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feat: WebAssembly inference proof of concept
Adds Emscripten build support and a browser-based roundtrip demo
for TurboQuant's polar_quant_encode_turbo4 / polar_quant_decode_turbo4
functions.

Changes:
- CMakeLists.txt: detect Emscripten toolchain; build shared WASM module
  with exported C functions; set ALLOW_MEMORY_GROWTH and MODULARIZE
- Added build-wasm.sh: convenience script using emcmake to produce
  libturboquant-wasm.js + libturboquant-wasm.wasm
- Added wasm-demo/: self-contained HTML/JS demo that loads the WASM
  module and runs an encode/decode roundtrip displaying latency

This establishes the build pipeline and client-side harness needed to
run TurboQuant in the browser. A working demo is now one `./build-wasm.sh`
plus `python3 -m http.server` away.

Closes #104
2026-04-26 12:50:14 -04:00
2026-03-30 17:08:45 +00:00
2026-03-30 21:06:49 +00:00

TurboQuant

KV cache compression for local inference on M4 Max MacBook Pro.

What

TurboQuant (Google, ICLR 2026) is a three-stage KV cache compression method:

  1. PolarQuant — WHT rotation + polar coordinates + Lloyd-Max codebook (~4.2x compression)
  2. QJL — 1-bit quantized Johnson-Lindenstrauss residual correction
  3. TurboQuant — PolarQuant + QJL = ~3.5 bits/channel, zero accuracy loss

Why

Unlock 64K-128K context on qwen3.5:27b within 32GB unified memory. A 27B model at 128K context with TurboQuant beats a 72B at Q2 with 8K context.

Status

See issues for current progress.

Roles

  • Strago: Build spec author
  • Cid: Implementation, benchmarks, deployment
  • Locke: Research support, upstream watch
  • John: Quality review
  • Frankie: Coordination

Source Repos

Docs

Description
TurboQuant KV cache compression for local inference — PolarQuant + QJL on M4 Max via llama.cpp/Ollama. Build spec from Strago, build by Cid, coordination by Frankie.
Readme MIT 28 MiB
Languages
Python 90.5%
C++ 6.2%
Metal 2.4%
CMake 0.9%