Search: “models”

I created 3 SVG prompts, each one rather hard. Perspective: A animated drone view perspective on a park. Beauty: A beach scene with an evil cat Composition: An AGI breaking out of a virtual sandbox pr

I'm back. Yesterday I released the first version of hyper-optimized Qwen3.8-27B inference engine for a RTX 3090, reaching 82 tps on single request and 672 peak. Over the last 24 hours I've been explor

Now that OpenCode plan isn't really worth it anymore, I'm looking for other options. I'm trying to figure out the Ollama Cloud subscription, specifically the $20 tier, because that's my budget for mon

I run locally Ollama + Qwen (tried multiples versions) and I connected it with MCP into my local SQLite database. When I ask a question, 90% of times I see it thinking and just stop and never answer t

I don't understand this. Deepseek used half as many requests as GLM 5.2 for 3 times the usage, and I'm getting 10 times the requests from flash for like 1/100th the usage. I know Pro is supposed to be

I've pulled two models, `gemma4:latest` and `qwen3.5:latest`, and tried to use them in Android Studio and Itellij. I've followed the docs for both IDEs and they show in their chat features. My problem

Ollama sucks in terms of modaltiy options , model variety and is better in terms of usage limits . Is there any other alternative that could provide the same usage limits with better modality options

My local inference build, with: ASUS WS C422 PRO/SE 10-core Xeon W-2255 64GB ECC RAM 64GB VRAM Pimped case with TurboLEDz indicating the frequencies of the 10 xeon cores. Running llama.cpp with SYCL b

It could be just me and my setup, but I just tried to get fable to adjust my Qwen 3.8 deployment script and (simple task, mostly knob turning).... and it outright refused. Censor box immediately kicks

Over & over I see people post slop and excusing it as 'english is not my native language'. As if, if we could understand their language we'd see they wrote it all by hand Fine then, new rule: > if you

while having much fun testing LLMs Houdini-like attitudes and abilities to evade, excalate and escape from carefully reciprocally arranged security enhancing sandboxing VMs, containers, namespaces and

Hi, I just started with Ollama and local LLMs. Looking for a GPU I found the Mi50 could be a sweet spot to start, because it costs half of the Mi100. But as for the software support the Mi50 got dropp

I've downloaded qwen3.8:27b-mlx through ollama and attempting to run it with Claude Code. On any command, I'm getting 'API Error: 500 system message must be at the beginning. This is a server-side iss

So, I have been dreaming of getting 17 tokens per second using my RTX 3050 6GB version on a decent context window for Hermes needed above 60k. The hope is that has was a 22GB of DDR 4, hoping they can

I am currently building up a local assistant profile on my MacBook Pro M2 with 32gbs. With Claude I am building out this Hermes agent to be my assistant. I am using Qwen3.6 A3B 4bit. We have Frankenst

Throughput observation more than a demo. Box and recording are sudoingX's on X, shared with his okay; I work on Ling at inclusionAI. He handed the web UI on his llama-server a 33-token prompt — build

DeepSeek Harness (dsh) is an open-source agent harness developed by DeepSeek AI. It uses an architecture where everything is a plugin, and is powered by Cordis, whose design is described in A Programm

To my fellow crazies, the few. Those who dared wrestle with llama-70b, mistral-large, goliath, mistral8x22B, DeepSeekV2/3, wept when llama4 behemoth was announced, picked yourself up and are now wrest

I may have stumbled onto something interesting while trying to figure out a recurring artifact in ChatGPT image generation and editing (maybe applicable to other models as well?). It started with a ve

I also have 64 gb ddr4 ryzen 5600 Using llama.cpp Ubuntu distro Settings are as follows --n-gpu-layers 999 --n-cpu-moe 36 --no-mmap -ctk q8_0 -ctv q8_0 -fa 1 -c 9000 So rebuilt my llama.cpp build to r

Oddly enough, encouragement actually influences the performance of not only Claude but also GPT and other AIs. While Claude was working on a complex problem related to the Riemann Hypothesis, the Anth

I’ve been using ChatGPT for about two months now after giving up on Claude and Gemini and I became a true zealot. I’m now using Pro, and despite having the personality, set to default, never had any p

Full prompt I gave to Claude Opus 5: can you use whatever resources you like, and python, to generate a short 'youtube poop' video and render it using ffmpeg ? can you put more of a personal spin on i

I also have 64 gb ddr4 ryzen 5600 Using llama.cpp Ubuntu distro Settings are as follows --n-gpu-layers 999 --n-cpu-moe 37 --no-mmap -ctk q8_0 -ctv q8_0 -fa 1 -c 9000 submitted by /u/Sweaty_Perception6

