Kimi K3 (2.8T) runs at 1 token/s on a MacBook Pro, streamed from four SSDs
Argonautlabs · hn · 2026-09-09
An HN post showcases Deltafin, an open-source project (argonautlabsai/deltafin) that streams the 2.8T-parameter Kimi K3 weights from four SSDs and runs it on a MacBook Pro at roughly 1 token/s.
- The idea: weights don't need to fit in memory; they're streamed on demand from SSD.
- Speed is impractical, but it's an interesting feasibility demo for pushing local inference beyond RAM limits.
More from Infra
- DeepSeek open-sources DeepInfer, its production inference engine, with equal Nvidia/Huawei support — thione · 2026-10-26
- Engineer with thousands of fabricated devices pours cold water on photonic crystal modulator yields — jwt0625 · 2026-10-26
- Anthropic S-1 reveals 48 cents of compute cost per dollar of Q2 revenue — nmasc_ · 2026-10-26
- Persistent AI joins UR network to route private AI inference with encrypted, IP-hidden traffic — 0xSammy · 2026-10-26
- Anthropic's disclosed compute commitments: $114.5B Google, $161.2B Broadcom top the list — BenBajarin · 2026-10-26
- SpaceX strikes $40B deal with Apollo Global to lease AI chips and data center hardware — Polymarket · 2026-10-26