231–240 of 324 posts
Do they have an api to try the model in real envs?
They've got an openai + anthropic compatible endpoints. I got far enough to run some tests on the openai endpoint, albeit with some finagling (their /models list is empty, my tool auto-configures using that, was an initial stumble).
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I don’t really get the business plan for open weights model companies, is the idea companies would pay them for serving?
Thinky's main commercial product AFAIK is Tinker [0] - companies pay them to host their fine-tuning workloads and then the resulting fine-tuned models. I don't know if this is a good business plan, but I'm sure at least one person there has read Joel on Software [1]. [0] https://thinkingmachines.ai/tinker/ [1] https://www.joelonsoftware.com/2002/06/12/strategy-letter-v/
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?
Is it censored or will it eventually stop working in Middle Eastern countries?
Or is it biased towards powerful political lobby group interests?
When weights are open I usually don't care where is it from, as long as it is working for my use cases well
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MiniMax M3 and DeepSeek v4-Pro are highly capable long context open weight multi-modal models. But long-context is a trap, because performance still falls dramatically after 150k-200k context.
> But long-context is a trap, because performance still falls dramatically after 150k-200k context. I'm not sure exactly what causes the difference, but this heavily depends on the model. In my experience with Opus 4.8, I can go well over 500k and still get extremely good results. A drastically different example was GLM-5.1, which worked great until about 100k and then turned insane almost immediately. They did fix t…
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.…
Buried at the end there is the details I was most interested in - a possible competitor for DeepSeek V4 Flash? Excitedly awaiting the release of the weights for this one.
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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.
Interesting, I didn’t know this existed, do you think it’s competitive with Qwen 3.6 35B A3B which seems to be the closest comparator? It’s 20 vs 32 in favor of Qwen on artificial analysis intelligence index (cohere isn’t benchmarked on the coding index)
You can try it out for free: