Tag
long context
Long context refers to an LLM’s ability to keep and use very large histories in one pass, shaping memory design, retrieval, fast-weight updates, and stable reasoning. It shows up in 1M-2M token windows, state-space memory, TTT, and agent workflows.
6 articles
MiniMax-M1 brings 1M-token open reasoning model
MiniMax released M1, an open-source reasoning model with 1M-token context, 80k output, and low-cost API pricing.
Sessa: Attention and State-Space Memory for Long Context
Sessa mixes attention with recurrent state-space feedback to improve long-context recall, with power-law memory tails and strong benchmark results.
In-Place TTT Lets LLMs Adapt at Inference
A new test-time training setup lets LLMs update fast weights in place, aiming for better long-context adaptation without full retraining.
Grok 4.20: xAI's new flagship model explained
xAI’s Grok 4.20 adds a 2M-token context window, multi-agent reasoning, and API pricing from $2 per million input tokens.
Gemini 3.1 Pro: Google’s new top model in numbers
Gemini 3.1 Pro posts 77.1% on ARC-AGI-2, 94.3% on GPQA Diamond, and a 1M-token context window, while keeping Gemini 3 pricing.
Universal YOCO aims to scale depth without cache bloat
YOCO-U mixes recursive computation with efficient attention to scale LLM depth while keeping inference overhead and KV cache growth in check.