Thinking Machines Lab debuts Inkling, an open-weight MoE model with 975B total and 41B active parameters, trained to be broad rather than optimized for one area

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Thinking Machines Lab 2026-07-16

Context & Ripple Effects

Thinking Machines Lab first positioned Tinker as a fine-tuning API, initially with third-party model support, then made it generally available. Its later interaction-model work emphasized systems users can continuously collaborate with rather than fixed, one-off outputs.

Inkling extends that arc from tooling and interaction design to a model the lab says is broadly capable and open-weight. The combination makes the release relevant to users seeking to adapt a general model rather than start with a narrowly optimized one.

First-order effects

Developers and organizations gain access to an open-weight MoE model whose 41B active parameters are the relevant per-inference footprint, despite its much larger total parameter count.
Thinking Machines Lab can pair its model release with Tinker, giving its fine-tuning product a more direct role in adapting a model from the same organization.

Second-order effects

Model users evaluating Tinker now have a potentially tighter model-and-customization path, while alternative fine-tuning platforms and open-model providers must compete on model quality, adaptation workflow, and deployment flexibility.
A broadly positioned base model may shift more differentiation to downstream tuning and interaction design, areas the lab has already highlighted through Tinker and its interaction-model previews.

Third-order effects

If labs increasingly release open-weight general models alongside proprietary customization layers, competition may move from owning model access alone toward controlling the tooling and workflows that make models useful to specific organizations.
MoE architectures with a smaller active parameter set than total capacity could broaden interest in balancing model scale against practical serving costs, though the corpus provides no performance or cost comparison for Inkling.

The trend: Inkling is one data point in the convergence of open-weight foundation models with managed fine-tuning and collaborative AI-product layers.

