Ollama Turbo
ollama.com
Ollama Turbo
1–10 of 251 posts
Re: Ollama Turbo
#2Man, busy day in the world of AI announcements! This looks coordinated with OpenAI, as it launches with `gpt-oss-20b` and `gpt-oss-120b`
Re: Ollama Turbo
#3Man, busy day in the world of AI announcements! This looks coordinated with OpenAI, as it launches with `gpt-oss-20b` and `gpt-oss-120b`
Yep, on the ollama home page (https://ollama.com/) it says
> OpenAI and Ollama partner to launch gpt-oss
Re: Ollama Turbo
#4Interested to see how this plays out - I feel like Ollama is synonymous with "local".
Re: Ollama Turbo
#5Ollama is great but I feel like Georgi Gerganov deserves way more credit for llama.cpp.
He (almost) single-handedly brought LLMs to the masses.
With the latest news of some AI engineers' compensation reaching up to a billion dollars, feels a bit unfair that Georgi is not getting a much larger slice of the pie.
Re: Ollama Turbo
#6Ollama is great but I feel like Georgi Gerganov deserves way more credit for llama.cpp. He (almost) single-handedly brought LLMs to the masses. With the latest news of some AI engineers' compensation reaching up to a billion dollars, feels a bit unfair that Georgi is not getting a much larger slice of the pie.
Is Georgi landing any of those big-time money jobs? I could see a conflict-of-interest given his involvment with llama.cpp, but I would think he'd be well positioned for something like that
Re: Ollama Turbo
#7Interested to see how this plays out - I feel like Ollama is synonymous with "local".
There's a small but vocal minority of users who don't trust big companies, but don't mind paying small companies for a similar service.
I'm also interested to see if that small minority of people are willing to pay for a service like this.
Re: Ollama Turbo
#8Ollama is great but I feel like Georgi Gerganov deserves way more credit for llama.cpp. He (almost) single-handedly brought LLMs to the masses. With the latest news of some AI engineers' compensation reaching up to a billion dollars, feels a bit unfair that Georgi is not getting a much larger slice of the pie.
Is Georgi landing any of those big-time money jobs? I could see a conflict-of-interest given his involvment with llama.cpp, but I would think he'd be well positioned for something like that
(This is mere speculation)
I think he's happy doing his own thing.
But then, if someone came in with a billion ... who wouldn't give it a thought?
Re: Ollama Turbo
#9Ollama is great but I feel like Georgi Gerganov deserves way more credit for llama.cpp. He (almost) single-handedly brought LLMs to the masses. With the latest news of some AI engineers' compensation reaching up to a billion dollars, feels a bit unfair that Georgi is not getting a much larger slice of the pie.
Agreed. Ollama itself is kind a wrapper around llamacpp anyway. Feel like the real guy is not included to the process.
Now I am going to go and write a wrapper around llamacpp, that is only open source, truly local.
How can I trust ollama to not to sell my data.
Re: Ollama Turbo
#10Nice release. Part of the problem right now with OSS models (at least for enterprise users) is the diversity of offerings in terms of:
- Speed
- Cost
- Reliability
- Feature Parity (eg: context caching)
- Performance (What quant level is being used...really?)
- Host region/data privacy guarantees
- LTS
And that's not even including the decision of what model you want to use!
Realistically if you want to use an OSS model instead of the big 3, you're faced with evalutating models/providers across all these axes, which can require a fair amount of expertise to discern. You may even have to write your own custom evaluations. Meanwhile Anthropic/OAI/Google "just work" and you get what it says on the tin, to the best of their ability. Even if they're more expensive (and they're not that much more expensive), you are basically paying for the priviledge of "we'll handle everything for you".
I think until providers start standardizing OSS offerings, we're going to continue to exist in this in-between world where OSS models theoretically are at performance parity with closed source, but in practice aren't really even in the running for serious large scale deployments.