I have set up openclaw on my slightly older server that has no GPU, but 64GiB RAM. I tried with various different models, and I think I now found something that works ok.
The problem is of course that most models are censored, and I can only run small models of which most don’t work that well with openclaw. I have arrived at ollama/huihui_ai/Qwen3.6-abliterated:35b, which does work quite well. It’s a mixture of experts model, so responds fast even though it is quite big. Responses to simple prompts come after a minute, more complex maybe take ten, or sometimes even more. But for me that’s fine, given that I’m just using unused computation.
One issue with this model is of course that it is Chinese, and it does for example avoid the topic of the Tiananmen Square Massacre. But I’m not intending to talk about this kind of heavy stuff with it, so it’s not that bad. And when asked directly, it also searches the web for information about it.
For roleplaying it works quite well so far. I am still testing out the tool calling capabilities.
Before I tried ollama/huihui_ai/gemma-4-abliterated:26b, but while it talked nicely, it was bad at calling tools and updating e.g. the SOUL.md and IDENTITY.md file, and also tried to write information about me into the IDENTITY.md file instead of the USER.md file. So I looked for alternatives.
But I am interested in your setups. What models work well for you, and what kind of hardware do you use for them? Do you have any experience to share, or any tips you can give?
Definitely a new one for here…
That said, your post is missing the [AIT] tag - AI Topic. Please update asap.
Edit: Locking until updated.
…Go outside dude
But there’s people out there! (shudders)
Please ignore the post if you are not interested.
Please, ignore my comment and downvote if you are not interested.
There is an ERP (erotic role play) Benchmark: https://huggingface.co/spaces/overhead520/Unhinged-ERP-Benchmark?not-for-all-audiences=true You may also interested in software that is more ERP capable. 2 options would be Marinara Engine and SillyTavern. There you pair a model, a character card, your persona card, lorebooks and presets. What is that? A character card are the character, the AI plays. Being it a specific character, a world or a scenario. A persona is structured like a character card, but the purpose is that you are this character. Best practice is only to fill this card with stuff the character knows or sees about you.
A lorebook is additional information about the world or items. For example Marinara Engine can be used for RPG roleplay and in a lorebook you can explain weapons and items in details. This saves tokens, as these information only get pulled from the lorebook and send to the AI, when it get’s triggered by keywords.
Presets are the structure. It tells the AI how to output stuff and so on. These can contain soft jailbreaks. https://rentry.org/freaky-frankenstein-presets Freaky Frankenstein is one I use (FF5 Micro) and there you can set up a lot of things. But of course you can download other presets, that do fit you more or you write your own.
You must do research which presets work with which model and how far you can go and what you want and what you like. I use GLM 5.1 with FF5 Micro. I tried Deepseek but it was slower and I didn’t liked the output as much.
And now a comment to people who are disliking this: As long as you do treat it more as porn replacement and not as replacement for real human interactions, I find this good. Porn videos did killed the imagination and goes more back to erotic literature, which does require you to do more mentally. With AI you can choose your setting and boundaries and aren’t on other humans to do ERP. I never did ERP with other humans, but I’m pretty sure you can’t just close the chat window, when you are satisfied and let the other person hanging.
Also with both Marinara Engine and Silly Tavern, you don’t need to go sexual. Marinara does support games. I didn’t used it much yet. I tried the RPG function once. I didn’t had a char card, that was optimized to it. And the thing is, I have zero RPG experience. I never had friends who played DnD or pen and paper. But apparently Marinara does support this and they added a Multiplayer function. This way the AI can do the GM or other players. I don’t have much information for this, as I didn’t found a good resource jet, which explains me stuff and does recommend me fitting char cards to use.
I’ve already got a 128GB Framework Desktop that I picked up prior to the memory shortage for AI compute stuff, but if I didn’t…
In 2028, I expect memory prices to start coming down.
The GPU hardware itself isn’t really the limiting factor, but rather available memory.
I just don’t think that I’d be willing to put in massive amounts of effort trying to work around hardware limitations (or spend a bunch of money, which is the other route, outbidding people for the limited supply of memory) to get a local AI compute setup going in 2026 or 2027 when the hardware situation should change substantially in the not-so-distant future.
