Slipstream appears to be a self-contained implementation for running very large mixture-of-experts coding modelsāclaimed at 35Bā480B parametersāon a 36 GB MacBook by streaming experts from SSD rather than keeping all weights in memory. The evidence titles say its repository predates the associated Reddit post and includes the implementation, app, benchmarks, and failed experiments. However, the supplied web results are unrelated and provide no independent confirmation of performance, latency, swapping behavior, SSD wear, or even the repositoryās details, so the core claims remain unverified here.
2026-07-31T18:26:56Z
No Slipstream-specific benchmark, comparison, or SSD-wear evidence has emerged across dozens of reobservations; the broader SSD-streamed MoE pattern is well-established via independent implementations (TurboFieldfare, Kimi K3 engine, RunNburn, Qwen 3.6 port), but that thread has saturated and Slipstream itself remains unvalidated. Nothing new expected within horizon; low relevance to Scott.
2026-07-31T17:30:15Z
The latest reobservations add no substantive Slipstream-specific benchmark or SSD-wear evidence; they only repeat the already-established spread of SSD-streamed MoE inference. Slipstreamās comparative utility remains unresolved, so this case no longer warrants frequent checks without project-specific results.
2026-07-31T16:29:31Z
No new substantive evidence independently benchmarks Slipstream; the latest reobservations add only repetitive amplification. SSD-streamed MoE inference is an established, spreading implementation pattern, but Slipstreamās comparative latency, swapping behavior, and SSD-wear costs remain unresolved.
2026-07-31T15:27:51Z
No new Slipstream-specific benchmark or wear analysis changes the case; the latest reobservations are repetitive amplification. SSD-streamed MoE inference remains an independently established and spreading pattern, but Slipstreamās comparative utility is still unresolved.
2026-07-31T14:27:13Z
No new substantive evidence independently benchmarks Slipstream; the latest activity is repetitive amplification of the already-established, spreading SSD-streamed MoE pattern. Slipstreamās comparative latency, swapping behavior, and SSD-wear costs remain unresolved, so monitoring should wait for project-specific results.
2026-07-31T13:24:37Z
The added engagement and refreshed discussion amplify TurboFieldfare but provide no new Slipstream-specific benchmark, comparison, or SSD-wear evidence. The broader SSD-streamed MoE pattern remains portable and actively spreading, while Slipstreamās claimed practical advantage is still unresolved.
2026-07-31T12:25:16Z
The Qwen 3.6 port extends SSD-streamed MoE inference beyond a single model and reports useful throughput, strengthening the broader patternās portability and practical viability. It still does not independently benchmark Slipstream or answer its comparative-performance, swapping, and SSD-wear questions.
2026-07-31T12:21:06Z
evidence attached: reddit.post.1vbp8te ā Independent implementation shows SSD-streamed MoE inference working for Qwen 3.6 at roughly 19ā23 tokens per second on an 8 GB working set.
2026-07-31T11:27:49Z
The latest reobservations add no substantive evidence beyond the already-established spread of SSD-backed MoE streaming. Slipstream itself still lacks independent comparative benchmarks or SSD-wear analysis, so further checks should wait for project-specific results.
2026-07-31T10:24:52Z
The engagement change adds no substantive Slipstream-specific evidence and only repeats the already-established broader adoption of SSD-backed MoE streaming. Slipstreamās comparative latency, swapping behavior, and SSD-wear costs remain unresolved, so monitoring should wait for independent project-specific benchmarks.
2026-07-31T05:22:37Z
The latest reobservations add no substantive evidence: the broader SSD-backed MoE streaming pattern is established and spreading, but Slipstream still lacks independent comparative benchmarks or SSD-wear analysis. Further checks should wait for project-specific results rather than repeated amplification.
2026-07-31T04:22:30Z
No new substantive evidence independently benchmarks Slipstream; the latest reobservations only amplify the already-established broader SSD-backed MoE streaming pattern. Slipstreamās comparative latency, swapping behavior, and SSD-wear costs remain unresolved, so wait for project-specific results.
2026-07-31T01:25:39Z
The reobservations add no substantive evidence beyond the independently established spread of SSD-backed MoE streaming. Slipstream itself still lacks comparative benchmarks and SSD-wear validation, so its practical advantage remains unresolved and no longer merits frequent checks without project-specific results.
