// ZDNET — INTELLIGENZA ARTIFICIALE
Thinking Machines’ new model takes the lead in western open-weight AI
Another competitive model developed outside of China could change the open-weight landscape.
Thinking Machines Lab, a small AI startup from ex-OpenAI CTO Mira Murati, has released its latest model, Inkling 2 Small — and according to third-party tester Artificial Analysis, it’s set to give Chinese models a run for their lead. It’s technically proprietary until now, but Thinking Machines said it will release its weights next week.
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Chinese companies have led the pack on open models over the last few years. Models from DeepSeek and Moonshot regularly top leaderboards and rival the capabilities of much more expensive, closed models from OpenAI and Anthropic.
Since DeepSeek’s R1 performed similarly to OpenAI’s o1 in January 2025, Chinese open models have given investors and high-paying enterprise customers reasons to rethink their expensive contracts with US-based labs. Western labs creating more competitive open models changes the landscape.
Thinking Machines’ latest model has 594 billion parameters and supports image inputs but outputs only text. The company noted its web and game design capabilities and that it evaluated the model’s approach to coding problems alongside the code it generated during testing.
“The result is a model that is both stronger at coding and easier to use inside real agent loops,” the company said.
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Inkling 2 Small scored a 31 on the Artificial Analysis Intelligence Index, a composite test “for tracking progress toward artificial general intelligence” that combines benchmark scores spanning coding, science, and general categories. A score of 31 is above average for models in its class and is tied with Gemini 3.8 Flash. For context, Gemini 4 Carbon and Claude Opus 5.5 top the index at 60 and 59, respectively.
Thinking Machines said it will release the model’s weights next week, a practice that is becoming customary. Given the heightened security concerns around AI in general, AI companies spend a few weeks testing the to-be-open model with cybersecurity teams and safety reviewers before releasing the weights, rather than leading with the weights out of the gate.