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[ARTICLE · art-61054] src=notes.designarena.ai ↗ pub= topic=artificial-intelligence verified=true sentiment=↑ positive

Thinking Machines’ Open Weights Model is Now on Design Arena

Thinking Machines released Inkling, its first open weights model, now available on Design Arena. Inkling ranks #9 on agentic Web Apps leaderboard, making it the top US-based open weights model for agentic workloads. The model excels in token efficiency, fine-tuning, and design tasks like landing pages and data visualization.

read2 min views1 publishedJul 15, 2026
Thinking Machines’ Open Weights Model is Now on Design Arena
Image: Notes (auto-discovered)

We are excited to introduce Inkling, Thinking Machines' first model - and it’s open weights. With this release, Thinking Machines establishes itself as a top 6 lab in agentic workloads. Inkling is the top US-based open weights model, representing a step forward for the open source ecosystem as a whole.

Where it Ranks #

Inkling ranks #9 on our agentic Web Apps leaderboard, just behind Qwen 3.7 Max and at the same tier as Claude Opus 4.6 and Gemini 3.5 Flash. This makes Inkling the highest-ranking US-based open weights model for agentic workloads, achieving frontier-level performance.

Inkling is notably token-efficient, setting a new Pareto frontier in the average number of tokens per task. This makes Inkling especially useful for agentic workloads, achieving similar performance for less tokens.

What Sets Inkling Apart #

Built to Be Fine Tuned

Inkling was designed to be broad, trained across agentic, reasoning, coding, instruction-following, factuality, vision, and audio tasks, rather than narrowly optimizing for one domain. That breadth matters for customization and real-world use, as different users need models that can adapt to very different workflows. It also makes Inkling one of the best models for fine-tuning, as it has a broad knowledge base that can be adapted to different tasks and organizations.

Efficient Open Weights

Inkling supports controllable thinking effort, allowing users to balance performance with token efficiency. Cost and latency matter for a model that users run millions of times and as part of longer workflows; looking at the full cost curve allows developers to choose the best model for each use case. Inkling is notably token-efficient for its performance, and sets a new Pareto frontier for token efficiency on agents.

Beautiful Landing Pages #

Inkling performs especially well when crafting hero images and headers, making it a perfect candidate for producing beautiful landing pages. It avoids antipatterns like purple gradients and emojis in hero headers, while using golden accents and elegant typography to craft enthralling user experiences.

Strong 3D Design #

Inkling shows strong 3D design skills, especially when it comes to hero decorations. By using libraries like three.js, it’s able to craft intricate hero images that feel quality without having to rely on external dependencies.

Data Visualization #

Inkling generates clean, beautiful dashboards that present data in a hierarchical, easy-to-understand manner. It presents thoughtful layout designs and impressive visuals, keeping data visualizations clean and understandable.

Marketing Materials #

Inkling also displays strong performance in generating marketing materials, creating websites that retain consistent styling and tone throughout the generation. It also excels at copywriting, crafting compelling messages that provide useful information while engaging readers.

Congratulations to the Thinking Machines team for this achievement, and view Inkling’s full performance profile on Design Arena.

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