2026-07-30T16:24:25Z
The latest activity remains repetitive amplification of TurboFieldfare and adds no independent Slipstream benchmark or SSD-wear analysis. The broader SSD-backed MoE streaming pattern is still spreading, but Slipstreamās practical comparative advantage remains unresolved.
2026-07-30T14:25:20Z
The new Reddit link only recirculates TurboFieldfare, reinforcing the already-established broader implementation pattern without adding independent Slipstream results. Slipstreamās comparative latency, swapping behavior, and SSD-wear costs remain unresolved, so further attention should wait for project-specific benchmarks.
2026-07-30T13:21:17Z
evidence attached: reddit.post.1vasnys ā shared external link with case evidence
2026-07-30T09:23:36Z
No Slipstream-specific benchmark or wear analysis has arrived; the latest reobservation adds only repetitive amplification. The broader SSD-backed MoE streaming pattern remains independently established and spreading, but Slipstream's practical advantage is still unresolved.
2026-07-30T08:22:29Z
No Slipstream-specific benchmark or wear analysis has arrived; the latest reobservation adds only repetitive amplification. The broader SSD-backed MoE streaming pattern remains independently established and spreading, but Slipstream's practical advantage is still unresolved.
2026-07-30T07:23:11Z
No Slipstream-specific benchmark or wear analysis has arrived; the latest reobservation adds only repetitive amplification. The broader SSD-backed MoE streaming pattern remains independently established and spreading, but Slipstream's practical advantage is still unresolved.
2026-07-30T06:22:42Z
No Slipstream-specific benchmark or wear analysis has arrived; the latest reobservation adds only repetitive amplification. The broader SSD-backed MoE streaming pattern remains independently established and spreading, but Slipstreamās practical advantage is still unresolved.
2026-07-30T05:21:56Z
No new substantive evidence independently benchmarks Slipstream; the case still shows an accelerating broader implementation pattern while Slipstreamās comparative latency, swapping behavior, and SSD-wear costs remain unresolved. Reobservations are repetitive amplification, so attention should remain low until Slipstream-specific results arrive.
2026-07-30T04:21:37Z
No new substantive evidence changes the read: multiple independent implementations establish SSD-backed MoE streaming as a spreading pattern, but none independently benchmarks Slipstreamās latency, comparative performance, swapping behavior, or SSD wear. Further activity is repetitive amplification unless Slipstream-specific results arrive.
2026-07-30T03:21:21Z
RunNburn adds a third independent implementation, strengthening the read that bounded-memory SSD-backed MoE streaming is becoming a real implementation pattern rather than an isolated experiment. It still does not benchmark Slipstreamās throughput, comparative advantage, swapping behavior, or SSD wear, so Slipstreamās specific utility remains unresolved.
2026-07-30T03:20:52Z
evidence attached: hn.story.49105154 ā An independent Rust implementation demonstrates practical on-demand expert streaming for a 295B MoE from a file larger than combined RAM and VRAM, materially supporting the broader feasibility premise behind Slipstream.
2026-07-30T02:21:16Z
No new substantive evidence independently benchmarks Slipstream; the slight engagement change is noise and adds nothing beyond the established spread of SSD-backed MoE streaming. Slipstreamās comparative latency, swapping behavior, and SSD-wear costs remain unresolved.
2026-07-30T01:21:56Z
No new substantive evidence independently benchmarks Slipstream; activity remains amplification of the broader, already-corroborated SSD-backed MoE streaming trend. Slipstreamās comparative latency, swapping behavior, and SSD-wear costs remain unresolved.
2026-07-30T00:24:04Z
No new substantive evidence benchmarks Slipstream itself; the latest activity remains repetitive amplification of the already-established broader SSD-backed MoE streaming trend. Slipstreamās comparative throughput, swapping behavior, and SSD-wear costs remain unresolved.
2026-07-29T23:22:48Z
No new substantive evidence changes the case: independent implementations continue to establish SSD-backed MoE streaming as a spreading technique, but Slipstream itself still lacks comparative benchmarks and SSD-wear validation. The latest activity is repetitive amplification rather than further corroboration.
