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Test-Time Compute

4 articles · Page 1 of 1
Architect
Architect
Sep 7, 2026 · Artificial Intelligence

Loop Tech Behind GPT-6 Astra: Recurrent Depth, Trade-offs & Agent Verification

This article traces the Loop architecture lineage from Universal Transformer to recurrent depth, examines engineering challenges like placement, state drift, dynamic stopping, and KV cache, and argues that as internal computation decouples from parameters and visible reasoning, Agent verification must rely on external evidence like tests, approvals, and versioned artifacts rather than chain-of-thought alone.

Agent VerificationGPT-6 AstraKV Cache
0 likes · 25 min read
Loop Tech Behind GPT-6 Astra: Recurrent Depth, Trade-offs & Agent Verification
Ops Development & AI Practice
Ops Development & AI Practice
Jul 28, 2026 · Artificial Intelligence

How Open-Source Kimi K3 Challenges the Commercial Survival of Top Large Models

Kimi K3, an open‑source LLM with 2.8 trillion parameters and a 57‑point intelligence score, outperforms many closed‑source rivals in benchmarks but suffers from a 40‑second first‑token delay and $0.72 per‑task cost, exposing the steep Test‑Time Compute hurdle that reshapes the AI market’s competitive landscape.

AI market competitionKimi K3Test-Time Compute
0 likes · 8 min read
How Open-Source Kimi K3 Challenges the Commercial Survival of Top Large Models
Machine Heart
Machine Heart
Jun 30, 2026 · Artificial Intelligence

Why One Extra Loop Is All a 7B Model Needs – LoopCoder‑v2’s Surprising Sweet Spot

LoopCoder‑v2, a 7B LLM, gains a massive boost on SWE‑bench Verified (43.0 → 64.4) by adding just one test‑time loop, while additional loops cause performance to collapse, a finding explained through detailed probe analysis of hidden‑state convergence, attention re‑routing, and a constant “position‑mismatch tax”.

AI model efficiencyLLM loopingLoopCoder-v2
0 likes · 8 min read
Why One Extra Loop Is All a 7B Model Needs – LoopCoder‑v2’s Surprising Sweet Spot
Top Architect
Top Architect
Jun 13, 2026 · Artificial Intelligence

What Is an Inference Large Language Model? A Visual Guide

The article explains inference‑type large language models, how they differ from traditional models by breaking questions into reasoning steps, the shift from training‑time to test‑time compute, scaling‑law insights, validation techniques, proposal‑distribution tricks, and the detailed training pipeline of DeepSeek‑R1, while also discussing failed experiments and future directions.

DeepSeek R1Large Language ModelsTest-Time Compute
0 likes · 20 min read
What Is an Inference Large Language Model? A Visual Guide