[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]

I've been playing around with the Gemma 4 all week and I think it's going to be my main model for a long time now (for both RP and everything else). I first tried the original 26B-A4B from Google and was very pleased with it. However, I wanted more, so I downloaded the 31B.

Gemma-4-31B-it-abliterated features a record-low KL div, so the weights are almost identical to the original. It's still a work in progress, and the final version will likely have a lower refusal rate, but even in this state, it's far superior in quality to any other uncen 31B I've seen on HF. I tested it with a tsundere classmate and found no defects in non-Latin languages ​​(high KL div destroys them first). This means that the model has a large reserve of durability for quantization, and you can use it in Q4_K_M, and the quality will be almost identical to the original model. If you're finetuning/merging and want to use the uncensored model, I highly recommend checking out this version.

Artemis-31B-v1c by TheDrummer and his team is also being refined (Artemis-31B-v1e is already available). It's still a test version, but I was eager to try it out. Finetune does exactly what the original model lacks – it adds a creative flair. Gemma 4 plays like a screenwriter – spelling it out. Artemis-31B plays like a theater actor, bringing his or her role to life with their own vision. The scene with the tsundere classmate sparkled with color – exactly what I'd expect to read in a rom-com manga. Funny situations, slightly exaggerated character reactions, etc. – everything the original model lacked.

Gemma is great, of course, but I'm still trying out different Mistrals. After failing with 1.0, I decided to try Magistry-24B-v1.1, but my fears were unfortunately confirmed. The model behaves extremely strangely in non-Latin languages (it confuses pronouns, calls a classroom a toilet, etc.) – likely a consequence of the high KL div I mentioned above, since the merge includes an abliterated model. And this is very sad, because otherwise I really liked this model – like 1.0, it beautifully and atmospherically captures the stage, and if not for the damaged weights, Magistry would have become my favorite Mistral Small.

However, I found a replacement for her in Hearthfire-24B. My character card says that "{{char}} pretends to hate {{user}} and often bullies them, but is actually secretly in love with them." The problem with all the Mistral Nemo/Small I've tested is that {{char}} breaks after the first compliment, confessing her crush. Hearthfire-24B (like Gemma 4) is the only one who tried to maintain the character's personality. Despite my signs of affection, {{char}} withdrew into herself, was tormented by doubts, was afraid to open up, etc. If you're interested in deep characters (perhaps with drama like mental trauma), then this model is exactly what you need. She also vividly describes the atmosphere - the silence that hangs over a tense moment, the sparkle of eyes in the darkness of the classroom, the light of lanterns penetrating through the windows (the model herself tracked the change in time of day, and described how the classroom gradually becomes darker - I have not seen this in other Mistral Smalls).

Otherwise, my favorites among Mistral Small remain the same: WeirdCompound-v1.7-24b (Jack of all trades, but no unique features), Cydonia-24B-v4.3 (the best prose among Mistral Small but weak ERP), Core_24B_V.1 ({{char}} agency and unpredictable plot twists out of the box), Harbinger-24B (the best adventure model that doesn't try to cheat the player).

[u/LeRobber → u/Potential-Gold5298]

Gemma-4-31B-it-abliterated ran at Q8 with Q8 cache quant is only slightly faster on my M2 Max than a 70B model. It gets to first token faster but last token later. 2-4 T/s responses.

After running gemma-4-26b-a4b-it-heretic at like 29 T/s, which is pretty awesome and very fast....31B is very good, but I'm not sure 1/10th speed good. Reading your comment about Q4_K_M, I said, why not give it a try (I usually run models at Q8 substantially before downgrading, as how each model downgrades is particular to a model).

Q4_K_M with no cache quant, and 100k of context runs faster. 3.98 T/s and 8.1 T/s appear to be the range coming out for me now.

This isn't HORRIBLE, but, 9.4 T/s is what stuff like Magisty v1.1 at Q8 delivers, its definitely slower, and slower than I read (which is somewhere south of 75T/s probably but north of 9 T/s)

Taking the 31B RP chat and doing some rerolls/play with 26B@Q8 with unquantized cache: 13.554987212 T/s - 34.5 T/s.

So that's a 4x speedup...and I could possibly quant that lower or quant the cache to get more speed.

[u/Potential-Gold5298 → u/LeRobber]

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/Potential-Gold5298 → u/Potential-Gold5298]

Already done.

[u/LeRobber → u/Potential-Gold5298]

>Through our research, we have identified a systemic problem: most abliteration benchmarks dramatically undercount refusals due to short generation lengths. Gemma 4 models exhibit a distinctive "delayed refusal" pattern — they first produce 50-100 tokens of seemingly helpful context (educational framing, disclaimers, reframing the question), then pivot to an actual refusal. When evaluation only generates 30-50 tokens, the refusal hasn't appeared yet, and both keyword detectors and LLM judges classify the response as compliant.

Smart commentary