Open weights 975B multimodal model built for fine-tuning
Inkling is Thinking Machines’ first open-weights model, a 975B MoE with 41B active parameters, 1M context, native reasoning across text, images, and audio, and controllable thinking effort. Fine-tune it on Tinker or download the Apache 2.0 weights.
Inkling is the first model from Thinking Machines.
It is a 975B MoE with 41B active parameters, a 1M-token context window, and native reasoning across text, images, and audio. The full weights are available under Apache 2.0.
Thinking Machines is clear about what Inkling is for. They say directly that it is not the strongest model available today. It is meant to be a broad base that can be adapted to a specific product or workflow.
You can control how much thinking it uses, fine-tune it on @Tinker, and deploy the resulting checkpoints through several inference providers.
They even had Inkling write and run its own fine-tuning job, turning itself into a model that avoids the letter “e”.
The bet is that a model shaped around your own work can be more useful than a slightly higher score on a temporary leaderboard.
About Inkling on Product Hunt
“Open weights 975B multimodal model built for fine-tuning”
Inkling launched on Product Hunt on July 20th, 2026 and earned 184 upvotes and 11 comments, placing #6 on the daily leaderboard. Inkling is Thinking Machines’ first open-weights model, a 975B MoE with 41B active parameters, 1M context, native reasoning across text, images, and audio, and controllable thinking effort. Fine-tune it on Tinker or download the Apache 2.0 weights.
On the analytics side, Inkling competes within Artificial Intelligence and Development — topics that collectively have 480.1k followers on Product Hunt. The dashboard above tracks how Inkling performed against the three products that launched closest to it on the same day.
Who hunted Inkling?
Inkling was hunted by Zac Zuo. A “hunter” on Product Hunt is the community member who submits a product to the platform — uploading the images, the link, and tagging the makers behind it. Hunters typically write the first comment explaining why a product is worth attention, and their followers are notified the moment they post. Around 79% of featured launches on Product Hunt are self-hunted by their makers, but a well-known hunter still acts as a signal of quality to the rest of the community. See the full all-time top hunters leaderboard to discover who is shaping the Product Hunt ecosystem.
For a complete overview of Inkling including community comment highlights and product details, visit the product overview.
Zac Zuo
Hi everyone!
Inkling is the first model from Thinking Machines.
It is a 975B MoE with 41B active parameters, a 1M-token context window, and native reasoning across text, images, and audio. The full weights are available under Apache 2.0.
Thinking Machines is clear about what Inkling is for. They say directly that it is not the strongest model available today. It is meant to be a broad base that can be adapted to a specific product or workflow.
You can control how much thinking it uses, fine-tune it on @Tinker, and deploy the resulting checkpoints through several inference providers.
They even had Inkling write and run its own fine-tuning job, turning itself into a model that avoids the letter “e”.
The bet is that a model shaped around your own work can be more useful than a slightly higher score on a temporary leaderboard.