Condense

CompressLLM Models.
Deploy Anywhere.

DistillationQuantizationPruningLoRA

Condense compresses large models into small, deployable networks — automatically.

Get Started
Scroll

Big Models.
Bigger Problems.

Today's neural networks are too large, too slow, too expensive.

500ms+ delays

Latency

Models take too long to respond

$10k+ monthly

Cost

GPU inference bills skyrocket

10GB+ memory

Hardware

Cannot deploy to edge devices

Distillation-as-a-Service

Upload your model. Choose your objective. Get a distilled, deployable version — automatically.

Export Formats

TorchScript
ONNX
TFLite
CoreML
TensorRT
01

Upload Model

Provide your model or Hugging Face link

02

Choose Objective

Select target size, latency, or hardware

03

Distillation Runs

Automated distillation, pruning, quantization

04

Download Model

Get optimized model in your format

Incoming

30 Seconds to Value

Install, compress, deploy. It's that simple.

1
Install SDK
2
Initialize Client
3
Start Compression Job
4
Download Result
main.py
1from condense import Condense
2 
3client = Condense(api_key="...")
4 
5# Start compression job
6job = client.compress(
7 model="meta-llama/Llama-3-8b",
8 target_size="800M",
9 strategy="distillation"
10)
11 
12# Download result
13job.wait_until_done()
14job.download("./model")

Built for Production

Enterprise-grade compression with the simplicity of a service.

Custom Compression Pipelines

Tailor pruning, quantization, and distillation strategies to your specific needs.

Prune
Quantize
Distill

Automatic Benchmarking

Real-time accuracy, latency, and throughput metrics for every compressed model.

Size
Latency
Accuracy
Cost

Hosted Model Monitoring

Monitor accuracy and performance in one dashboard. Track drift and degradation.

CLI + SDK Interface

Incoming

Integrate distillation into your CI/CD. Python SDK for programmatic access.

$ condense compress model.pt

Quantization Modules

INT8, INT4, and mixed-precision quantization with minimal accuracy loss.

INT8INT4FP16

GPU-Accelerated Jobs

Scale distillation workloads with on-demand GPU clusters. Fast iteration cycles.

A100H100T4

Simple, Transparent Pricing

Choose the plan that fits your compression needs.

Starter

$-
per month

For small teams and early-stage startups

  • 10 compression jobs/month (per run)
  • Additional jobs: $20/run
  • Standard distillation pipeline
  • Basic benchmarking
  • Community support
Get Started
Most Popular

Professional

$-
per month

For growing teams with production workloads

  • 50 compression jobs/month (per run)
  • Additional jobs: $15/run
  • Custom compression pipelines
  • Advanced benchmarking & monitoring
  • Priority support
  • CLI + Python SDKIncoming
Get Started

Enterprise

Custom
contact us

For organizations at scale

  • Unlimited compression jobs
  • Dedicated infrastructure
  • Custom model architectures
  • SLA & dedicated support
  • On-premise deployment
  • Advanced security & compliance
Contact Sales

The Path Forward

Building the future of neural network compression.

Q1 2026
Current
  • Knowledge Distillation
  • HuggingFace Integration
  • Multi-format Export
  • Real-time Job Monitoring
Q2 2026
In Progress
  • Post-Training Quantization
  • Structured Pruning
  • Python SDK & CLI
  • Visual Pipeline Builder
Q3 2026
Planned
  • LoRA Compression
  • Multi-Teacher Distillation
  • Quantization-Aware Training
  • Edge Device Optimization
Q4 2026
Vision
  • Multi-Modal Compression
  • Neural Architecture Search
  • Distributed Training
  • On-Premise Deployment

Stay Updated.
Join the Community.

Get the latest updates on model compression research and features.

Weekly research digests
Product updates
Community access