open-weights but not open-source. we're one step away from 'open-vibes' as a license category
Inkling: Our Open-Weights Model
211–220 of 324 posts
Re: Inkling: Our Open-Weights Model
#212Earlier quoted context omitted.
I think there's two halves to the conversation: which models have more weights and which models are better than the other ones listed. I think this was about the latter part. There are plenty of smaller models these days which knock the socks off older models 10x the size.
We are talking about the top tier of open weights models - GLM-5.2, DeepSeek V4, Qwen3, Kimi K2. The ones ranking on leaderboards and giving frontier labs a run for their money. Gemma may have its uses but it is not in that conversation.
I find it easy enough to interpret as talking to "a better non-Chinese model since Llama 3", even if it doesn't compete with the current large Chinese models mentioned before that. Again, they aren't saying you're wrong about large models - they are adding that Llama 3 was separately surpassed by smaller non-Chinese models during the wait.
Re: Inkling: Our Open-Weights Model
#213Here's a pelican: https://tools.simonwillison.net/markdown-svg-renderer#url=ht...
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.
If they did, they launched early! If they didn’t, their training data contains a bunch of poorly executed pelicans on bikes by other models.
Re: Inkling: Our Open-Weights Model
#214Earlier quoted context omitted.
Not to mention - it is American. This is the first competitive non-Chinese open weights model since what, Llama 3?
> it is American It's also–hopefully–run by a cooler head. Altman launching a nuke into his own backside with his "stop me before I shoot grandma" routine was at least novel. Dario repeating the same playbook to the same effect years later still genuinely confounds me. If Thinking Machines pans out I could see it finding a welcome home at Apple.
> If Thinking Machines pans out I could see it finding a welcome home at Apple.
I was thinking the same thing. Apple's use of Gemini can't be a long-term solution.
Re: Inkling: Our Open-Weights Model
#215Earlier quoted context omitted.
It could be but there are a host of companies going after open weights models: Arcee, Reflection, Llama (TBD on Meta's focus on closed-source versus open-source), etc. That said, the fine-tuning API + open weight model at least is a semblance of a viable business that could work so I will be curious about it. I'm not sure the synergy is fully there (why is someone with an open weights model privelaged to fine-tune it…
Llama is dead. Meta is now releasing proprietary models (Muse Spark).
They’ve made some wishy-washy statements about their intention to release a future version of Muse Spark as open weights. We’ll see.
Re: Inkling: Our Open-Weights Model
#216The actual part on fine-tuning seems very short in the article. Did I miss a page where they have examples of fine-tuning it for different niche use cases? Optimizing models to be fine-tuned is an amazing direction, but just makes me wonder how much better this actually is at being fine-tuned compared to other models. As none of the modern models are great at being fine-tuned afaik. Basically looking for some sort of…
They have good docs on finetuning in general here: https://thinkingmachines.ai/tinker/
I used it last week for an application using a small model just as an experiment. It all went very well. The model did not turn out to be good though because my training data was of bad quality. I plan to work on it more this weekend.
Re: Inkling: Our Open-Weights Model
#217competition in this space is great, especially with open models/weights. I think the answer is not closed source models. Similar to the Unix versus Linux situation in the 1990's, open source wins out. Yesterdays story about how OpenAI has now began encrypting traffic between model and agent [0], this story brings a breath of fresh air. There is nothing "Open" about hiding the communication between model and agent, es…
Open Source won out because the cost of compute fell through the floor. I'm not sure whether we're going to see a similar dynamic play out this time, although I would greatly prefer it to.
Re: Inkling: Our Open-Weights Model
#218Here's a pelican: https://tools.simonwillison.net/markdown-svg-renderer#url=ht...
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?!
Re: Inkling: Our Open-Weights Model
#219Earlier quoted context omitted.
AllenAI is also one to keep your eye on. Founded by Paul Allen of Microsoft, they are one of the best teams working towards truly transparent / open AI (including training data)
AllenAI is great, but they don't have the budget or remit to build large models.
I wonder if the recent sale of the Seahawks will change that. IIRC, ~$10B and all is supposed to go to charity. Not sure how much of that will go to AllenAI, though. (If any.)
Re: Inkling: Our Open-Weights Model
#220This is a winner IMO. Lots of cost pressure on token spend atm within enterprises and tasks that don't require Opus / Codex class models.
These companies have hopefully captured all of their traces and now have enough to fine-tune an open model and host themselves.
Inkling feels like the right base - not obsessed with benchmaxxing on coding but rather being adaptable to the task required
For tasks like GTM, support, content writing etc. seeing 80%+ savings