
Databricks Hits $188B While Defaulting to Chinese AI for Code
Databricks signed a term sheet for a $188 billion valuation days after quietly making a Chinese open-weight model its default coding engine over Anthropic.
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Databricks signed a term sheet for a $188 billion valuation days after quietly making a Chinese open-weight model its default coding engine over Anthropic.

PrismML compressed a 27B-parameter Qwen model from 54GB to under 4GB using 1-bit and ternary weights, and Apple is evaluating the technology for on-device Siri.

Bonsai 27B compresses Alibaba's Qwen3.6-27B into 1-bit and ternary weights, shrinking a 54GB model to as little as 3.9GB so it runs on an iPhone.

Moonshot's Kimi K3 tops LMArena's Frontend Code Arena and undercuts Opus 4.8 on cost per task, but a tripled price tag, a rising hallucination rate, and an unresolved distillation question complicate the win.

LM Studio launched Bionic, a standalone agent app that routes coding and document work between local open models and a Zero Data Retention cloud tier.

Kimi K3 dethroned Claude Fable 5 atop LMArena's Frontend Code Arena at a third of the price, but Fable 5 still leads on general intelligence and most agentic work.

Moonshot AI's Kimi K3 jumped 17 spots to #1 on LMArena's Frontend Code Arena, but the win comes with a tripled price tag and a weaker showing on broader intelligence benchmarks.

Moonshot AI's Kimi K3 is a 2.8 trillion parameter MoE model that tops LMArena's Frontend Code Arena and nears Claude Fable 5 on intelligence benchmarks, but at roughly triple Kimi K2.6's price and a higher hallucination rate.

China's internet regulator approved Apple Intelligence for the local market, but only after Apple agreed to run Alibaba's Qwen and Baidu's models instead of its own.

Snowflake's reasoning-first text-to-SQL model tops the BIRD benchmark at 71.83% execution accuracy, trained with GRPO and a reward that only checks if the SQL runs correctly.

Mira Murati's Thinking Machines Lab released its first open-weight model, Inkling, and published benchmarks showing it losing to closed rivals on most of them.

Thinking Machines Lab's first open-weight model - a 975B-parameter MoE with native text, image, and audio reasoning, released under Apache 2.0 and tuned for customization on the Tinker platform.