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Qwen3.7-Max debuts at Alibaba's Cloud Summit in Hangzhou as the company's most capable agent model, sustaining continuous autonomous execution for 35 hours in internal testing.

Google's new efficiency flagship outperforms Gemini 3.1 Pro on most evals while running 4x faster and costing 40% less.

Cloudflare detailed the custom infrastructure behind its Workers AI expansion to host models like Kimi K2.5, including a Rust-based inference engine and a lossless weight-compression system.

The Beijing lab behind Kimi K2.6 raised $2 billion led by Meituan's Long-Z Investments, lifting its valuation to $20 billion and bringing six-month funding to $3.9 billion as ARR cleared $200 million.

Subquadratic launched SubQ on May 5, 2026 with a 12 million token context window and benchmarks it claims undercut Claude Opus by orders of magnitude. AI researchers are split between fascination and accusations of vaporware.

Mistral released Medium 3.5, a dense 128B open-weight model with a 256k context window that consolidates Medium 3.1, Magistral, and Devstral 2 under a Modified MIT license, with a per-query reasoning toggle.

DeepSeek's V4-Pro and V4-Flash arrive with 1M-token context, three reasoning modes, and pricing that undercuts frontier rivals by up to 8x.

OpenAI's GPT-5.5 arrives as a ground-up retrain with a 922K-token context window, 82.7% on Terminal-Bench 2.0, and two-tier pricing starting at $5/$30 per million tokens.

Alibaba's new flagship tops SWE-bench Pro, Terminal-Bench 2.0 and four other coding leaderboards, but ships as a proprietary hosted model rather than an open-weight release.

Moonshot released Kimi K2.6 under a modified MIT license, claiming parity with GPT-5.4 and Claude Opus 4.6 on coding benchmarks while orchestrating agent swarms that run for half a day unattended.

Opus 4.7 lands across Claude, Bedrock, Vertex AI, and Foundry with unchanged pricing, while Anthropic uses it to trial new cyber safeguards before any broader Mythos rollout.

A JAMA Network Open study using the new PrIME-LLM framework finds top AI models excel at final diagnoses with full data but collapse on differential diagnosis when patient information is incomplete.