Daily Digest
Ant Group's Ling-3.1-flash is open weights under MIT
inclusionAI published Ling-3.1-flash on Hugging Face under MIT: 560B total parameters, 25B active, and a 1M-token context on the model card.
Littlewolf Labs
inclusionAI, Ant Group's AI lab, published Ling-3.1-flash on Hugging Face under MIT. Mixture-of-experts, 560B total / 25B active parameters, 1M-token context per the model card. Card benchmarks are inclusionAI's own: Terminal-Bench 4.0, SWE-bench Pro, FrontierSWE, GDPVal-AA. X posts highlight website, UI and 3D-prototype generation, but those are early impressions.
What it costs
Weights free, but recommended server is 8x H200, not a home-PC model. On OpenRouter, DeepInfra lists $0.30/M input, $0.90 output; Novita shows $0.075/$0.225 with a 75% discount applied, both at 262K context.
Should you switch
Cheap API option worth testing for coding agents and UI prototypes; run locally only with datacenter GPUs.
Affiliate disclosure: some stories use affiliate or referral links. When a link pays a commission, the sentence next to it says so. Sponsored slots are labeled Sponsored. The channel card is a house ad until a sponsor is booked.
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