vs 1.94× zlib · 15 datasets · Python 3.12 Apple M-series · verified Sep 2026
12,500×Peak ratio
125×Minimum ratio
0.035msp50 latency
64 bytesOutput size
FREEAPI access
↓ explore the data
What UUON CFE-A02 actually does
The model
Gravitational Field Zones
Input data is partitioned into gravitational zones via AIBH infall dynamics. Each zone collapses to a centroid — the mathematical center of mass of that region of the field.
The output
Packed Float32 Binary
8 zones produces 16 floats — 64 bytes fixed, regardless of input size. 800,000 bytes encodes to 64 bytes. Shannon entropy H returned per zone on every call.
The tradeoff
Lossy Structural
Not byte-for-byte lossless. Approximate reconstruction from centroids. Use zlib or zstd for exact recovery. Use UUON CFE for field structure transmission, telemetry, ML features, and IoT streams.
15 datasets · 100 runs each · all results verified · Sep 2026
Select a dataset
Compression ratio — UUON CFE-A02 vs zlib
125×Binary ratio
64.8×vs zlib adv.
0.035msp50 latency
0.039msp99 latency
Dataset
N
Ratio
vs zlib
p50
Full results — all datasets · all metrics
Dataset
N
Orig bytes
UUON bytes
Ratio
vs zlib adv.
p50 ms
p99 ms
min ms
Sine Wave 1K
1,000
8,000
64
125.0x
64.8x
0.0351
0.0394
0.0312
Sine Wave 10K
10,000
80,000
64
1,250.0x
637.8x
0.2948
0.3130
0.2710
Sine Wave 100K
100,000
800,000
64
12,500.0x
6,345.2x
3.0323
3.3071
2.9100
Cosine Mix 1K
1,000
8,000
64
125.0x
64.4x
0.0340
0.0420
0.0311
Random Uniform 1K
1,000
8,000
64
125.0x
64.8x
0.0328
0.0384
0.0299
Random Uniform 10K
10,000
80,000
64
1,250.0x
637.8x
0.3020
0.3200
0.2780
Gaussian 1K
1,000
8,000
64
125.0x
64.4x
0.0326
0.0423
0.0298
Gaussian 10K
10,000
80,000
64
1,250.0x
634.5x
0.2963
0.3288
0.2720
Spiky Chaos 1K
1,000
8,000
64
125.0x
64.4x
0.0326
0.0435
0.0299
Constant 1K
1,000
8,000
64
125.0x
1.3x
0.0343
0.0389
0.0310
Linear Ramp 1K
1,000
8,000
64
125.0x
34.5x
0.0335
0.0422
0.0305
Step Function 1K
1,000
8,000
64
125.0x
1.7x
0.0337
0.0444
0.0308
Sensor Telemetry
5,000
40,000
64
625.0x
297.6x
0.1529
0.1797
0.1410
Financial Series
1,000
8,000
64
125.0x
64.1x
0.0334
0.0351
0.0305
Extreme Values
1,000
8,000
64
125.0x
1.5x
0.0335
0.0394
0.0308
Methodology: 100 iterations per dataset, Python 3.12, Apple M-series, local execution. UUON output: 8 zones x (centroid + max_deviation) x float32 = 64 bytes fixed, regardless of input size. zlib baseline: level-1 compression of string-encoded float64 array. Compression class: Lossy structural. Not lossless. Approximate reconstruction from zone centroids only. Advantage column: UUON binary ratio divided by zlib ratio. Different compression classes — not a direct equivalence.
Interactive · calls compress.uuon.world live · demo key included
Test the engine
Input — paste numbers or load a sample
--Ratio
--Entropy H
--Zones
--Latency
Stress test — concurrent calls to live Fargate
// Click to fire N concurrent calls against the live endpoint
Output — AIBH result from live API
// Select a sample dataset above
// or enter comma-separated numbers
// then click Compress
//
// Returns:
// compression_ratio_b64 actual byte ratio
// H_total Shannon entropy
// H_per_zone entropy per zone
// compressed_b64 packed float32 binary
// compressed_bytes_b64 output size in bytes
Copy · paste · run · no SDK required
One endpoint. Any language.
