NSED 0.3 Release. Steer Multi-Agent AI Swarm for Frontier Performance

Hacker News

Use open-weight models on your own GPU or combine with proprietary to max out reasoning quality while staying compliant! Three 8–20B open-weight models on a $7K machine have matched frontier model reasoning on AIME 2025. Here's the orchestrator that makes it work. Today we're publishing the core orchestration engine behind our paper benchmark results. The NSED repository is live at github.com/peeramid-labs/nsed — source-available under BSL 1.1, free for organizations under $1M revenue, research, and education. This post explains what NSED does, why it matters for teams that rely on AI for high-stakes reasoning, and how to run it today.

Visit product View on Hacker NewsFeb 26, 2026

Share card

Actual performance

3points

Did not reach leaderboard

Launch Intel predictions

Analyze your own launch →

Product HuntOn track for Day 1 leaderboard · Strong signals: mac, agent, model · Missing: agents, macos, cursor

92%92% predicted probability of success on Product Hunt, based on ML models trained on real launch data.

best fitHighest predicted score across all platforms for this description.

Indie HackersFits the IH revenue-focused audience · Strong signals: organizations · Missing: supports, reddit linkedin, podcasting

61%61% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.

Hacker NewsStrong engagement from HN community · Strong signals: io · Missing: https docs, excited, just released

54%54% 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 · Strong signals: education · Missing: mobile apps, ios, personal

45%45% 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

38%38% predicted probability of success on AppSumo, based on ML models trained on real launch data.

Acquire.comPre-revenue stage for this audience · Strong signals: revenue · Missing: arr, mrr, profit

30%30% predicted probability of success on Acquire.com, based on ML models trained on real launch data.

BetaListMay not resonate with beta-testers · Missing: web3, chat, crypto

5%5% predicted probability of success on BetaList, based on ML models trained on real launch data.

Incorrect prediction on native model

Similar products

Ida Swarm – Multi-agent AI system for automated reverse engineering57%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

Ida Swarm – Multi-agent AI system for automated reverse engineering

Hacker News1

Rifft40%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

Debugger for multi-agent AI systems

Indie Hackers1ai

Autonomous Research Swarm – Repo as shared memory for multi-agent AI38%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

Autonomous Research Swarm – Repo as shared memory for multi-agent AI

Hacker News1

SidekickBar67%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

Your new multi-agent AI sidekick

Product Hunt+163Productivity

Aida | Multi-AI Orchestrator40%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

Multi-Agent AI platform that orchestrates real business work

Indie Hackers1ai

LIA79%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

Open-source multi-agent AI assistant

Product Hunt

Find where multi-agent AI systems break before production44%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

Find where multi-agent AI systems break before production

Hacker News2

OpenOrb – I built a transparent multi-agent AI tool43%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

OpenOrb – I built a transparent multi-agent AI tool

Hacker News1

Deliberon20%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

Multi-Agent AI Command Center

Indie Hackers1ai

Sellclaw32%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

Sellclaw — Your Multi-Agent AI Personal Assistant for E-comm

Indie Hackers1$10,000/moai

Browse all products Analyze your launch