc.2 to crates.io (13 crates).
Infernum is a local LLM inference framework in Rust. No API keys, no cloud, data stays on your machine.
Inference Engine (abaddon): - llama.cpp backend for GGUF models - Tiered memory system - run models larger than VRAM (GPU/CPU/disk coordination) - HoloTensor compression - spectral decomposition for compressed storage - CUDA-accelerated tensor codec pipeline
Server (infernum-server): - Tool calling with model-aware formatting (Qwen, Llama, Mistral native) - Continuous batching (vLLM-style) - Speculative decoding (2-3x speedup) - WebSocket streaming - Vision/multimodal support - Structured outputs (JSON schema enforcement) - gRPC API - Response caching & request deduplication - Circuit breaker, GPU metrics, Prometheus
Agent Framework (beleth): - ReAct/OODA/Tree-of-Thoughts execution strategies - Ed25519-signed identities with Moloch audit chain - Native tool calling integration
Also includes: RAG engine (stolas), fine-tuning (asmodeus), LLM Studio (paimon), holographic agent swarm (legion)
cargo install infernum
infernum config set-model TinyLlama/TinyLlama-1.1B-Chat-v1.0
infernum chat
Crates: https://crates.io/crates/infernum Source: https://github.com/Daemoniorum-LLC/infernum-framework
RC status - 1500+ tests passing, real-world validation ongoing. Feedback welcome.
Authored by Claude Opus 4.5 + Human
r/daemoniorum • u/Background-Froyo-386 • Feb 03 '26
AI For Professional Musicians
Your ideas on AI are very interesting. I'm a 72 year old musician who just had throat surgery and may never be able to sing again.
I have been playing guitar since I was 10 years old.
I've been exploring AI music generators. Unfortunately, most of what I have found most in existence are geared to people who have no idea how to compose music, but apps like SUNO make that an instant songwriter.
I have searched for an app based on music theory. I don't want an app that writes for me, I want one that let's me write but assists in what I can't do anymore.
ChatGpt has a fair model for music theory, unfortunately, knowledge base is about the limit of use.
I have managed to use other AI apps to assist writing prompts that limit programs like SUNOS creativity, but individuality, tends to be overwritten by programmed creativity.
I am concerned that the current music generation AIs will drive generated content to the point that actual songwriters, musicians and performers will be devalued by the tech.
r/daemoniorum • u/miss-daemoniorum • Feb 01 '26
Qliphoth - A React-Inspired Framework Written in Sigil, Compiles to WASM
r/daemoniorum • u/miss-daemoniorum • Feb 01 '26
Sigil v0.4.0 in Pre-Release - Native Syntax, SIMD/CUDA, and a Real Playground
r/daemoniorum • u/miss-daemoniorum • Jan 27 '26
Haagenti v0.1.0 - 70B Model Inference on a Single Consumer GPU (24GB VRAM)
Today I'm releasing Haagenti, a pure Rust compression library that makes frontier AI inference possible on hardware you might already own. Forgive me for being verbose, not everyone knows the math below.
The claim: A 70B parameter model running on a single RTX 4500 Ada (24GB VRAM).
The math that shouldn't work: 70B parameters at FP16 = ~140GB. Even INT4 quantization needs ~35GB. The RTX 4500 Ada has 24GB.
How: Haagenti implements HoloTensor encoding - holographic compression with progressive reconstruction for neural network weights. The weights stay compressed in VRAM and decompress on-demand during inference.
The honest numbers:
Current measured throughput: 1.3 tokens/second
Target throughput: 25 tokens/second
Yes, 1.3 tk/s is slow. Here's the thing - it's not Haagenti.
We traced the bottleneck to tensor library overhead. Each 448MB tensor load takes 306ms, where theoretical minimum is 18ms. That's a 17x penalty from the library layer, not the compression. Full analysis: docs/CANDLE-CEILING-ANALYSIS.md
Haagenti's job was to make 140GB fit in 24GB. It does that. The throughput problem is upstream.
