LM Studio VS PixelAPI.dev
Compare LM Studio VS PixelAPI.dev and see what are their differences
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LM Studio
Ollama
GPT4All
Jan.ai
AnythingLLM
ChatGPT
llama.cpp
LocalAI
PixelAPI.dev
Replicate.com
Stability
DeepAI
Ruxa.ai
remove.bg for Photoshop
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Based on our record, LM Studio seems to be a lot more popular than PixelAPI.dev. While we know about 56 links to LM Studio, we've tracked only 4 mentions of PixelAPI.dev. We are tracking product recommendations and mentions on various public social media platforms and blogs. They can help you identify which product is more popular and what people think of it.
A good place to browse is the LocalLLaMa subreddit. [0] A good software to start is LM Studio [1]. Another popular alternative is Ollama [2]. A better software when you're used to it all is llama.cpp as it's usually a bit faster and more frequently updated [3]. A good place to get models is HuggingFace, particularly the Unsloth models [4] Most popular models lately to run on "regular" gaming PC's, workstations,... - Source: Hacker News / 10 days ago
LM Studio wraps the same inference engine in a desktop application with a visual model browser, one-click downloads from Hugging Face, and a built-in chat interface. - Source: dev.to / 18 days ago
LM Studio is the reference standard for running local models. It's not really an "AI client" in the workspace sense โ it's a local inference engine with a chat UI attached. Its MLX backend on Apple Silicon is noticeably faster than Ollama for many models, especially on larger ones, though both now use MLX on Mac so the gap has narrowed over time. The built-in model browser lets you discover, download, and run... - Source: dev.to / 22 days ago
Fully offline: Point it at Ollama or LM Studio. Zero cost, nothing leaves your network. - Source: dev.to / 24 days ago
On the other side, Ollama and LM Studio wrap llama.cpp in friendlier shells. Ollama is opinionated about model storage, format, and config. LM Studio is GUI-first and not terminal native. Both pay a real performance cost compared to raw llama-server, and both hide the underlying primitives that I actually like working with. - Source: dev.to / about 1 month ago
Import httpx Import os PIXELAPI_KEY = os.environ["PIXELAPI_KEY"] Def color_grade(image_url: str, style: str) -> str: response = httpx.post( "https://pixelapi.dev/api/color-grade", headers={"Authorization": f"Bearer {PIXELAPI_KEY}"}, json={ "image_url": image_url, "style": style, }, timeout=30, ) response.raise_for_status() return... - Source: dev.to / about 1 month ago
I shipped PixelAPI's /v1/pattern endpoint yesterday โ 8 styles, 512px or 1024px output, recolor + upscale ops, fully seamless tileable. At $0.008/pattern, it's 2-5ร cheaper than PatternedAI's GUI sessions. - Source: dev.to / 2 months ago
Import fs from "fs"; Import path from "path"; Import fetch from "node-fetch"; Import FormData from "form-data"; Async function addShadow(imagePath) { const form = new FormData(); form.append("image", fs.createReadStream(imagePath)); const response = await fetch("https://pixelapi.dev/api/shadow-generator", { method: "POST", headers: { Authorization: `Bearer ${process.env.PIXELAPI_KEY}`, ... - Source: dev.to / 2 months ago
Free credits at pixelapi.dev โ no card needed. Run your hardest test images through it. - Source: dev.to / 3 months ago
Ollama - The easiest way to run large language models locally
Replicate.com - Run open-source machine learning models with a cloud API
GPT4All - A powerful assistant chatbot that you can run on your laptop
Stability - Activating humanity's potential through generative AI. Open models in every modality, for everyone, everywhere.
Jan.ai - Run LLMs like Mistral or Llama2 locally and offline on your computer, or connect to remote AI APIs like OpenAIโs GPT-4 or Groq.
DeepAI - Easily build the power of AI into your applications