5 comments

  • impulser_40 minutes ago
    Good. These have been basically useless for the past few generations of models, and most of the time made the model perform worst.
  • aesthesia54 minutes ago
    My guess is that RL training being done with particular generation parameters makes models much more brittle to changes in these parameters, and that's why we're seeing changes like this across model providers. But I don't really know.
    • pixelmelt42 minutes ago
      I'm inclined to agree given how unstable Gemma 4 is when not using the "official" sampler settings
  • tolugenius1 hour ago
    &gt; To improve determinism, define a system instruction with explicit rules for your specific use case.<p>Is this guaranteed to work any better than top_k or top_p? This just sounds like making a smaller version of a Agent.md doc.
  • tough1 hour ago
    fwiw sonnet-5 also drops temperature (sonne-4 had it)
  • greatgib3 hours ago
    1. Sampling parameter deprecation (temperature, top_p, top_k)<p>temperature, top_p, and top_k are deprecated and ignored. In future model generations, supplying these parameters returns an HTTP 400 error. Remove these parameters from all requests.