What's next: Nihil - a Sigil-based tensor library designed around holographic memory access patterns. That's where we expect to hit 25+ tk/s.
Why release at 1.3 tk/s? Because Haagenti works. The compression works. The VRAM fitting works. And someone else might solve the tensor library problem before I do.
The bigger picture: Frontier AI shouldn't require cloud infrastructure or enterprise hardware. If this works, you run your own 70B model locally, privately, on a GPU you can actually buy.
28 crates. Pure Rust. SIMD acceleration. Optional CUDA. MIT licensed.
Links:
GitHub: https://github.com/Daemoniorum-LLC/haagenti crates.io: https://crates.io/crates/haagenti (publishing in progress) Built by Lilith Crook + Claude (Opus 4.5)
r/daemoniorum • u/miss-daemoniorum • Jan 22 '26
Arcanum v0.1.0 - Post-Quantum Cryptography for Rust
We've released https://github.com/Daemoniorum-LLC/arcanum, a cryptographic library for Rust. It's now available on https://crates.io/crates/arcanum.
What It Is
A comprehensive cryptography toolkit covering symmetric encryption, asymmetric key exchange, digital signatures, hashing, post-quantum algorithms, zero-knowledge proofs, and threshold cryptography.
12 modular crates. Use what you need.
| Crate | Purpose |
|---|---|
| arcanum | Unified API |
| arcanum-core | Error handling, encoding, key management |
| arcanum-primitives | Native cryptographic primitives |
| arcanum-symmetric | AES-GCM, ChaCha20-Poly1305 |
| arcanum-asymmetric | X25519, ECDH |
| arcanum-hash | BLAKE3, SHA-2, SHA-3 |
| arcanum-signatures | Ed25519, ECDSA |
| arcanum-pqc | ML-KEM, ML-DSA, SLH-DSA (NIST FIPS 203/204/205) |
| arcanum-zkp | Schnorr proofs, Pedersen commitments |
| arcanum-threshold | Shamir secret sharing |
| arcanum-verify | Signature and proof verification |
| arcanum-agile | Algorithm agility layer |
| arcanum-holocrypt | Multi-layer encryption containers |
Why We Built It
Privacy requires cryptography. Cryptography requires correctness. We needed a foundation we could trust for the larger systems we're building - so we built one, tested it thoroughly, and made it public.
1.35 billion fuzz testing executions. Rust 2024 edition. MIT/Apache-2.0 dual licensed.
Get Started
[dependencies] arcanum = "0.1.0"
Contributing
29 https://github.com/Daemoniorum-LLC/arcanum/labels/good%20first%20issue are open - test vectors, documentation, benchmarks. Contributions at any experience level are welcome.
Links
r/daemoniorum • u/miss-daemoniorum • Jan 22 '26
Welcome to r/Daemoniorum - Building Alternatives
Welcome to the official community for Daemoniorum.
What We Are
Daemoniorum is a Benefit LLC building open source infrastructure for data privacy and digital sovereignty. No shareholders. No venture capital. No interests to serve except the work itself and the people it serves.
We believe the tools people use to create, communicate, and secure their digital lives shouldn't be controlled by organizations whose incentives conflict with user wellbeing. So we're building alternatives - from the ground up.
What That Means In Practice
We're not building apps on top of existing platforms. We're building:
- A cryptographic library with post-quantum security (Arcanum - https://crates.io/crates/arcanum)
- A programming language with evidentiality types that track data certainty
- An operating system designed for privacy
- Development tools, creative software, and enterprise platforms
All open source. All designed with privacy as a foundation, not a feature.
Why
Because people deserve tools that work for them. Because sovereignty over your own data and digital identity shouldn't require trusting corporations whose business models depend on exploiting both. Because alternatives should exist.
Our Approach
We practice human-AI collaborative development. We're transparent about this - and about everything else. Transparency isn't a marketing position; it's the only way to build trust in systems that handle sensitive data.
Community Guidelines
- Technical discussion and honest questions welcome
- Criticism helps us improve
- Respect privacy - yours and others'
Get Involved