Crusoe and Thinking Machines Lab partner to power open-model inference at scale. The AI lab will run its production workloads on Crusoe Managed Inference, tuned for throughput, price-performance, and reliability. September 23, 2026 11:07 ET | Source: Crusoe SAN FRANCISCO, Sept. 23, 2026 (GLOBE NEWSWIRE) - Crusoe, the industry's first vertically integrated AI infrastructure provider, and AI innovator Thinking Machines Lab today announced a $65 million annual agreement to power inference for the lab's open models on Crusoe Cloud. Through Crusoe Managed Inference, Thinking Machines Lab will serve a range of production workloads - including its Inkling models, GLM 5.2 and 5.3, and its own fine-tuned variants - on a dedicated Tailored Deployment of NVIDIA HGX B200 systems connected with NVIDIA Quantum-2 InfiniBand networking, engineered for high-throughput, cost-efficient serving at scale. "Crusoe Managed Inference took us from evaluation to production quickly and met the standards we hold our own systems to, giving us the scale and economics to reinvest in the research at the core of what we do," said Myle Ott, ML Infra Lead at Thinking Machines Lab. "Thinking Machines Lab has a very sophisticated engineering team that expects partners to meet their high bar as they grow," said Erwan Menard, SVP, Product Management of Crusoe Cloud. "Our team of leading AI engineers built Crusoe Managed Inference to deliver cost-efficient, reliable infrastructure, inference, and model lifecycle tooling as-a-service, so innovative companies can run their favorite models in production at scale, relying on our expertise." Crusoe will run and support the cluster directly as a Tailored Deployment - a dedicated, benchmarked, SLA-backed endpoint - giving Thinking Machines Lab the price-performance and headroom to scale without managing its own inference stack. The companies are also looking to expand into batch inference for large-scale synthetic data generation, turning inference into a flywheel for research. Thinking Machines Lab joins a roster that has taken Crusoe Managed Inference past $100 million in contracted ARR less than a year from launch. About Crusoe As the AI factory company, Crusoe is on a mission to accelerate the abundance of energy and intelligence. The company provides a reliable, scalable, cost-effective, energy-first solution for AI infrastructure. By harnessing large-scale energy sources, building AI-optimized data centers, and delivering a powerful AI cloud platform, Crusoe empowers its customers and partners to build the future faster. For more information, visit crusoe.ai.

Thinking Machines Lab seeks $40B valuation as Nvidia extends its capital allocator role into model-space. Thinking Machines Lab, the AI startup founded by former OpenAI CTO Mira Murati, is in talks to raise between $5 billion and $6 billion at a pre-money valuation of at least $40 billion. Nvidia is separately in discussions to invest approximately $2.5 billion, while existing backer Accel is reportedly in talks to lead the round. The valuation represents a significant correction from the company's previous fundraise ambitions. Thinking Machines had sought a $50 billion to $60 billion valuation in a round that collapsed earlier this year, with three co-founders returning to OpenAI. The current talks price the lab at 3.3 times its July 2025 seed round, which raised $2 billion at a $12 billion valuation led by Andreessen Horowitz with participation from Nvidia, AMD, Cisco, ServiceNow, Accel, and Jane Street. The Nvidia dimension is what makes this more than a fundraise story. The chipmaker's reported $2.5 billion investment in Thinking Machines completes a five-week pattern of model-space capital deployment that has no historical precedent from a hardware company. Nvidia's reported $12.9 billion acquisition of Hugging Face (Aug 26-27) targeted model distribution. Its investment in SSI (Jul 28) backed safety-aligned frontier research. Its $30 billion-plus investment in Perplexity (Aug 24) bet on AI-native search. And now the Thinking Machines talks target open-weights frontier infrastructure. Each investment occupies a different layer of the emerging AI stack. Together they suggest Nvidia is no longer content to sell compute to frontier labs. It is becoming the capital allocator that determines which of them survive and on what terms. The partnership infrastructure reinforces the pattern. In March 2026, Thinking Machines and Nvidia announced a multiyear arrangement under which the lab will deploy at least one gigawatt of Nvidia's next-generation Vera Rubin systems, with first rollout targeted for early 2027. Capital investment and hardware supply are no longer separate conversations. For Thinking Machines, the round arrives at a critical juncture. The lab shipped Inkling-Small on July 15 - a 276 billion-parameter open-weights model with 12 billion active parameters that scored 80.2 percent on SWE-Bench Verified and 64.7 percent on Terminal Bench 2.1. The Tinker fine-tuning-as-a-service platform launched alongside it, positioning the lab to generate recurring revenue from enterprise customization rather than relying on inference fees alone. The open-weights positioning carries strategic weight in the current market. Thinking Machines is the only US-based lab shipping frontier-class open-weights models that compete directly with Chinese releases from DeepSeek, Moonshot, Qwen, and GLM on both capability and price. For investors weighing geopolitical risk and supply-chain provenance, that distinction commands a premium - though it has not yet translated to the valuations the company once sought. The repricing from $50-60 billion to "at least" $40 billion tells its own story. The failed round earlier this year was not just a financing miss. The departure of three co-founders back to OpenAI signaled organizational turbulence that makes this second attempt a credibility test as much as a capital raise. Whether the lower valuation reflects broader market cooling, company-specific concerns, or both, the number itself becomes a signal for how the market is pricing frontier-lab risk in late 2026. The deal has not closed. All reports describe ongoing discussions, and the final structure - whether Nvidia's $2.5 billion is part of the $5-6 billion total or sits alongside it - remains unclear. Accel and Thinking Machines have not commented. What to watch: whether the round closes at or above the reported $40 billion floor, and how Nvidia's dual role as hardware supplier and equity investor shapes Thinking Machines' deployment timeline for the Vera Rubin systems commitment.

Thinking Machines Lab aims to raise $1 billion at $40 billion valuation, the Information reports. Published on 09/03/2026 at 03:08 pm EDT or by email NVIDIA Corporation is the world leader in the design, development, and marketing of programmable graphics processors. The group also develops associated software. Net sales break down by family of products as follows: - computing and networking solutions (89%): data center platforms and infrastructure, Ethernet interconnect solutions, high-performance computing solutions, platforms and solutions for autonomous and intelligent vehicles, solutions for enterprise artificial intelligence infrastructure, crypto-currency mining processors, embedded computer boards for robotics, teaching, learning and artificial intelligence development, etc.; - graphics processors (11%): for PCs, game consoles, video game streaming platforms, workstations, etc. (GeForce, NVIDIA RTX, Quadro brands, etc.). The group also offers laptops, desktops, gaming computers, computer peripherals (monitors, mice, joysticks, remote controls, etc.), software for visual and virtual computing, platforms for automotive infotainment systems and cloud collaboration platforms. Net sales break down by industry between data storage (88.3%), gaming (8.7%), professional visualization (1.4%), automotive (1.3%) and other (0.3%). Net sales are distributed geographically as follows: the United States (46.9%), Singapore (18.2%), Taiwan (15.8%), China and Hong Kong (13.1%) and other (6%). Mean consensus Number of Analysts Last Close Price 230.36 USD Average target price 327.13 USD Spread / Average Target