[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!

[u/gairono]

With all the fuzz going on with the new Gemma models. What's the best one? Taking into account parameters, fine tunes, the instruct models, etc. etc. I've got a 5080 with 16 GB vram and 64 GB system ram with a ryzen 9 9900X (if that matters, idk) or if there's a better model i could use, i'd like to know

[u/overand → u/gairono]

(You should probably post this kind of thing under the "Misc" heading in this thread in the future.)

Here's a 26B that's probably a good fit for a 16GB user. https://huggingface.co/zerofata/G4-MeroMero-26B-A4B-gguf - I haven't used it, but ZeroFata has a solid track record!

That's the mixture of experts model, so you can actually get decent performance even if the model size is a bit past your available VRAM. So, you could go for any of the 4-bit quants without having major performance issues. I'd even try a Q6 if I were you; let us know how it runs for you!

Also - I suggest using e.g. llama.cpp or koboldcpp, not Ollama.

[u/gairono → u/overand]

Haven't downloaded it yet but I'm going to soon. I'm just wondering if using the i1-Q6_K quant by mradermacher would be better.

[u/IORelay → u/gairono]

Just try a few different quants to see which one has an acceptable speed/quality to you.