8 results for “1m context window”
Related topics1m context window
Jul 26
Moonshot open-sources Kimi K3, a 2.8T model with a million-token window
Ten days after the API launch, Moonshot released the open weights for Kimi K3 — 2.8T parameters (about 50B active), a 1M-token context, and a new hybrid-linear-attention architecture (KDA) shipped natively in 4-bit MXFP4. It resets what the open-weight frontier means: the interesting axis is no longer raw knowledge but how cheaply a model stays coherent across a million tokens.
Feb 24
Claude's 1M Tokens & 90% Recall: What It Solves, What It Doesn't
Anthropic's Claude Opus 4.6 offers a 1M token context window, but its real value lies in its claimed 90% recall. This article explores when this massive context replaces RAG and when it's an expensive distraction.
Mar 19
Gemini 3.1 Pro: Is a 1M Token Window Worth a Blind Upgrade?
Google's Gemini 3.1 Pro was released in February 2026 with a 1M token context window but few performance details. This article provides a production-focused framework for deciding whether to upgrade your AI stack to a new model when vendor benchmarks are missing.
Jul 29
2.8 Trillion Parameters, Free to Download: Inside Moonshot AI's Kimi K3
Kimi K3 packs 2.8 trillion parameters but activates only 104 billion per token — and Moonshot AI put the full weights on Hugging Face eleven days after announcing it.
Jan 13
Codex-Max and the $100+ Mistake 24 Hours In
GPT-5.1-Codex-Max can code autonomously for over 24 hours, but this power introduces new risks. This article explores the economics of long-horizon tasks and how to architect systems that prevent costly, deep-rooted errors.
Nov 07
The 1M Token Budget: Why 1 in 10 Queries Fail at Scale
Large context windows are not a free upgrade; they are a budget with steep costs in money, latency, and accuracy. This article explains the three hidden costs of long context and provides a framework for deciding when to use it.
Apr 30
The Trillion-Parameter Tipping Point: Open-Weight AI Is Now a C-Suite Decision
As of April 2026, open-weight models with over a trillion parameters rival proprietary APIs in capability, forcing a new strategic decision for enterprises. This article breaks down the choice across four critical axes: data control, capability, cost, and the upgrade cycle.
Jul 28
Kimi K3: a 2.8-trillion-parameter open model that bets on linear attention
Moonshot's new open-weight flagship isn't chasing a leaderboard — it's a bet that a cheap million-token context changes what we build. What actually changed under the hood, how to run it, and where it sits against the open-weight frontier.