Ollama VS Cachely.dev
Compare Ollama VS Cachely.dev and see what are their differences
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Ollama
LM Studio
Hugging Face
Jan.ai
LangChain
Claude AI
GPT4All
OpenAI
Cachely.dev
nxCloud
Cachely is the managed self-hosted remote cache for Nx and Turborepo - the cache backend you'd otherwise build and run yourself, hosted for you on Cloudflare's edge (R2). It's a drop-in replacement for a DIY @nx/s3-cache / S3 bucket setup: point your build tool at Cachely with a token and two environment variables, and share build cache across CI and every developer's laptop.
Unlike a self-hosted cache, Cachely enforces read-only tokens at the API, so pull-request and fork builds can read but never write - closing the Nx cache-poisoning attack (CVE-2025-36852). It adds ROI reporting (the real build minutes and dollars the cache saved), per-tool insights, and build-optimization suggestions on top.
Pricing is a flat per-workspace subscription with no per-seat fees - add every developer, bot, and CI actor without watching the bill. Cachely never stores your source code; it caches only task outputs and their content hashes. Nx and Turborepo today; Bazel on the roadmap.
Ollama Cachely.devOllama is recommended for businesses and teams seeking an efficient project management solution. It is especially useful for remote teams, startups, and any organization looking to enhance collaboration and project tracking capabilities.
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Based on our record, Ollama seems to be more popular. It has been mentiond 292 times since March 2021. 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.
Local open-weight models solve the model half. Ollama serves a model and exposes an OpenAI-compatible endpoint, which means the standard red-team tooling works unchanged against a target that never leaves the host:. - Source: dev.to / 6 days ago
I didn't want a cloud API key for a side project, so I ran Ollama locally on an old CPU-only laptop. This is where the framework knowledge from above collided with the actual, physical limits of local inference โ and where I learned the most. - Source: dev.to / 13 days ago
Ollama running on the inference box, serving your model of choice. - Source: dev.to / 13 days ago
The problem was the ergonomics. Ollama makes running local models genuinely easy, but I wanted a smoother terminal workflow โ streaming chat that didn't feel clunky, safe file editing, and the ability to run real multi-file agent tasks without leaving my shell. - Source: dev.to / 15 days ago
If you don't have it, get it. Seriously. Itโs the easiest way to get an open source llm mac experience going. Go to ollama.com and download the macOS app. Install it. Simple. - Source: dev.to / 18 days ago
LM Studio - Discover, download, and run local LLMs
nxCloud - nxCloud is a commercial OwnCloud provider
Hugging Face - The AI community building the future. The platform where the machine learning community collaborates on models, datasets, and applications.
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.
LangChain - Framework for building applications with LLMs through composability
Claude AI - Claude is a next generation AI assistant built for work and trained to be safe, accurate, and secure. An AI assistant from Anthropic.