Baseten vs Groq

Goodfire Launches Internal AI Agent Monitors

Goodfire, a startup specializing in AI interpretability, launched on Thursday a new type of AI agent monitor that inspects a model's internal signals rather than reading its output, aiming to detect rogue behaviors more efficiently and at a fraction of the cost. The monitors are available to customers of Baseten, an AI model hosting platform. Baseten's Base Labs had previously announced a safety partnership with Goodfire and Hugging Face. Goodfire's approach uses small probes that scan a model's internal activations at each step, triggering a closer AI review only when flagged. In tests on the Kimi K3 model, Goodfire's monitors caught 94% of malicious hacking sessions and cost about $51 for 1,500 sessions, compared to $233 for a cheaper model and $10,000 for a top-tier one. The company positions the solution for open models, which can be stripped of safeguards, and sees it as critical for inference-time guardrails.

• Goodfire launched internal activation monitors for AI agents on October 8, 2026.
• Monitors are available to Baseten customers.
• In tests on Kimi K3, monitors caught 94% of malicious hacking sessions.

Announcing our partnership with OpenAI

Baseten announces a partnership with OpenAI, as featured on their blog.

Baseten, Hugging Face, Goodfire Partner for AI Safety

Baseten's research arm, Base Labs, announced a partnership with Hugging Face and Goodfire AI to establish a safety standard for open-weight AI models. The collaboration aims to develop and publish methods for training and monitoring these models, making safety an integrated feature rather than an afterthought. This comes amid rising concern over 'abliteration,' a technique that removes safeguards from open models, with Hugging Face listing over 6,000 such models. The companies have not detailed technical specifics, but Goodfire's expertise in AI interpretability is expected to play a key role. This initiative seeks to leverage openness as an advantage for safety, providing transparent controls and encouraging community contributions.

• Baseten launched a safety infrastructure standard via Base Labs.
• Partnership with Hugging Face and Goodfire AI announced.
• Hugging Face hosts over 6,000 abliterated models.

Hardware Specialization Returns For AI Inference Era

The a16z newsletter article revisits the historic debate between general-purpose and specialized chips, arguing that the pendulum has swung back in favor of specialized hardware for AI inference. It details how general-purpose CPUs won in the 1990s due to volume-driven performance gains, but shifts to GPUs and the end of Dennard scaling changed the landscape. The article highlights that specialized chips like Nvidia's LPU (formerly Groq), Cerebras, and d-Matrix are now complementary to GPUs, delivering better performance per watt for heterogeneous inference workloads. It reports that GPUs have surpassed CPUs in revenue, and that inference demand is expected to grow 24x while power availability only doubles by 2030. The author, from Gimlet, advocates for orchestrating diverse accelerators to maximize efficiency.

• GPUs generated more revenue than CPUs for chip companies.
• Nvidia acquired Groq, now known as Nvidia's LPU.
• Inference demand is projected to increase 24x from 2026 to 2030, while power availability only doubles.

Nvidia's $20B Groq Deal Faces Stockholder Lawsuit

A lawsuit filed by former Groq engineers Joshua Rubin and Benjamin Serebrin alleges that Nvidia's $20 billion deal with Groq "squeezed out" stockholders. The complaint, filed on October 2 at the Delaware Court of Chancery, claims the deal offered a "lowball" price and that Groq's board approved the transaction without a required stockholder vote. The lawsuit argues that a conflicted board cost stockholders billions of dollars, pointing to $17 billion allocated to a non-exclusive license and $3 billion in Nvidia RSUs for employees. Groq dismissed the lawsuit as "meritless," stating the licensing agreement with Nvidia delivered exceptional value. Nvidia has not commented. The deal, announced in December, involved a licensing agreement for Groq's inference technology, with CEO Jonathan Ross and other leaders joining Nvidia, but Groq remains an independent company.

• Former Groq engineers Joshua Rubin and Benjamin Serebrin filed a lawsuit on Oct. 2 alleging Nvidia's $20B deal with Groq shortchanged stockholders.
• The lawsuit claims Groq's board approved the transaction without a required stockholder vote and that the deal cost stockholders 'billions of dollars.'
• The deal allocated $17 billion for a non-exclusive license and $3 billion in Nvidia RSUs for moving employees.

Groq Founder: Poor Leadership Cost Company Years

Jonathan Ross, founder of AI chip maker Groq, admitted in a podcast that his management failures initially cost the company three to four years. A former Google engineer, Ross founded Groq in 2016 to develop Language Processing Units (LPUs) as alternatives to Nvidia GPUs. He acknowledged being 'a terrible leader' at the start, citing mistakes in hiring employees who were not self-sufficient and giving them too much responsibility, leading to stagnation. He learned to focus on people management and became more selective in hiring. In December 2025, Nvidia signed a $20 billion licensing and talent deal with Groq, after which Ross and other key engineers moved to Nvidia, where Ross now serves as chief architect for software. Groq continues as an independent company led by Adam Winter. Similar leadership challenges were shared by Figma CEO Dylan Field and Duolingo CEO Luis von Ahn.

• Jonathan Ross founded Groq in 2016 to develop AI inference chips (LPUs) as alternatives to Nvidia GPUs.
• Ross admitted that his poor leadership set back Groq by three to four years.
• In December 2025, Nvidia signed a $20 billion license and talent deal with Groq.