Specifically on generating literary erotica, my own experience is that quality is substantially better with larger, dense models. I’ve read that MoE models, like Qwen, are not very good at it, and my limited experimentation with Qwen supports that, though I haven’t tried to aggressively track the latest versions.
If you look at this thread:
…while the OP in that thread is talking about using Qwen 3.6 for erotic role-play (ERP), other users are not generally all that enthusiastic about Qwen 3.6.
In general, I think that /r/SillyTavernAI favors /u/TheDrummer’s models—which are not merely abliterated base models, but ERP-oriented finetunes—for ERP.
EDIT: If you are after generating erotica, my own experience is that TheDrummer’s Cydonia, which is recommended in that thread, is the best smaller (consumer GPU-runnable) model, though it starts to get nonsensical once the history grows large enough. I don’t know if you’d get a tolerable response rate out of that on a CPU-only setup. The best quality I feel I’ve seen has been out of the Llama-3-based AnubisLemonade, but I think that it’s going to be painful to run that on even a very high-end CPU-only setup. On my 128GB, unified memory setup, I use a Q6_K quantitization of that with llama.cpp run with (checks)
--direct-io --fit-off --no-mmproj -c0 -ngl 99 --dry-multiplier 0.8 --cache-type-k q8_0 --cache-type-v q8_0 --flash-attn onand a 128k token context window.I’m presently using Vulkan for compute with llama.cpp, though my experience with ComfyUI is that ROCm 10.1 is (finally) stable and effective on Strix Halo hardware, and I’ve been meaning to look into how llama.cpp handles ROCm now. In the past, llama.cpp had ROCm win on prompt processing performance and Vulkan win on inference performance; I’d been using Vulkan because ROCm releases had been having problems on that hardware and because I used a large context window and unchanging-from-prompt-to-prompt history with llama.cpp, so prompt processing time didn’t matter much, since one could rely on the cache to avoid most of the prompt processing, and inference time did matter.
The quantitization there is done to get response time down rather than because the system is memory-constrained.
In your case, the performance constraints may be quite different.
Often discrete GPU-based users (more bandwidth than my system, but much less memory) aim to use a small context window and have the system modify the history for each prompt, so they can’t leverage their K-V cache but can play tricks with things like RAG to keep a small context window and still keep a lot of relevant information, injecting relevant information into the history on each prompt. The problem they run into is generally trying to work around limited memory, not being able to store large models and a lot of history.
On my unified-memory setup, I use a large context window, leverage my memory, and rely on cache to keep performance acceptable. I’ve got plenty of memory, so I don’t have to worry about large model size or having loads of history, but have less memory bandwidth, so response time is the issue that I work on. So I use very different models and techniques from what’s optimal for a discrete GPU user.
Not sure what the best route for a CPU-only setup is. I’d expect that to be less memory-constrained than a GPU user, but be compute-constrained.
I don’t have experience nor do I want to get into it, but openclaw is a very token heavy application and you can probably do a lot better performance wise.
The reason it takes so long for first message is the amount of prompt openclaw requires. It’s almost certainly overkill, and with low prompt processing it will spend most of its time reading memory and soul files and config info for all of its tools.
I think you could just install earandil pi, set a prompt, and add a memory plugin and this will be faster. This is what openclaw uses if you strip back all the extras.
Also look for mixture of experts, they’re far less GPU intensive, so you’ll get better mileage. No idea what models are out there, but like even an a3b or a4b will be slow but maybe usable.
Again, I do not want to get into what this use case lacks or doesn’t work for, that’s your business and I don’t want to get into it. I’m just saying openclaw is probably like driving a 12 ton Humvee to the grocery store.
That’s too bad you can’t discuss the tianamen square massacre with your sex/roleplay chat bot.
Lol what’s your tokens per second not the server with no GPU running those sizes of models?
I’m getting like 10-20tps with some other similar-sized models, but didn’t benchmark qwen yet. Note that they are mixture-of-experts, so they are evaluating only a few billion parameters each time.
as someone who wants the global population to be reduced drastically, i support this
but also this is sad
cognitive dissonance sucks
