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Comment by mvkel

3 months ago

Open weight LLMs aren't supposed to "beat" closed models, and they never will. That isn’t their purpose. Their value is as a structural check on the power of proprietary systems; they guarantee a competitive floor. They’re essential to the ecosystem, but they’re not chasing SOTA.

This may be the case, but DeepSeek 3.2 is "good enough" that it competes well with Sonnet 4 -- maybe 4.5 -- for about 80% of my use cases, at a fraction of the cost.

I feel we're only a year or two away from hitting a plateau with the frontier closed models having diminishing returns vs what's "open"

  • I think you're right, and I feel the same about Mistral. It's "good enough", super cheap, privacy friendly, and doesn't burn coal by the shovel-full. No need to pay through the nose for the SOTA models just to get wrapped into the same SaaS games that plague the rest of the industry.

I can attest to Mistral beating OpenAI in my use cases pretty definitively :)

  • In my use cases mistral has been next to useless.

    Granted my uses have been programming related. Mistral prints the answer almost immediately and is also completely and utterly hallucinating everything and producing just something that looks like code but could never even compile...

> Open weight LLMs aren't supposed to "beat" closed models, and they never will. That isn’t their purpose.

Do things ever work that way? What if Google did Open source Gemini. Would you say the same? You never know. There's never "supposed" and "purpose" like that.

  • Not the above poster, but:

    OpenAI went closed (despite open literally being in the name) once they had the advantage. Meta also is going closed now that they've caught up.

    Open-source makes sense to accelerate to catch up, but once ahead, closed will come back to retain advantage.

    • I continue to be surprised that the supposed bastion of "safe" AI, anthropic, has a record of being the least-open AI company

> Their value is as a structural check on the power of proprietary systems

Unfortunately that doesn't pay the electricity bill

  • It kind of does, because the proprietary systems are unacceptable for many usecases because they are proprietary.

    There's a lot of businesses who do not want to hand over their sensitive data to hackers, employees of their competitors, and various world governments. There's inherent risk in choosing a propreitary option, and that doesn't just go for LLMs. You can get your feet swept up from underneath you.