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Google DeepMind's cheapest paid Gemini tier prices input at $0.30/M and output at $2.50/M tokens, more than doubling OSWorld-Verified and Terminal-Bench 2.1 scores over Gemini 3.1 Flash-Lite while trailing GPT-5.4 mini on raw coding benchmarks.
Google DeepMind's workhorse Flash model cuts output tokens 17% versus Gemini 3.5 Flash, drops output pricing to $7.50/M, and cuts DeepSWE task tokens by 65% while trailing GPT-5.6 Luna and Grok 4.5 on raw coding scores.
Nonprofit Current AI wants a free, public alternative to Big Tech's AI models, and it has $400 million and a chatbot to show for it so far.
Ex-Google DeepMind researcher Andrew Dai raised $55M at a $300M valuation for Elorian, a visual AI lab with no product yet, joining a growing list of frontier labs priced on pedigree alone.
Google DeepMind's Gemini 3 Pro debuted at 1501 Elo on LMArena with 91.9% on GPQA Diamond and a 1M-token context window, before Google retired it for Gemini 3.1 Pro.
Google DeepMind CEO Demis Hassabis wants a FINRA-style body testing frontier AI models before release, with power to slow the industry down if needed.
Google's hybrid reasoning workhorse pairs a 1M-token context window with $0.30/$2.50 per million token pricing and a toggleable 0-24,576 token thinking budget, now heading toward an October 2026 shutdown.
Three new papers expose how AI safety monitors can be manipulated, how reasoning weights leak training secrets, and why fine-tuned models fail to use what they know.
Anthropic's Claude Science workbench completes a three-way AI battle with Google DeepMind and OpenAI over drug discovery, backed by Nobel laureate John Jumper and 60+ scientific database integrations.
A benchmark-driven comparison of Claude Fable 5 and Gemini 3.5 Flash across coding, agents, pricing, and speed - two models built for opposite priorities.
Google DeepMind's multimodal video generation model that creates 10-second clips with native audio from text, images, or video inputs - and lets you refine results through conversation.
A 57-page DeepMind paper by co-founder Shane Legg identifies four pathways from AGI to superintelligence and six bottlenecks that could block each route.
