
Quantization's Hidden Tax, Cliff Tokens, Smarter Memory
Three new arXiv papers reveal hidden costs in quantized reasoning models, single-token failure triggers, and a new framework that cuts agent memory errors by up to 79%.
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Three new arXiv papers reveal hidden costs in quantized reasoning models, single-token failure triggers, and a new framework that cuts agent memory errors by up to 79%.

Sakana Fugu tops SWE-Bench Pro by routing tasks across rival LLMs, Microsoft's 9B browser agent beats OpenAI Operator, and a 3B model from Weibo matches DeepSeek V3.2 on math.

WeiboAI's 3B dense reasoning model fine-tuned from Qwen2.5-Coder-3B, posting AIME 2026 scores that match DeepSeek V3.2 (671B) using the Spectrum-to-Signal training pipeline.

Baidu's ERNIE 5.1 is a text-focused MoE model that claims the top Chinese model slot on LMArena with 800B parameters built at 6% of comparable training costs.

Three arXiv papers: a conscience mechanism for ethical training, shared memory for agent populations, and selective verification that cuts test-time compute waste.

Pramaana Labs uses the LEAN proof language to attach a mathematical certificate to every AI answer in high-stakes domains like tax, law, and drug discovery.

GPT-5.1 is OpenAI's November 2025 coding and agentic flagship with 400K context, configurable reasoning effort, and 76.3% on SWE-bench Verified.

Moonshot AI's Kimi K2.7-Code is a 1T-parameter open-weight MoE coding model with mandatory thinking mode, 256K context, and 30% fewer reasoning tokens than K2.6.

A hands-on review of all seven MAI models - from the April transcription and image launch to Build 2026's MAI-Thinking-1, MAI-Code-1-Flash, and the multimodal upgrades.

Microsoft's first in-house reasoning model, a 35B-active sparse MoE with 256K context, 97% on AIME 2025, and no distillation from third-party labs.

Three new arXiv papers expose how context bloat tanks agent performance, agent memory bleeds private data, and misaligned behavior spreads through multi-agent systems.

Anthropic's Claude Opus 4.8 scores 69.2% on SWE-bench Pro and ships hundreds of parallel subagents in Claude Code, with pricing unchanged at $5 per million input tokens.