455 summarised stories about Large Language Models, each linking back to the original source. Browse all topics →
SiliconANGLE 2 months ago 12 ● 8 sources
Google launched Gemini 3.7 Flash, its most capable entry-level model for coding and AI agent projects. It is rolling out 3 weeks after Gemini 3.6 Flash and is priced at half the cost of Gemini 3.6 Flash through the end of the year. Developers get improved coding and UI generation plus added ability to power AI agent ensembles and to browse/use Google services via Gemini Spark.
MarkTechPost 2 months ago 12 ● 8 sources
Google released Gemini 3.7 Flash, a refined update in its Flash tier, for multi-modal input and agent-style use via hosted APIs. It costs $0.75 per 1M input tokens (and $3.75 per 1M output tokens). Pricing drops and deployability remains API/enterprise-only, with reported gains on coding and document-work benchmarks alongside some reasoning regressions.
Product Hunt 2 months ago 11 ● 8 sources
Gemini 3.7 Flash is presented as Google’s workhorse model for coding and agent tasks. No number, benchmark, or date is mentioned in the provided text. As a result, Google is positioning a new Gemini version for developer-oriented AI coding and agent use cases.
The Batch 43 ● 4 sources
DeepSeek released DeepSeek-V4-Flash-0731, a fine-tuned small model that overtook its own DeepSeek-V4-Pro on independent tests. It scored 50 points on Artificial Analysis’ Intelligence Index (max reasoning), up from 44 for DeepSeek-V4-Pro. The update improves agentic performance and lowers per-task costs through the unchanged V4-Flash architecture with new fine-tuning, with weights available under the MIT license and API prices starting at $0.14 per 1 million input tokens.
SiliconANGLE 2 months ago 46 ● 3 sources
SpaceXAI released its Grok 4.6 large language model as its current flagship. Grok 4.6 scored 61 on the Artificial Analysis Intelligence Index. The rollout comes about 1 month after Grok 4.5 and includes an updated training pipeline with longer training plus supervised fine-tuning and reinforcement learning, alongside new $2/$6 per million token pricing.
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TLDRocket
20 October 2026
The biggest AI thread today is Meta’s move from “spend on models” to “own the machine,” with Mark Zuckerberg and Alexandr Wang describing a full-stack strategy and a $100 billion-plus bet that could rise to $200 billion. Meta isn’t waiting for proof before building; it’s scaling its own infrastructure while also plotting monetization beyond ads—commercializing AI compute and deploying agent-style tools like Muse to turn internal capacity into an external revenue stream. It’s a familiar platform play, but with unusually large numbers attached.
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