Discussion

@thinkymachines @thinkymachines on x
Today, we are introducing Inkling. Inkling reasons efficiently across text, image, and audio modalities. We are making the full weights available. https://thinkingmachines.ai/ ... Available today for fine-tuning on Tinker. Play with it in the Inkling Playground. 🧵
@johnschulman2 John Schulman on x
Inkling is out today, with open weights and in Tinker. It's been fun to watch this one come together: pretraining began last winter, and starting in mid-January a small team built up the coding, reasoning, and agentic training from there. We learned a lot building it, and I hop…
@chhillee Horace He on x
It truly takes a village to release a model, perhaps especially an open weights model. Actually doing the entire process from scratch, from data to pretraining to posttraining to actual release, gives a lot of appreciation for anyone who does it! There's so many places to go
@designarena @designarena on x
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-rankin…
@karinanguyen Karina on x
What Thinking Machines' Inkling Is Really Like, Part I
@miramurati Mira Murati on x
Our first model, Inkling. Trained from scratch, weights are open, fine-tunable on Tinker today.
@soumithchintala Soumith Chintala on x
Excited for our first general model Inkling — open weights, 975B, natively multimodal (text, image, audio). Available on Tinker, HuggingFace and partners. It is yours to personalize and use openly. It is yours.
@natolambert Nathan Lambert on x
Pretty detailed safety section of model card, I found this interesting and practical: “Across all areas, we concluded that Inkling did not present risk of material uplift beyond what's already available in the open-weight ecosystem.”
@deedydas Deedy on x
Thinking Machines just dropped the best open weight AI model outside of China! Inkling beats Nemotron 3 Ultra and benchmarks put it between Kimi 2.5 & 2.6. Many were contending to this throne, but Thinky has come out on top. Really solid release, and will pair well with Tinker. […
@lilianweng Lilian Weng on x
Inkling is our open weights model. It aims to serve as a foundation with solid performance across a broad categories of capabilities, for use in practice and customization. Play it on Tinker! 😄
@lmsysorg @lmsysorg on x
Inkling, @thinkymachines' first open model, dropped today: 975B total / 41B active MoE, up to 1M context, reasoning natively over text, images, and audio. Serving and RL support are already live: you can run and shape it on an open stack, starting now. Day 0 support on SGLang [vi…
@baseten @baseten on x
Inkling is live on Baseten. We're proud to partner with @thinkymachines to provide day 0 support. Try it here: https://www.baseten.co/... [image]
@yuchenj_uw Yuchen Jin on x
We're excited to announce that Databricks is a Day-0 launch partner of Thinking Machines Lab (@thinkymachines), bringing its first oss model, Inkling, to the Databricks platform. - the strongest US oss model - 974B total parameters, 41B active MoE - Apache 2.0 license The
@natolambert Nathan Lambert on x
Thinky with a ~1T param, 41B active, apache-2 model Benchmarks are a clear step up from Nemotron Ultra (55B active), new best American model, and omni input. A bit behind GLM 5.2 on agentic benchies, and Kimi K 2.6 on multi modal Super exciting! Thank you @johnschulman2 & team [i…
@artificialanlys @artificialanlys on x
Thinking Machines has released Inkling, the new leading U.S. open weights model, debuting at 41 on the Artificial Analysis Intelligence Index @thinkymachines has previously released research previews of models and this is their first production language model release. The model […
@scaling01 @scaling01 on x
Thinking Labs finally released their first big model as part of a model family, including smaller models it's an MoE with 975B @ 41B parameters, trained on 45 trillion tokens and it's open-weight! noticeably it reasons over text, images, and audio but benchmarks don't look [image…
@eliebakouch Elie on x
first open weight thinking machine model!! 975B total, 41B active trained on 45T tokens, 1M context, multimodal in sliding window with a 5:1 ratio and 512 size, deepseek aux-free load balancing and 2 shared experts (usually people only use 1), actually curious why the model is [i…
@tinkerapi Tinker on x
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
@rasbt Sebastian Raschka on x
Interesting surprise drop from Thinky! The Inkling model looks pretty solid on benchmarks, and it has some little surprises in its architecture: - Small conv layers in several places - An RMSNorm for the embeddings (before the block RMSNorm) - Rel. position bias instead of RoPE […
@arena @arena on x
Inkling by @thinkymachines is now in the Agent Arena! Agent Arena evaluates long-running agents. It measures models on millions of real-world, long-horizon agentic tasks from a global community of users. Models can access web search, filesystem, and terminal tools to complete [im…
@_alex_kirillov_ Alexander Kirillov on x
Most omni-models get dumber when you talk to them, audio in = intelligence penalty. Inkling doesn't. Same reasoning, whether you type or speak. It is open weights.
@nvidiaai @nvidiaai on x
Congrats @thinkymachines on the new open model 🙌 Inkling was trained on NVIDIA GB300 NVL72 and the NVFP4 checkpoint is available today on @huggingface: https://huggingface.co/... Happy building!
