FORGE Service

FORGE Distillation

Teacher-student compression for fast, efficient inference on edge and enterprise hardware.

Overview

FORGE Distillation compresses large models into smaller, faster deployments without sacrificing accuracy. We use teacher-student training, quantization, and pruning to deliver 3 to 5x inference speedups.

Distillation is ideal for edge devices, high-volume inference, and mission applications where latency and power are critical constraints.

What you get

  • Teacher-student distillation strategy
  • Quantization and pruning for footprint reduction
  • Speculative decoding for latency improvements
  • Inference benchmarking and validation
  • Deployment packaging for edge or cloud
  • Optional alignment and safety checks

Capabilities

  • Teacher-student distillation with accuracy targets
  • Quantization for reduced memory footprint
  • Latency optimization with speculative decoding
  • Compression tuned for target hardware
  • Performance benchmarking and validation
  • Integration with FORGE deployment services

Technical specs

Compression methods Teacher-student, quantization, pruning
Performance target 3 to 5x faster inference
Latency focus Optimized for low-latency endpoints
Deployment targets Edge devices, on-prem, cloud
Validation Accuracy retention and bias checks
Typical timeline 3 to 5 weeks

Pipeline placement

Distillation is the second stage of the FORGE pipeline, compressing models after training and before alignment and deployment.

01 Train 02 Distill 03 Align 04 Deploy

Ideal for

  • Edge and tactical deployments with limited power
  • High-throughput inference workloads
  • Programs that need lower latency and lower costs
  • Models requiring smaller memory footprints

Use cases

Deliver faster, lighter models for real-world deployments.

Edge AI

Deploy models on tactical devices with constrained compute and power budgets.

High-volume inference

Scale inference for enterprise workflows while controlling costs.

Latency-sensitive systems

Support mission decisions where response time is critical.

Accelerate inference without sacrificing accuracy

Deploy lighter, faster models with FORGE Distillation.