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Inkling: Our Open-Weights Model

thinkingmachines.ai

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Re: Inkling: Our Open-Weights Model

#282
post #86

Earlier quoted context omitted.

So they're constantly hemorrhaging their most valuable clients? Tech history is littered with the corpses of "open source but we sell hosting" services. Models are so expensive to train, you can't be losing the big clients once they get super profitable.

This is genuine, noob question: how is this different from AWS? I get that they're in very different businesses, but for both don't they have the issue that once a client gets big enough the client might decide to move the services in-house? Based on how much of the internet went down when that AWS data center crashed the answer is clearly "No" for AWS. Is that because of physical, real-world infrastructure? Are ther…

> This is genuine, noob question: how is this different from AWS?

AWS owns the hardware, and doesn't write a lot of the software.

AWS actually is kind of the opposite - it often takes open source software (e.g. Apache, Mongo, Kubernetes) and then makes money off it by hosting it itself (with some enhancements etc).

If they do develop their own software (e.g. with S3) they don't give away the source code so others can deploy it, as that's part of their secret sauce.

In this scenario, where they would be offering the open source model and then offering the same model hosted, there isn't really a moat here - they would be leasing the hardware from a company like AWS, and adding a margin, but it woudl be trivial for another company (or Amazon) to take their same model and offer it for the same price or less.

Re: Inkling: Our Open-Weights Model

#284

Earlier quoted context omitted.

I’m afraid you’re going to have to start randomizing your benchmarks somehow. I’m sure these models are trained on this problem by now.

Wait. Based on the results of the test linked above you think this model might have been trained to produce it? Did you look at the results?!

That’s the problem. If all (or zero) models were trained on it, it would be fine as a benchmark.

Re: Inkling: Our Open-Weights Model

#285
post #119

Very nice, multi modal, largest open weight model that supports audio. Would be interesting to see how good the audio capability is. If you want to run locally, checkout https://github.com/danielhanchen/llama.cpp/tree/add-inkling https://unsloth.ai/docs/models/inkling https://huggingface.co/unsloth/inkling-GGUF https://huggingface.co/unsloth/inkling-NVFP4 This supposedly is better than KimiK2.7, as much hype as GLM5.…

Not to mention - it is American. This is the first competitive non-Chinese open weights model since what, Llama 3?

+1 I enthusiastically use Chinese open weight models for a wide range of tasks (I also love Opus and Gemini) but I am so happy to see another high quality American open model (I consider gemma to be high quality, like qwen).

I enjoyed turning off web search for Inkling to experiment with what innate knowledge is encoded in the model weights. A fun thing I do is check what innate knowledge very large models contain about me, as an individual. Inkling has an interesting concise shadow of what I do. (I have written a lot of books, so I am in training data.)

Re: Inkling: Our Open-Weights Model

#286
post #119

Earlier quoted context omitted.

Not to mention - it is American. This is the first competitive non-Chinese open weights model since what, Llama 3?

There's also poolside.ai

I was blown away by how effective their latest model drop that works with their own coding harness pool is. I tested it extensively with Haskell, Python, and TypeScript for small coding projects. The functionality is good but the inference speed is too slow for most of my work: I would set up a problem, take a walk, then return later to evaluate the results. Note that I have an old mac mini with 32B memory; a fast modern home system would be much better.

EDIT: their business model is interesting, aiming for supporting organizations with privacy and security concerns.

Re: Inkling: Our Open-Weights Model

#287
post #119

Very nice, multi modal, largest open weight model that supports audio. Would be interesting to see how good the audio capability is. If you want to run locally, checkout https://github.com/danielhanchen/llama.cpp/tree/add-inkling https://unsloth.ai/docs/models/inkling https://huggingface.co/unsloth/inkling-GGUF https://huggingface.co/unsloth/inkling-NVFP4 This supposedly is better than KimiK2.7, as much hype as GLM5.…

Not to mention - it is American. This is the first competitive non-Chinese open weights model since what, Llama 3?

GPT OSS was post Llama 3 and pretty strong at the time. But yeah this is the first seriously competitive non-Chinese open model in a good bit now.

Re: Inkling: Our Open-Weights Model

#288
post #271

Earlier quoted context omitted.

I’m afraid you’re going to have to start randomizing your benchmarks somehow. I’m sure these models are trained on this problem by now.

It's not a benchmark, it's a meme

To be fair, the "they're trained on this benchmark" response is also a meme.

Re: Inkling: Our Open-Weights Model

#289
post #152
post #119

Earlier quoted context omitted.

Not to mention - it is American. This is the first competitive non-Chinese open weights model since what, Llama 3?

North Mini Code by Cohere (HQd in Toronto) has honestly been very competitive in my personal assessment with many of the models coming out of the PRC. I'd position it below Moonshot AIs and Z.ais recent releases, but above the varieties of Qwen, Deepseek, MiMo, etc. Depends whether America the continent or just the United States counts of course.

>Cohere (HQd in Toronto)

Cohere keeps changing their story about where they're headquartered. From 2019-2020 they were HQed in Toronto. Then from early 2020 to 2026 they billed themselves as dual-headquartered in Toronto and San Francisco. Then in April 2026 they started to bill themselves as dual headquartered in Toronto and Berlin. Sometime in the last two months they've started to bill themselves as HQed in Toronto again.

Re: Inkling: Our Open-Weights Model

#290
post #2

America needs its own DeepSeek or Z.ai, a lot of people (myself included) root for open chinese models to win because they have no other choice. Thinking Machines might be it.

I’m trying to be charitable but your comment reads as “China bad” propaganda to me. Who cares that DeepSeek and Z.ai are Chinese companies?

you live under a rock or what?
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