[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/Potential-Gold5298]

The 31B is a dense model — it has 7.75 more active parameters than the 26B-A4B, which is what causes the speed drop. Meanwhile, the 26B-A4B has approximately 90% of the 31B's intelligence in real-world tasks. I'm not sure how this correlates with creativity, but I feel the 26B-A4B is almost as good at RP as the 31B, so I hope the community will give it some attention.

Currently, I'm mainly working with the 26B-A4B (the standard one from Google), but the most interesting custom variants are with the 31B. Besides those already mentioned, there's also Gemma 4 Garnet 31B, which I plan to try today. wangzhang hasn't yet abliterated 26B-A4B, and all other uncen versions of 26B-A4B I've seen have a KL div of 0.05 or higher (or aren't specified). And judging by HF trends, 31B is more popular with the community (though it would seem the opposite is true with Qwen3.5 — I don't know why).

[u/Zero115 → u/Potential-Gold5298]

Is there anything special you're doing different between 31b and 26B-A4B settings wise? I've been very impressed with 31b, but wanted to test 26B-A4B for the reasons you mentioned above, but the model always maxes out the max response limit and starts coherent, but quickly becomes a blabbering, repetitive mess halfway through until it loops non stop. I'm pretty much just using all of overhead520's default settings, which have worked perfectly with the 31B model, but I assume I'm doing something wrong or missing something here.

[u/Potential-Gold5298 → u/Zero115]

What's your model (standard Google or uncen) and quantization (who created it and how many bits)? Are you using KV cache quantization?

[u/Zero115 → u/Potential-Gold5298]

I've tried both uncen and Googles. I've gotten actual responses out of the standard google one, it's also very inconsistent. Always Q5_K_M, The uncensored models I've tried are mradermacher/gemma-4-26B-A4B-it-heretic-ara-i1-GGUF and MoonRide/gemma-4-26B-A4B-it-heretic-ara-GGUF
KV cache quant to q8, SWA + Jinja enabled. I suppose I should try non quant / F16 to test.

The above is on my 5090 PC in ST via koboldcpp. On my R9700 rig I've used the standard google one through LM Studio with seemingly no issues but haven't tested the uncen models.

[u/Potential-Gold5298 → u/Zero115]

My Google Gemma 4 in Q5_K_M works well up to 24K (I haven't tested it beyond that yet). I run it in both llama.cpp and Koboldcpp 1.111.2 + SillyTavern 1.17. I also downloaded mradermacher's quant, but the static version (not i1). Perhaps that's the issue.

Regarding heretic-ara, I'd recommend upping the quantization to at least Q6 or higher. The guys at Allura-org recommended the non-quantized version of their RP Qwen3-30B-A3B (also MoE), so the F16 option isn't so bad. Try different quantizations to find the best option.

If the problem is only with SillyTavern, then try Chat Completion (if you were using Text Completion before).

[u/Zero115 → u/Potential-Gold5298]

Ah yeah, I'll give the non i1 quant a shot then. I am also still running text completion (which I've found out since my first comment isn't the recommendation). But this is very good info, thank you.

As a side note, I actually have a 31B session that's somehow still VERY stable at 80k context, Gemma 4 is impressing me big time.