Oxylabs Reviews

llama.cpp Reviews

Oxylabs mentions (11)

• Python vs Go vs Java vs Ruby: Picking the Right Language for Production Web Scraping

  Enterprise proxy providers like Bright Data and Oxylabs offer large shared mobile pools that work well for high-volume data collection. For scraping workflows that need dedicated IPs with longer session stability and programmatic proxy management, smaller specialized providers like VoidMob offer dedicated mobile proxies on carrier infrastructure with MCP server access for agent-level control over rotation and... - Source: dev.to / 5 months ago

• How Rotating Mobile Proxies Are Transforming Data Collection: A 2025 Comparison of the Top Providers

  The Mobile Proxies of Oxylabs provide reliability and performance for the more established markets. Their offerings are suitable for well-structured and predictable workloads. Their pricing scheme indicates their enterprise solution offerings. - Source: dev.to / 7 months ago

• Cheap Residential Proxy: Affordable and Reliable Proxy Service for Anonymous Browsing

  Utilize Residential Proxies: Residential proxies come with the advantage of having whitelisted IPs tied to real devices, making them reliable for web scraping and anonymous browsing. Providers like Oxylabs, SOAX, and NetNut offer residential proxy services that can cater to your specific needs. Source: over 2 years ago

• Scraping with puppeteer and export in JSON format

  To begin scraping data, you have to decide which platform data you want to scrap. While it is easy to scrap data, some platforms prevent access to scraping of it data and you will have to use a third-party tool like ZenRows or Oxylabs just to mention a few. - Source: dev.to / over 2 years ago

• Best Proxy Website? Reddit recommendations?

  Have you tried Oxylabs? They have both residential and datacenter proxies. But I’ve heard their speed is not that great, so do your research. Source: about 3 years ago

llama.cpp mentions (13)

• Ask HN: How close are we to local LLM models being useful? What's the impact?

  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 / about 1 month ago

• llama-bench skipped FA on capable GPUs — b9437 corrects it

  Yes, for a local source build: pull the latest commit from ggml-org/llama.cpp and recompile. Tagged binary releases lag the continuous builds. Check the GitHub releases page for a pre-built artifact if you want to skip compilation, but verify the build number includes the b9437 changes before treating it as current. - Source: dev.to / about 1 month ago

• Introducing LlamaStash: a zero-overhead, terminal-native llama.cpp launcher

  That script grew up. Today I'm releasing LlamaStash, the first public release of a fast, cross-platform, terminal-native launcher for llama.cpp with zero overhead. - Source: dev.to / about 2 months ago

• How fast is LlamaStash? Overhead, throughput, and a fair comparison with Ollama and LM Studio

  LlamaStash spawns the unmodified upstream llama-server. So three different questions follow from that, and there is a benchmark suite for each. - Source: dev.to / about 2 months ago

• Why MTP doesn't speed up your llama.cpp inference (and how to actually fix it)

  Last week, I spent two days banging my head against a wall. I had just spun up a fresh llama.cpp build with multi-token prediction (MTP) support, loaded a quantized Qwen3 model, and ran my benchmark suite expecting that sweet 2-3x speedup everyone keeps talking about. - Source: dev.to / 2 months ago