Thinking Machines releases Inkling 2 Small AI model
MarkTechPost: Thinking Machines Releases Inkling 2 Small, a 594B MoE With 17B Active
Thinking Machines Lab has released Inkling 2 Small, the first model of its second Inkling generation. The Inkling 2 Small model is a sparse Mixture-of-Experts (MoE) with 594B total and 17B active parameters. It accepts text and images, and supports variable reasoning effort. On the Artificial Analysis Intelligence Index, it scores 31. Its predecessor, Inkling Small, scores 13 on the same index. The model is live on Tinker for fine-tuning and inference. TL;DR Size: 594B total, 17B active
What happened
Thinking Machines Lab released Inkling 2 Small, a multimodal AI model with 594 billion total parameters and 17 billion active parameters that accepts text and images. The model scores 31 on the Artificial Analysis Intelligence Index, more than double its predecessor's score of 13. Around the same time, Business Insider reported that Thinking Machines is in the process of raising $5 billion in funding at a reported $40 billion valuation.
What each outlet adds
- MarkTechPost ↗: The model is currently available for fine-tuning and inference on Tinker with pricing at $0.30 per million input tokens and $1.00 per million output tokens, with weights remaining closed pending external safety testing.
- SiliconANGLE ↗: The company was founded by a former OpenAI Chief Technology Officer and the $5 billion funding round is reportedly led by Accel.
Why it matters
The model performs particularly well on coding and enterprise tasks, and can learn from custom data more efficiently than earlier versions. The simultaneous product launch and major funding round signal significant momentum for the company in the competitive AI market.
Get smart on it
Thinking Machines Lab released Inkling 2 Small, a new multimodal AI model that accepts text and images as input and uses a sparse Mixture-of-Experts architecture with 594 billion total parameters but only 17 billion active at any time. The model scores 31 on the Artificial Analysis Intelligence Index, more than double its predecessor's score of 13, and performs particularly well on coding and enterprise tasks. It is currently available for fine-tuning and inference on Tinker with pricing at $0.30 per million input tokens and $1.00 per million output tokens, while weights remain closed pending external safety testing before an open release is planned.
Explainer: What Is a Mixture of Experts Model and Why Does It Use Fewer Resources?
Relevant courses
Want to go deeper than the news? Explore live, cohort-based AI courses taught by practitioners.
Browse AI courses on MavenRelated news
Why a new report on Anthropic automating AI development is alarming researchers
Anthropic CEO Dario Amodei. | Photo: Jason Henry/Bloomberg via Getty Images Anthropic is using AI to build more powerful AI. And it appears to be working remarkably well, with the company's models improving roughly twice as quickly as a year ago, with little indication of slowing down. That's according to a new report published Thursday by the AI safety research organization METR, following an 11-week investigation inside the company, as part of a report evaluating its AI resear
Google Releases Gemini Omni 1.2 Flash: 15-Second AI Video at $0.07 per Second
Google has released Gemini Omni 1.2 Flash, the newest version of its video generation and editing model. Gemini Omni 1.2 Flash generates and edits clips up to 15 seconds natively. It also cuts the price by 30% compared with Omni 1.1 Flash. The model is generally available on Google Cloud and the Gemini API. For developers, the takeaways are longer clips, fewer re-renders and a lower bill per second. TL;DR Runs on: Google-hosted only (Gemini API, Google Cloud). No open weights, no local d
Also reported by Google DeepMind
GPT‑6 Cyber: Advancing the frontier of aligned cybersecurity agents
Introducing GPT‑6 Cyber, OpenAI’s cybersecurity model for finding exploitable vulnerabilities and developing fixes, trained to stay within authorized scope.
Tencent releases Hy4, powerful frontier LLM introducing visual understanding and computer use
Tencent Holdings Ltd. today introduced Hy4, a new large language model that adds computer-use capabilities for the first time, using advanced visual understanding, reasoning and tool-calling to deliver long-horizon agentic performance. The company said the model marks a significant leap in performance over its Hy4 Preview, which arrived August 28, weighing in at 770 billion parameters with 49 […] The post Tencent releases Hy4, powerful frontier LLM introducing visual understanding and comp
OpenAI says its new cybersecurity model is better at not hacking other companies
OpenAI is launching GPT-6 Cyber, the latest version of its cybersecurity AI model, which it says is better at finding vulnerabilities and less likely to go rogue and hack other platforms in the process. OpenAI says that during testing, GPT-6 Cyber went out of bounds less than 1 percent of the time, down from around 5 percent with GPT-5.6 Cyber. The evaluation, called ExploitGym HoneyPot, is modeled after the Hugging Face Incident, in which OpenAI's AI agents breached the open-s
Also reported by TechCrunch
Baidu Releases ERNIE 5.5 Flash Base: A 280B MoE Base Model With 14B Active Parameters
Baidu has released ERNIE 5.5 Flash Base, the raw pre-training checkpoint of its new sparse Mixture-of-Experts language model. ERNIE 5.5 Flash Base is a 280B-parameter text model from Baidu that activates 14B parameters per token. The weights stop at the end of pre-training, with no mid- or post-training applied. This as a clean starting point for teams that want to compare fine-tuning, instruction tuning or RL methods from one checkpoint. TL;DR Size: 280B total, 14B active per token; 128