Z.ai Releases GLM-5.3-Flash: A 320B-A18B Natively Multimodal MoE With a 1M-Token Context
Z.ai has released GLM-5.3-Flash, the first natively multimodal model in the GLM-5 series and the cheapest capable coding model the lab has shipped. It is a mixture-of-experts model with 320B total parameters and 18B active per token, a 1,048,576-token context window, and image and video input — released under an MIT license with weights on Hugging Face. According to Z.ai reports, it beats GLM-5.2 across benchmarks and real workloads at roughly one-tenth the price, while landing within half a po
Z.ai released GLM-5.3-Flash, a new artificial intelligence model designed to handle multiple types of input including text, images, and video. The model uses a mixture-of-experts architecture with a very large context window that allows it to process over one million tokens at once, and it performs comparably to other leading models while costing roughly one-tenth the price of its predecessor. The model matters because it makes capable AI more accessible and affordable for applications like coding, document analysis, and automation tasks, with deployment options available both through a hosted API and through self-hosting for organizations with sufficient hardware resources. The efficiency gains come from architectural innovations including a hybrid attention system that combines linear and sparse attention methods, a compression technique called IndexPool that reduces memory requirements at large context sizes, and design changes that reduce the number of active parameters needed per token.
Explainer: What Is a Mixture of Experts Model and Why Does It Use Fewer Resources?
One short email a day with the stories that matter. Free. Unsubscribe with one click.
Want to go deeper than the news? Explore live, cohort-based AI courses taught by practitioners.
Browse AI courses on Maven
Anthropic releases new Mythos and Fable models amid RSI concerns
Anthropic says the new models "show improvements in areas like coding, reasoning, and vision," as well as in communicating more clearly with users.
Also reported by The Verge, SiliconANGLE and MarkTechPost
Google Launches Gemini Decisions API With Gemini Decision 1 at $0.10/M Tokens
Google has launched the Gemini Decisions API, powered by a new model, Gemini Decision 1 (gemini-decision-1). The Gemini Decisions API does not generate text. It scores up to 1,000 typed questions against one shared input and returns calibrated probabilities. For developers, this targets the small branching calls inside agents: routing, policy checks, tool selection and grading. Google prices it at $0.10 per 1M input tokens, with zero output tokens billed. TL;DR Size: Context is 262,144 t
Also reported by SiliconANGLE
Google releases Gemini 4 Carbon with agent ‘swarm’ feature
Google is rolling out its latest AI model, Gemini 4 Carbon, to the general public after releasing it to a select group of "cybersecurity defenders" two weeks ago. Google claims Carbon is its "strongest model" yet, and capable of competing with the very best systems from Anthropic and OpenAI. Google says Gemini 4 Carbon "pushes the frontier even further" than Argon, referring to the company's other frontier model that launched only last month. The company said Argon will likely
Gemini 4 Carbon is now available
The latest version aims to deliver improved performance while reducing the computational resources and energy required for AI operations.
Introducing AlphaProof Code: a breakthrough in verifying complex software at depth
AlphaProof Code agents wrote three million lines of proofs in Lean to verify Signal’s core encryption.
NVIDIA launches GR00T 2 and Isaac Lab 3.0 at CoRL
A range of developers, including RLWRLD, Skild AI, and Flexion, are already using NVIDIA’s latest technology. | Source: NVIDIA NVIDIA Corp. today introduced GR00T 2, its updated open frontier world action model, and Isaac Lab 3.0, the latest version of its open-source robot learning framework. The company made these announcements at the Conference on Robot Learning, or CoRL, in Austin, Texas. NVIDIA also gave a look at how its partners, like Ambi Robotics, Bosch Research, Dexmate, Dyna Rob