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- China's AI Model Race Heats Up as a Coding Startup Hits $1.5B Unicorn Status
China's AI Model Race Heats Up as a Coding Startup Hits $1.5B Unicorn Status
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China's AI labs kept the pressure on this week, with Moonshot, Alibaba, and DeepSeek all pushing frontier-scale open models within days of each other — while on the funding side, a one-year-old AI coding startup just became a unicorn five times over. Here's what founders, execs, and builders need to know today.
Today's Top Stories
Moonshot AI Launches Kimi K3, the World's Largest Open-Weight Model
Moonshot AI unveiled Kimi K3, a 2.8 trillion-parameter open-weight model it says is the largest of its kind, built for long-horizon coding and reasoning work with a 1M-token context window. Founder Yang Zhilin presented it at NVIDIA's GTC 2026, positioning it as a direct challenger to OpenAI and Anthropic. Full weights land July 27.
Alibaba Fires Back With Qwen3.8-Max-Preview
Alibaba unveiled Qwen3.8-Max-Preview, a 2.4 trillion-parameter model it claims trails only Claude's Fable 5 in capability. It's live now on Alibaba's Token Plan subscription tiers, with open weights expected to follow — continuing the rapid parameter-count escalation among Chinese labs.
DeepSeek Set to Launch V4 With Novel Peak-Valley Pricing
DeepSeek is expected to release its V4 model as early as Monday, with performance said to approach GPT-5.6. The launch introduces "peak-valley" pricing — cheaper API rates during off-peak hours — a first for a major Chinese AI lab, alongside steep discounts on repeated queries.
Emergent Raises $130M Series C at $1.5B Valuation
AI software creation platform Emergent closed a $130M Series C led by Creaegis, with Khosla Ventures, SoftBank Vision Fund 2, Lightspeed, and Y Combinator participating. The round quintuples Emergent's valuation in just four months, making it a unicorn roughly one year after launch.
Thinking Machines Lab Releases Inkling, a 975B-Parameter Open Model
Thinking Machines Lab launched Inkling, a 975 billion-parameter open-weight model with a DeepSeek-V3-inspired mixture-of-experts design, activating 41B parameters per token. It requires a hefty 2TB of GPU memory at full precision, with a lighter version available and paid fine-tuning through the company's Tinker platform.
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