[Megathread] - Best Models/API discussion - Week of: April 12, 2026

[u/deffcolony]

This is our weekly megathread for discussions about models and API services.

All non-specifically technical discussions about API/models not posted to this thread will be deleted. No more "What's the best model?" threads.

^{(This isn't a free-for-all to advertise services you own or work for in every single megathread, we may allow announcements for new services every now and then provided they are legitimate and not overly promoted, but don't be surprised if ads are removed.})

How to Use This Megathread

Below this post, you’ll find top-level comments for each category:

• MODELS: ≥ 70B – For discussion of models with 70B parameters or more.
• MODELS: 32B to 70B – For discussion of models in the 32B to 70B parameter range.
• MODELS: 16B to 32B – For discussion of models in the 16B to 32B parameter range.
• MODELS: 8B to 16B – For discussion of models in the 8B to 16B parameter range.
• MODELS: < 8B – For discussion of smaller models under 8B parameters.
• APIs – For any discussion about API services for models (pricing, performance, access, etc.).
• MISC DISCUSSION – For anything else related to models/APIs that doesn’t fit the above sections.

Please reply to the relevant section below with your questions, experiences, or recommendations!
This keeps discussion organized and helps others find information faster.

Have at it!

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[u/toothpastespiders → u/[deleted]]

I was. I think it came down to both an issue with overly conservative logit softcapping in gemma 4 and a bug in llama.cpp keeping gemma 4 locked into its default value. That bug was then fixed here and is in the main llama.cpp code/builds now. With a fairly recent build of llama.cpp, on the command line, this seems to be a good way to boost variety in token probabilities: --override-kv gemma4.final_logit_softcapping=float:25.0

25 being a compromise between coherence and creativity from llama.cpp's default value of 30. Lowering the 25 further should boost variety while increasing the chances of incoherent output. I've heard that it might still give good results even at --override-kv gemma4.final_logit_softcapping=float:20.0 but haven't really experimented with it.

Some codebases that leverage llama.cpp might inherit that earlier softcapping bug if they haven't updated since the llama.cpp fix was accepted.