@teortaxestex @teortaxestex on x
I like that Inkling is mediocre on benchmarks this suggests they haven't been cutting corners too much with distillation. So their independent data pipeline will shine through, and it's not reducible to scores. By the second-third update, they become a meaningful player.
@teortaxestex @teortaxestex on x
Western open source frontier is back. This is on par with the largest of known Chinese pretrains so far (though might be outclassed in a few hours). And yes, it's another DSMoE +trained on Kimi data. But it has vision and *audio*. Unexpected good news. [image]
@soumithchintala Soumith Chintala on x
Modal trained a DFlash speculator that's much faster than MTP, making it a great boost for inference speeds! [image]
@scaling01 @scaling01 on x
I think people should stop asking the question how far behind chinese open-weight models are and start asking how far behind western open-weight models are
@martin_casado @martin_casado on x
I suspect this is the only highly capable frontier model that's not distilled from the big labs. Amazing job from the Thinky team. Finally we have an independent, pre-trained OS model.
@litianleli Tim Li on x
Incredibly proud of the team. After countless late nights, Inkling is out, and I especially want to highlight the post-training stack and RL recipes behind it. A few of my favorite details: We scaled our largest RL run to 30M+ rollouts and thousands of continuous training [image]
@mweinbach Max Weinbach on x
This model is interesting because it's the seemingly best base for a full scale post train/RL run for specific workloads or generalization. Helps that it's audio/image/text in! I'd be curious to see a proper model built off this or how Thinking Machine customers use it
@illscience Anish Acharya on x
as the most important problems go from being intelligence-bound to intuition-bound models with this “shape” should consistently outperform models like glm 5.2 [image]
@nvidiaaiinfra @nvidiaaiinfra on x
🎉 Congratulations to @thinkymachines on the launch of Inkling — a new open-weights model trained on NVIDIA GB300 NVL72 with NVFP4 checkpoints for efficient inference. 🔗 Available on @huggingface: https://huggingface.co/...
@dorialexander Alexander Doria on x
Great fully open release (Apache!) and curious about visual reasoning: no shortage of unsolved industry use cases and internal test set right now.
@guangxuan_xiao Guangxuan Xiao on x
Excited to share Inkling, our first open-weights model 🎉 We pre-trained it from scratch on 45 trillion tokens across text, images, audio, and video. Very proud of what we built, and excited to see what people customize with it on Tinker! 🚀
@bgurley Bill Gurley on x
This piece from @miramurati & @thinkymachines is quite consistent with the POV this past week from Alex Karp & Satya about companies controlling their own IP. Right place. Right time. Decentralized. Apache 2.0 to boot!
@databricks @databricks on x
.@thinkymachines' first open-weights model, Inkling, is now available on Databricks through Unity AI Gateway. As a day zero launch partner, Databricks gives enterprise teams access to a model that excels at coding and agentic reasoning and supports multimodal inputs. Teams can [i…
@shiringhaffary Shirin Ghaffary on x
Mira Murati's Thinking Machine Labs releasing their first model today. Open-weights. Company says still not as good as best models out there, but it's an open option coming at a time when leading US labs are increasingly closed. https://www.bloomberg.com/...
@eliebakouch Elie on x
fun fact, literally all the open models from western “big labs” (with a lot of ex close lab people), so thinking machine, microsoft MAI, gemma, gpt-oss have one thing in common: they ALL use sliding window attention 🙂 [image]
@a_karvonen Adam Karvonen on x
Thinking Machines is full of ex-frontier lab researchers and much of their new model follows Deepseek V3 architecture 🤔 It looks like data is all you need. [image]
@leerob Lee Robinson on x
New open model from Thinking Machines! 1T MoE, 1M context, multimodal, some solid evals. Really nice blog post 👏
@zephyr_z9 @zephyr_z9 on x
New model from Thinky Looking strong They just need 1 or 2 post-training reps, and we have another true frontier model lab [image]
@litianleli Tim Li on x
It turns out you can build a frontier post-training team / stack in less than 6 months. Real proud and real excited for the model factory to keep churning and iterating. Join us!
@shizhediao Shizhe Diao on x
Inkling is our first open-weights model: 975B parameters, multimodal input, controllable reasoning effort, and available today for fine-tuning on Tinker. Proud of what we built together and excited to see what people teach it next!
@agupta Ankit Gupta on x
thinky using @opencode for their demo and @DesignArena for their eval warms my YC heart
@ekzhang1 Eric Zhang on x
we released our first open weights model! grateful to get to work with this team. it's been a long time baking (almost since I joined), and from the engineering side, a really humbling experience to see so many people's work come together
@beffjezos @beffjezos on x
Finally we have an American alternative to GLM 5.2 Awesome to see American Open Source catch up! Kudos to @thinkymachines team [image]
