TurboQuant lands in MLX, vLLM
TurboQuant’s KV-cache compression is starting to show up in real inference stacks, with mlx-vlm adding TurboQuant support and a vLLM PR targeting 2-bit cache compression. The Reddit post is basically a call for community benchmark data, especially tokens/sec, across MLX and vLLM setups.
This looks less like a finished product launch and more like the point where a research result starts turning into deployable infrastructure. The real question is not just memory savings, but whether long-context gains are worth the throughput tradeoff across MLX, vLLM, and similar backends.
DISCOVERED
45d ago
2026-04-17
PUBLISHED
45d ago
2026-04-17
RELEVANCE
AUTHOR
pmttyji
