Language models for the edge
Tiny edge language models for private, explainable inference on constrained hardware. Institutional control over raw capability.
Purpose
Private, low‑latency, explainable inference on constrained devices. Our LLM family prioritises transparency, energy efficiency, and institutional control over raw capability.
Private
On‑device inference. Your data never leaves your infrastructure.
Low‑latency
Optimised for edge deployment with minimal compute requirements.
Explainable
Clear reasoning paths and decision audit trails.
T‑E Model Family
Tunet Edge models follow a clear naming convention: T-E-{size}/{year.release}
S/M/L denote parameter budgets optimised for different edge deployment scenarios.
T‑E‑S/2025.1
Ultra‑compact model for IoT and mobile devices. Optimised for classification and simple reasoning tasks.
T‑E‑M/2025.1
Balanced model for edge servers and workstations. Good general‑purpose reasoning with safety guardrails.
T‑E‑L/2025.1
Full‑capability model for edge clusters. Complex reasoning with institutional safety requirements.
Model Card Standards
Every model comes with complete documentation following our transparency framework.
Summary
- • Intended use cases
- • Explicit non‑goals
- • Safety boundaries
Technical Specs
- • Parameter count
- • Context window
- • Quantisation options
- • Supported runtimes
Training
- • Data policy
- • Filtering methodology
- • Epochs & compute
- • Reproducibility notes
Evaluations
- • Task‑specific benchmarks
- • On‑device latencies
- • Energy profiling
- • Methodology notes
Safety
- • Guardrails & refusal policies
- • Jailbreak handling
- • Known failure modes
- • Bias assessments
Distribution
- • Licensing terms
- • Attribution requirements
- • Downloads & checksums
- • Redistribution policy
Assurance Standards
-
Reproducible on‑device benchmarks with fixed seeds
-
Deterministic builds where feasible
-
Provenance hashes for releases
-
Evaluation scripts with transparency reports
Framework Integration
All models integrate seamlessly with our Frameworks and APIs:
-
SDKs and adapters in our framework stack
-
Direct endpoints in Content/Translate APIs
-
Built‑in evaluation harness compatibility
-
Ready for ecosystem deployment
Ready for edge deployment?
Browse model cards, download weights, or request a technical briefing on edge ML strategy.