Our plan keeps open weights and safety compatible with each other. We hope that this will help resolve debates and policies that pit open weights and safety as opposite and incompatible; ensuring a future full of open weights!

Thinking Machines just released Inkling-Small: 276B total, 12B active. A faster Inkling that matches or beats its 975B big brother in many benchmarks. To test its speed, we plugged it into HF's speech-to-speech. Audio goes directly into the model, and it replies using faster-Qwen3TTS. Running on 8x RTX Pro 6000 Blackwell, we get audio back in under 500ms. The normal Inkling needs 2TB of VRAM, this one fits on one node. Because the model hears the audio instead of a transcript, it can hear your tone and emotions. You can check it in the video. Or just go and try it in the space! Really fun model:

For my first post, I’m sharing a letter @NVIDIA signed on why open models matter. AI will transform every industry, power every company, and be built by every country. Open models strengthen safety and cybersecurity, accelerate innovation and diffusion, and enable sovereignty. The world needs both frontier closed models and frontier open models.

A model drop by Thinky 🚨🚨 Have been doing some early testing on the model for the past couple of days. Here are some of my findings 1. The reasoning is sharp and concise! Always love to see models that dont ramble 2. Tool calling is beautifulllllll, Its consistent, clean, very well designed for streaming , multi-tool call per step, etc.! 3. Holds up impressively on agentic tasks. In my testing, I was particularly impressed with its ability to run long-horizon tasks with solid error recovery. 4. Most importantly, it was built from the ground up for post-training and customization and this is a real unlock for teams building on open source!! This will be greatly beneficial for continual learning workflows at @trajectorylabs! Amazing step for American OSS models, really excited to keep "tinkering" with it lol

Inkling is our first open model from @thinkymachines and is now available on Tinker! Check out these quotes from Tinker customers on their experience with Inkling: @_Mantic_AI: "Not only does Inkling outperform Kimi K2.6 on our forecasting evals, it does so with half the output tokens." @trajectorylabs: "We’ve been impressed by how sharp and efficient the model is. Its reasoning is concise, its tool calling is consistently strong, and it holds up well on complex, long-horizon agentic tasks. It feels like a meaningful unlock for what teams can build with open-source models designed for customization." @lightningrodai: "We came away impressed by the model’s underlying reasoning ability. It’s thoughtful, original, and refreshingly unsycophantic.”

BREAKING: Inkling by @thinkymachines is 9th overall on Agentic Web App Arena by Design Arena with an Elo of 1257 It's an open-weight model in the same performance band as Claude Opus 4.6 by @AnthropicAI and Gemini 3.5 Flash by @GoogleDeepMind This makes Inkling the highest-ranking US-based open-weight model for agentic workloads, achieving frontier-level performance Congrats to the @thinkymachines team for this achievement!

What do we do at @thinkymachines: Personalization/sovereignty, Human Participation, Decentralization. Democratize AI and make it useful for people. All three of them reduce society's dependence on centralized AGI companies (including ours when we get important), and that is a future worth aiming for. You've seen a preview of this with Tinker, Interaction models and our research openly published on Connectionism. A **lot** more to come very very soon...

Bridgewater, one of the worlds largest hedge funds, a Tinker customer talks through how they've carefully fine-tuned a model focused on what makes interesting financial news. Their fine-tuned model is more effective and cheaper than any frontier model.

sometimes , it really does take a decade for me to understand a paper and appreciate its insight and foresight. <Discovering Causal Signals in Images> is one such paper. wow ... david, @robertnishihara , @soumithchintala , @bschoelkopf & @LeonBottou really did see the future.

Cluster magicians and GPU whisperers, come join us! We’re looking for supercomputing engineers to build the infrastructure behind real-time interactive models, Tinker, and large-scale training: scheduling, storage, networking, reliability, and distributed systems at scale. Hiring in NYC and SF