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coreglass

See where local inference loses speed on Apple Silicon under Linux

This is 1 of 97 launches in local and on-device AI runtimes — see how it stacks up on momentum and crowding →

1069 other launches read as similar to this one →

Details

External ID
1401365496
Source
GITHUB
Company
—
Product
coreglass
Website domain
github.com
Launched
Oct. 2, 2026
Cohort
—
Upvotes
12
Upvotes percentile
0.251863684771033
Tags
—
Fetched at
Oct. 5, 2026, 1:02 a.m.
Updated at
Oct. 5, 2026, 1:02 a.m.

Enrichment

Theme
local and on-device AI runtimes
Vertical
Horizontal
Function
Observability & eval
Audience
Developer
AI stance
AI-native
Project type
Hobby / open-source project
Normalized one-liner
inference speed profiler for apple silicon linux users
Manually corrected
False

Could you build this?

No It requires low-level kernel profiling, Asahi Linux driver reverse engineering, and performance counter instrumentation for Apple Silicon GPU/NPU architectures.

What it would actually take: This tool necessitates deep instrumentation of the Linux kernel on Apple Silicon (Asahi Linux/m1n1/DRM drivers), tapping into hardware Performance Monitoring Units (PMUs) and GPU/NPU firmware interfaces. The hard part is interpreting undocumented Apple Silicon hardware registers, unified memory bus contention, and AGX driver performance bottlenecks without official documentation. Requires low-level Linux kernel developers and hardware performance architects.

Competitors

Other products that read as similar to this one — 1069 launches clear the similarity bar, closest 8 shown.

Attention rank: #835 of 1070 (itself plus its competitors, highest first — normalized so YC and Product Hunt are compared fairly).

Launched 336 days after the earliest competitor.

Other launches for this product

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