@natolambert Nathan Lambert on x
Love this approach to open releases from Thinky — release a practical foundation to build on. I expect this to succeed for them, much as Tinker has exceeded many people's expectations (myself included)! [image]
@scaleailabs @scaleailabs on x
Congrats to @thinkymachines on the release of their open weight model Inkling! We were proud to work with their incredible team on preparing this model for release for the past several months. Now live on our MCP Atlas and AudioMultiChallenge leaderboards. Inkling tied for 🥇 on […
@ccatalini Christian Catalini on x
An open-weight model, built in the 🇺🇸, within striking distance of the frontier. The model wars have been labs selling the same product in different harnesses. @thinkymachines shipped the weights instead. Thinky different.
@luke_drago_ Luke Drago on x
The Inklings were a writing group in Oxford convened by CS Lewis and JRR Tolkien. It produced works like Narnia and the Lord of the Rings. Human sharpening humans, producing work greater than they could have on their own. So it is with us today; so it should go with us and AI.
@levie Aaron Levie on x
Fantastic to see more open weights innovation happening right now, especially coming from a US Lab. The future of AI is going to be a mix of frontier intelligence that you can use as an orchestrator combined with either lower cost or tuned models for your workhorse tasks. [image]
@sriramk Sriram Krishnan on x
Congratulations to @thinkymachines - amazing to see many new models especially open models in the American ecosystem now.
@simonguozirui Simon Guo on x
Check out Inkling, our first general-purpose, open-weights model! Things I love about Inkling and lucky to help contribute: - Natively multimodal! check out the new cookbooks to see how it can listen 🎧 and see 👁️ - Variable Thinking Effort 🎛️ 📈 for you to tune
@emostaque Emad on x
Given GB300 I would estimate this is was trained on about 1e25 flops (same as DeepSeek v4) over 1.6m hours (1 month on 2k chips/28 racks) Cost $10-$20m ($6-12/hour/chip) The lite version likely 4x less, similar compute to DeepSeek v3 3e24 flops Congrats to Thinky team!
@natolambert Nathan Lambert on x
Inkling was somewhat inevitable once Tinker took off — integration of post-training services across @thinkymachines's entire stack — and it's one of the best open-model business stories to date. Excited to see it grow and more emerge (some inference companies are next).
Mohamed Yasser Mohamed Yasser on linkedin
“Not the most performant model available today, closed or open.” — That's how Thinking Machines Lab opens their announcement of Inkling …
Christian Catalini Christian Catalini on linkedin
An open-weight model, built in the 🇺🇸, within striking distance of the frontier. The model wars have been labs selling the same product in different harnesses. …
Sangeen Zeb Sangeen Zeb on linkedin
So excited to see the Thinking Machines Lab team launch Inkling - their first model, with the full weights free for anyone to download, customize, and truly make their own! …
Amanda Saunders Amanda Saunders on linkedin
I literally just posted about why open models matter. Today, Thinking Machines Lab gave us an incredible new example 💚 …
Jenya L. Jenya L. on linkedin
We have just released a new model - Inkling, give it a try! — And by the way - it's open weights ☺️ — https://lnkd.in/...
Soumith Chintala Soumith Chintala on linkedin
Excited for Thinking Machines Lab's first general model Inkling — open weights, 975B, natively multimodal (text, image, audio). …
@timkellogg.me Mr. Tim on bluesky
Thinking Machines has a real model — 975B multimodal audio + image input — it's a generalist model. built for easy customization, TM has a great finetuning API — audio up to 20 minutes, 1M token context for text — thinkingmachines.ai/news/introdu...
@sungkim Sung Kim on bluesky
Nvidia's Nemotron is one of the closest alternatives, but it is strategically tied to Nvidia's Blackwell and NVFP4 ecosystem, whereas Inkling gives Thinking Machines a foundation model it can optimize directly around Tinker. — Check it out: thinkingmachines.ai/news/introdu...
r/LocalLLaMA r on reddit
Thinking Machines releases first open-weight model “Inkling”
r/singularity r on reddit
Thinking Machines releases first Open Weight Model “Inkling”
Tobias Wagner Tobias Wagner on linkedin
Thinking Machines Lab released their 7B open source model “Inkling” — Multimodal (including Video!) — Supports Agentic Workflows …
@eliebakouch Elie on x
BREAKING: a source familiar with the matter confirms employees at thinking machines breathe the same air as openai/anthropic staff. our investigation also uncovered a secret technique called “MoE” and access to a hidden research site known as “arxiv” [image]
@sriramk Sriram Krishnan on x
It is clear open source models and harnesses are having a moment. There's a few factors at work 1/ It is now obvious that you can catch up to near-SOTA performance and do so with a clear training lineage. See:@thinkymachines Inkling launch today. 2/ There are several
Emil Protalinski Emil Protalinski on linkedin
Thinking Machines Lab now has the best US open-weight model. — Thinking Machines Lab has released Inkling (https://lnkd.in/g5FRdYfA) …

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