# Step 1 - register for your free key
curl -X POST http://compress.uuon.world/register \
-H "Content-Type: application/json" \
-d '{"email": "you@example.com"}'
# Step 2 - compress (binary endpoint - up to 12500x ratio)
curl -X POST http://compress.uuon.world/algorithms/compression-field/compress-binary \
-H "Content-Type: application/json" \
-H "x-api-key: YOUR_UUON_KEY" \
-d '{
"data": [1.2, 3.4, 5.6, 7.8, 9.0, 2.1, 4.3, 6.5, 8.7, 0.9],
"zone_count": 8
}'
# Response:
# compressed_b64 base64 packed float32 binary (64 bytes)
# compression_ratio_b64 actual byte compression ratio
# H_total Shannon field entropy
# H_per_zone entropy breakdown per zone
# original_bytes input size in bytes
# compressed_bytes_b64 output size in bytes
import requests, base64, struct, math
API_KEY = "your_uuon_key"
BASE = "http://compress.uuon.world"
data = [math.sin(i * 0.1) * 50 + 50 for i in range(1000)]
r = requests.post(
f"{BASE}/algorithms/compression-field/compress-binary",
headers={"x-api-key": API_KEY},
json={"data": data, "zone_count": 8}
).json()
o = r["output"]
print(f"Compression ratio : {o['compression_ratio_b64']}x")
print(f"Shannon entropy H : {o['H_total']}")
print(f"Original size : {o['original_bytes']} bytes")
print(f"Compressed size : {o['compressed_bytes_b64']} bytes")
# Decode the packed binary
raw = base64.b64decode(o["compressed_b64"])
floats = struct.unpack(f"{len(raw)//4}f", raw)
zones = [(floats[i], floats[i+1]) for i in range(0, len(floats), 2)]
for i, (centroid, deviation) in enumerate(zones):
print(f"Zone {i}: centroid={centroid:.4f} max_dev={deviation:.4f}")
const KEY = 'your_uuon_key';
const BASE = 'http://compress.uuon.world';
const data = Array.from({length: 1000}, (_, i) => Math.sin(i * 0.1) * 50 + 50);
const res = await fetch(`${BASE}/algorithms/compression-field/compress-binary`, {
method: 'POST',
headers: { 'Content-Type': 'application/json', 'x-api-key': KEY },
body: JSON.stringify({ data, zone_count: 8 })
});
const { output: o } = await res.json();
console.log(`Ratio : ${o.compression_ratio_b64}x`);
console.log(`Entropy: ${o.H_total}`);
console.log(`Size : ${o.original_bytes} to ${o.compressed_bytes_b64} bytes`);
// Decode binary in browser
const raw = atob(o.compressed_b64);
const buf = new ArrayBuffer(raw.length);
const u8 = new Uint8Array(buf);
for (let i = 0; i < raw.length; i++) u8[i] = raw.charCodeAt(i);
const f32 = new Float32Array(buf);
// f32 = [centroid_z0, maxdev_z0, centroid_z1, maxdev_z1, ...]
package main
import (
"bytes"
"encoding/base64"
"encoding/binary"
"encoding/json"
"fmt"
"math"
"net/http"
)
const apiKey = "your_uuon_key"
const base = "http://compress.uuon.world"
func main() {
data := make([]float64, 1000)
for i := range data {
data[i] = math.Sin(float64(i)*0.1)*50 + 50
}
body, _ := json.Marshal(map[string]interface{}{
"data": data, "zone_count": 8,
})
req, _ := http.NewRequest("POST",
base+"/algorithms/compression-field/compress-binary",
bytes.NewBuffer(body))
req.Header.Set("Content-Type", "application/json")
req.Header.Set("x-api-key", apiKey)
resp, _ := http.DefaultClient.Do(req)
defer resp.Body.Close()
var result map[string]interface{}
json.NewDecoder(resp.Body).Decode(&result)
o := result["output"].(map[string]interface{})
fmt.Printf("Ratio : %vx\n", o["compression_ratio_b64"])
fmt.Printf("Entropy: %v\n", o["H_total"])
raw, _ := base64.StdEncoding.DecodeString(o["compressed_b64"].(string))
for i := 0; i < len(raw)/4; i += 2 {
c := math.Float32frombits(binary.LittleEndian.Uint32(raw[i*4:]))
d := math.Float32frombits(binary.LittleEndian.Uint32(raw[(i+1)*4:]))
fmt.Printf("Zone %d: centroid=%.4f max_dev=%.4f\n", i/2, c, d)
}
}
use base64::{engine::general_purpose, Engine};
use reqwest::Client;
use serde_json::json;
#[tokio::main]
async fn main() -> Result<(), Box<dyn std::error::Error>> {
let client = Client::new();
let data: Vec<f64> = (0..1000)
.map(|i| (i as f64 * 0.1).sin() * 50.0 + 50.0)
.collect();
let res: serde_json::Value = client
.post("http://compress.uuon.world/algorithms/compression-field/compress-binary")
.header("x-api-key", "your_uuon_key")
.json(&json!({ "data": data, "zone_count": 8 }))
.send().await?.json().await?;
let o = &res["output"];
println!("Ratio : {}x", o["compression_ratio_b64"]);
println!("Entropy: {}", o["H_total"]);
let raw = general_purpose::STANDARD.decode(o["compressed_b64"].as_str().unwrap())?;
let floats: Vec<f32> = raw.chunks(4)
.map(|c| f32::from_le_bytes(c.try_into().unwrap()))
.collect();
for (i, chunk) in floats.chunks(2).enumerate() {
println!("Zone {}: centroid={:.4} max_dev={:.4}", i, chunk[0], chunk[1]);
}
Ok(())
}
import fetch from 'node-fetch'; // npm install node-fetch
const KEY = 'your_uuon_key';
const BASE = 'http://compress.uuon.world';
const data = Array.from({length: 1000}, (_, i) => Math.sin(i * 0.1) * 50 + 50);
const res = await fetch(`${BASE}/algorithms/compression-field/compress-binary`, {
method: 'POST',
headers: { 'Content-Type': 'application/json', 'x-api-key': KEY },
body: JSON.stringify({ data, zone_count: 8 })
});
const { output: o } = await res.json();
console.log(`Ratio : ${o.compression_ratio_b64}x`);
console.log(`Entropy: ${o.H_total}`);
const buf = Buffer.from(o.compressed_b64, 'base64');
const floats = [];
for (let i = 0; i < buf.length; i += 4) floats.push(buf.readFloatLE(i));
floats.forEach((v, i) => {
if (i % 2 === 0) process.stdout.write(`Zone ${i/2}: centroid=${v.toFixed(4)}`);
else console.log(` max_dev=${v.toFixed(4)}`);
});