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Topic

Disaggregated Prefill and Decode

Splitting prompt processing and token generation across different accelerator types within one cluster.

Current stories

buildOne report1 publisher

Cerebras measures its 5x mixed-chip inference gain against its own system count

Cerebras says splitting inference stages across chip types gave 5x more throughput from the same number of its systems without slowing token generation. Because the count covers only Cerebras hardware, the figure does not yet show what a mixed-chip fleet costs per unit of work.

Publishers:runtimewire.com

Reality

Evidence30
Adoption20
Hype gap+30
Incentives75
Confidence40
buildOne report1 publisher

d-Matrix's CTO labels Raptor's 1,000-tokens-per-second figure a simulation

d-Matrix CTO Sudeep Bhoja says Raptor's 1,000 tokens per second per user comes from a simulated 72-card system, with full racks not due until Q4 2027. Whole-system speed, power and cost per request are still unmeasured, so buyers are working from early silicon tests and simulations.

Reality

Evidence30
Adoption
Not scored
Hype gap+35
Incentives70
Confidence40
buildOne report1 publisher

Gimlet plans 100 MW of Cerebras wafer-scale capacity to split inference by phase

Gimlet Labs plans 100 MW of Cerebras-powered inference capacity, pairing wafer-scale chips with GPUs for different phases of each request. For buyers, the quoted 3,000 tokens per second is a company target until measured results appear.

Publishers:runtimewire.com

Reality

Evidence40
Adoption15
Hype gap+40
Incentives70
Confidence40