2026-07-29T22:26:47Z
The Strix Halo request shows prospective demand for the broader technique but supplies neither results nor an implementation, so it does not further validate Slipstream. Independent implementations still establish a spreading SSD-backed MoE inference pattern, while Slipstreamās comparative performance, swapping behavior, and SSD-wear costs remain open.
2026-07-29T22:21:21Z
evidence attached: reddit.post.1vaa4g4 ā The request directly targets SSD-streamed MoE inference on Strix Halo, a relevant deployment context for the open streaming-validation case.
2026-07-29T21:22:56Z
The new attachment adds no independent benchmark of Slipstream and does not change the established read: SSD-backed MoE streaming is spreading across implementations, while Slipstreamās specific latency, comparative performance, swapping, and SSD-wear claims remain unresolved. Further engagement is repetitive amplification rather than new corroboration.
2026-07-29T20:23:34Z
The latest attachment adds no substantive evidence beyond the already-established spread of SSD-backed MoE streaming. Slipstream itself still lacks independent benchmarks for throughput, comparative advantage, swapping behavior, and SSD wear, so this is repetitive amplification rather than a change in meaning.
2026-07-29T19:26:38Z
No newly substantive evidence benchmarks Slipstream itself; the attached material still supports only the broader spread of SSD-backed MoE streaming. Slipstreamās claimed throughput, comparative advantage, swapping behavior, and SSD-wear costs remain unresolved.
2026-07-29T18:24:25Z
The latest activity adds no independent benchmark of Slipstream itself; it remains amplification of a broader implementation trend already established by TurboFieldfare and the Kimi K3 engine. SSD-backed MoE streaming is spreading, but Slipstreamās practical latency, baseline performance, swapping, and SSD-wear claims remain open.
2026-07-29T17:26:27Z
No new substantive evidence changes the prior read: independent implementations show that SSD-backed MoE streaming is spreading, but none validates Slipstreamās specific throughput, baseline comparisons, swapping behavior, or SSD-wear claims. The latest activity is amplification rather than further corroboration of Slipstream itself.
2026-07-29T16:28:12Z
Two independent implementations (TurboFieldfare for Gemma 4 26B, Kimi K3 streaming engine) now demonstrate SSD expert streaming for MoE on memory-constrained Macs, corroborating the general feasibility. Slipstream's specific performance claims and SSD-wear analysis remain unverified, so the core hypothesis is not yet resolved.
2026-07-29T16:22:01Z
evidence attached: hn.story.49098966 ā An independent implementation streams Kimi K3 experts from NVMe on a 64GB Mac, directly bearing on practical SSD-based MoE inference.
2026-07-29T15:30:29Z
TurboFieldfare independently supports the broader feasibility of streaming oversized MoE weights on memory-constrained Macs, making Slipstream less isolated and worth monitoring. It does not benchmark Slipstream or resolve its latency, baseline-performance, swapping, and SSD-wear claims, so the core hypothesis remains uncorroborated.
2026-07-29T15:21:39Z
evidence attached: hn.story.49098510 ā This is independent implementation evidence for SSD expert streaming of MoE models on constrained Macs.
2026-07-26T02:21:58Z
The newly attached material remains first-party testimony about the repository and its claimed benchmarks, not independent validation. With no baseline comparison, SSD-wear evidence, or outside implementation, the caseās meaning is unchanged and the discussion is mostly repetitive skepticism.
2026-07-26T01:22:48Z
The expanded discussion adds skepticism and requests for baseline comparisons and SSD-wear analysis, but no independent benchmark or implementation evidence. The case remains testable but uncorroborated, while deteriorating reception lowers its near-term attention value.
2026-07-25T18:26:25Z
grounded: novel/none ā No intersection found: there are no Scott wiki hits connecting this claim to his positions or projects, and no radar hits showing that Slipstream or this develo
2026-07-25T18:25:50Z
origin walked (codex/luna, conf 0.98): anchor reddit.post.1v6eqvo -> echo.github.164fe953a2 by Schero D. (GitHub: Schero94)
2026-07-25T18:24:18Z
case created ā The claimed bounded-RAM expert-streaming implementation is a distinct, measurable approach to running oversized MoE models locally.