VBL-32M-Utility / README.md
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---
tags:
- vbl
- recurrent
- x86-64
- avx2
- rust
- cpu
- full-ram
- research
library_name: custom
---
# VBL-32M-Utility Native
**31,974,240-parameter VBL utility/research release with a native Rust x86_64 runtime.**
## Native execution
The primary runtime is **not Python/PyTorch**.
- Rust x86_64
- AVX2 + FMA optimized CPU dot products
- FP32 weights
- all model weights loaded into process RAM at startup
- **no mmap**
- **no SSD/model streaming**
- no quantization
- no GPU required for runtime
FP32 neural parameter payload: **121.97 MiB**.
## Neural architecture
Active checkpoint architecture:
`input -> embedding -> prelude -> [V16_NORM_MEAN + state-conditioned elastic bank + shared recurrent core] x R2 -> coda -> tied output`
- base VBL-RC M0: 20,013,920 parameters
- connected elastic capacity: 11,960,320 parameters
- total: 31,974,240
- 73 experts
- expert width: 320 -> 256 -> 320
- top-k: 3
- router: token-causal, shares expert `down.weight[0]`, zero additional router parameters
- selected experimental alpha: 0.75
## Verification status
This repository is intentionally named **Utility**, not Verified-32M.
The 32M candidate's official frozen C1 result was:
**583 / 853**
Therefore it is **NOT KR100 promoted**. The canonical M0 lineage remains preserved in the 32M base weights.
## Utility mode
The native executable loads the complete 32M model into RAM and first routes deterministic tasks
through executable verifiers. Unsupported utility requests abstain instead of fabricating a result.
Examples:
```bash
./vbl32m --model-dir . "What is 34 + -13?"
./vbl32m --model-dir . "Is 772 even or odd?"
./vbl32m --model-dir . "Complete the sequence: 32, 33, 34, 35,"
```
Raw experimental neural generation:
```bash
./vbl32m --model-dir . --raw "User: What is 2 + 2? Assistant:"
```
Trace recurrent state convergence:
```bash
./vbl32m --model-dir . --raw --trace "User: Hello Assistant:"
```
## Windows x86_64
The repository includes `native/build-windows-x86_64.ps1`.
On an x86_64 Windows machine with Rust installed:
```powershell
cd native
.uild-windows-x86_64.ps1
```
This produces `native arget elease bl32m.exe`.
## VBL architecture policy
See `ARCHITECTURE.json`.
Features that were approved as experimental directions but were not trained/certified in this exact
checkpoint are explicitly marked inactive instead of being falsely presented as learned behavior.
Full-RAM residency intentionally disables predictive SSD streaming/prefetch.
## Files
- `model.safetensors` β€” complete 32M FP32 state
- `tokenizer.json` β€” VBL-BPE-24K
- `native_config.json` β€” native runtime configuration and parity proof
- `native/` β€” Rust source
- `bin/linux-x86_64-v3/vbl32m` β€” compiled Linux x86_64 AVX2/FMA binary
- `ARCHITECTURE.json` β€” active/inactive VBL architecture contract
- `MANIFEST.json` / `SHA256SUMS` β€” provenance