Ni

NightRun, bare metal LLM inference, no OS, boots from USB

Hacker News

NightRun, bare metal LLM inference, no OS, boots from USB

Share card

Actual performance

6points
Did not reach leaderboard

Launch Intel predictions

Analyze your own launch →
BetaListSuited for BetaList early-adopters · Missing: web3, chat, crypto
79%79% predicted probability of success on BetaList, based on ML models trained on real launch data.
best fitHighest predicted score across all platforms for this description.
Product HuntOn track for Day 1 leaderboard · Missing: mac, agents, macos
67%67% predicted probability of success on Product Hunt, based on ML models trained on real launch data.
Hacker NewsStrong engagement from HN community · Missing: https docs, excited, just released
65%65% predicted probability of success on Hacker News, based on ML models trained on real launch data.
nativeThis product was originally launched on this platform.
TrustMRRLess likely to generate early MRR · Missing: mobile apps, ios, personal
47%47% predicted probability of success on TrustMRR, based on ML models trained on real launch data.
AppSumoMay struggle as an AppSumo deal · Missing: plus, platform, intuitive
34%34% predicted probability of success on AppSumo, based on ML models trained on real launch data.
Indie HackersIH features products with proven revenue · Missing: supports, reddit linkedin, podcasting
25%25% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.
Acquire.comPre-revenue stage for this audience · Missing: arr, mrr, revenue
18%18% predicted probability of success on Acquire.com, based on ML models trained on real launch data.

Incorrect prediction on native model

Similar products

LL
LLM Inference Requirements Profiler59%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

LLM Inference Requirements Profiler

Hacker News4
Ba
Bare metal OS images with Packer, VirtualBox and qemu-img59%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

Bare metal OS images with Packer, VirtualBox and qemu-img

Hacker News15
De
DerzForth – Bare-metal Forth implementation for RISC-V58%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

DerzForth – Bare-metal Forth implementation for RISC-V

Hacker News2
Re
Replacing VMs with bare-metal Containers71%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

Replacing VMs with bare-metal Containers

Hacker News5
LL
LLM as an OS [video]43%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

LLM as an OS [video]

Hacker News3
Sp
Speeding up LLM inference 2x times (possibly)74%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

Speeding up LLM inference 2x times (possibly)

Hacker News419
Op
Open-source AMDGCN kernels for optimizing LLM inference72%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

Open-source AMDGCN kernels for optimizing LLM inference

Hacker News5
On
Onera – Private LLM Inference Inside AMD SEV-SNP Enclaves59%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

Onera – Private LLM Inference Inside AMD SEV-SNP Enclaves

Hacker News1
Bo
BonzAI – self-sovereign, local LLM inference in the browser62%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

BonzAI – self-sovereign, local LLM inference in the browser

Hacker News5
Bu
Building the LLM OS by Karpathy59%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

Building the LLM OS by Karpathy

Hacker News1