Bit unrelated, I realized that z.ai gives you access to deepseek 4 flash. It's incredible how well it performs when given a detailed spec. I'm not sure I've seen a model one-shot like that, and I was already impressed by gemma 4's speed and efficiency.
Beating GPT-5.6 Sol on retrieval with 100x cheaper open models
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Re: Beating GPT-5.6 Sol on retrieval with 100x cheaper open models
#12I have done my own testing and found that smaller models can beat their larger siblings on fact retrieval from documents. I haven’t investigated it in depth with a large enough dataset but my guess is that larger models overthink it while smaller ones just do it. I would like if they compared this with 5.6 Luna instead.
Re: Beating GPT-5.6 Sol on retrieval with 100x cheaper open models
#13I have done my own testing and found that smaller models can beat their larger siblings on fact retrieval from documents. I haven’t investigated it in depth with a large enough dataset but my guess is that larger models overthink it while smaller ones just do it. I would like if they compared this with 5.6 Luna instead.
Re: Beating GPT-5.6 Sol on retrieval with 100x cheaper open models
#14There is so much opportunity for purpose built models like this. Ideally a harness should spin up a subagent to offload to targeted models for specific tasks like this. I know this is not a novel idea. Claude code does some of this by handing off the "explore" agent work to haiku. I just love seeing that specialized LLMs are being developed.
Models keep on improving though, so doesn't fine tuning become an ongoing task with ongoing maintenance burden?
Re: Beating GPT-5.6 Sol on retrieval with 100x cheaper open models
#15Re: Beating GPT-5.6 Sol on retrieval with 100x cheaper open models
#16There is so much opportunity for purpose built models like this. Ideally a harness should spin up a subagent to offload to targeted models for specific tasks like this. I know this is not a novel idea. Claude code does some of this by handing off the "explore" agent work to haiku. I just love seeing that specialized LLMs are being developed.
OpenAI etc could themselves do this, and maybe they already do? Where the public-facing interface delegates to multiple little goblins behinds the scenes
Re: Beating GPT-5.6 Sol on retrieval with 100x cheaper open models
#17On what do you guys test the model. Its very dubious that there is no common retrieval benchmark such as browsecomp plus or similar tested. And what metric do you report?
Re: Beating GPT-5.6 Sol on retrieval with 100x cheaper open models
#18There is so much opportunity for purpose built models like this. Ideally a harness should spin up a subagent to offload to targeted models for specific tasks like this. I know this is not a novel idea. Claude code does some of this by handing off the "explore" agent work to haiku. I just love seeing that specialized LLMs are being developed.
> There is so much opportunity for purpose built models like this. OpenAI etc could themselves do this, and maybe they already do? Where the public-facing interface delegates to multiple little goblins behinds the scenes
Re: Beating GPT-5.6 Sol on retrieval with 100x cheaper open models
#19There is so much opportunity for purpose built models like this. Ideally a harness should spin up a subagent to offload to targeted models for specific tasks like this. I know this is not a novel idea. Claude code does some of this by handing off the "explore" agent work to haiku. I just love seeing that specialized LLMs are being developed.
This is no longer necessarily true. As of 2.1.198 [0] (released July 1st): "The built-in Explore agent now inherits the main session’s model (capped at opus) instead of running on haiku"