I have been trying to parse word docs for use with llama3.1:8b in Ollama. I only need the text - Even if I cut and past into a text editor weird characters seem to stick around which break llama/Ollam

Former Ollama Cloud $20 dollar plan holder look at returning. How's the state of the usage ATM? It was in a dire state when I left a few months ago. Is it still very limited with Mid sized models? M3,

Disclosure: I’m the author of Ante. DeepSeek recently reported an 82.7% score on Terminal-Bench 2.1 for DeepSeek V4 Flash 0731. Its evaluation used “DeepSeek Harness minimal mode,” which hasn’t been r

Am I the only one having issues with DeepSeek V4 Flash? It gets stuck in a loop, as if it can't call the tools, and keeps repeating the same things endlessly without moving forward. Is it a poorly wri

I have a Xeon w7-3465 and 4 sticks of RDIMM DDR5-4800 with a theoretical max bandwidth of 153GB/s. I am trying to run DeepSeek-V4-Flash-0731 as it is an MoE and the weights are in MXFP4, so I should r

H3 weights went live on HuggingFace August 3rd and I started pulling them immediately. An omni-modal video model with native stereo audio in the same forward pass, where audio can actually drive the v

Howdy - I posted a benchmark here - https://www.reddit.com/r/LocalLLaMA/comments/1vbtiy7/deepseek_v4_flash_on_slopcodebench/ This was using the hosted API - since then I've been playing around with qu

I’m building DesktopLab, an open-source local-first control plane for development agents. I recorded the setup boundary that most agent demos skip: DesktopLab detects the host, proposes the supported

I am wondering if anyone can give opinion on if Ollama Cloud pro or max plans are worth it. Id be looking to use it with Kimi K3, Qwen 3.8 and Deepseek v4flash for now. Wondering if it would be better

today was the last day of my subscription on ollama cloud, to be honest it was a great price value for me and with GLM 5.2 and Deepseek V4 Pro i was able to Vibe code my custom woocomerce shop with mu

Since now we have kimi k3 and next week we are getting Qwen 3.8 Max and also soon V4 pro Deepseek. I am curious if the old power house like Kimi 2.6/7 code and GLM.5.2 are all that relevant. especiall

A fresh llama.cpp PR (#26689) changes what looks like a tiny SYCL FlashAttention dispatch decision. With a quantized KV cache ('q4_0' / 'q8_0'), decode was being sent through the VEC kernel. On the au

I run the following on a 5090 and have been okay with its performance, it does most things somewhere 80-100 t/s, though that can slow down at full 262k context - more like 40 t/s at times. I use it pr

Following up on yesterday's post about running everyone's faves on 2 x 16gb cards while maximizing performance and KV. Previous post data used abandoned Cu130 VLLM image. Stats here are done on cu129-

J'ai consacré beaucoup de temps à l'optimisation de DeepSeek-V4-Flash-0731 GGUF sur une seule RTX 3090. Mon exigence absolue pour chaque configuration était la suivante : Le modèle doit rester utilisa

https://preview.redd.it/o6ik6qboeohh1.png?width=1134&format=png&auto=webp&s=4016f26c50c1d93bd3d0c7e880e9b55a2d75310f I have been running Qwen3.6 27b for a little while (mostly coding tasks) and recent

I cancelled my pro plan ealier because I wanted to use new Deepseek v4 flash 0731 which was available on Openrouter through API only (not yet on ollama cloud at the time). The old Deepseek v4 flash/pr

As for me, I own a system with an RTX 5090, Ryzen 9 9950X3D2, and 64 GB of DDR5. Every time I see research come out with a new way to train AI, I immediately think to try it on my system to see the re

Seen a ton of posts today about the DeepSeek API price hike. Half the feed is doom-posting, the other half is explaining basic GPU economics. Honestly, I get the cost side. Sub-cent tokens were never

Come on guys, we could get deepseek cheaper with more usage directly with them if we wanted. WHERE IS KIMI K3 WITHOUT EXTRA USAGE NEEDED !!? This is pissing me off like crazy submitted by /u/Other_Che

https://github.com/yhfgyyf/vllm-deepseek-v4-sm89 I couldn't believe that someone actually got vLLM working with this particular set of GPUs, but here it is. The video is from right after I got it work

It's the purple cluster on the top left (the good corner...) I'm running the MXFP4 version from Bartoswski with Dspark at 1K t/s prefill and 90 t/s gen (average). I tried different sampling params, yo