SiliconFlow
One Platform — All Your AI Inference Needs.
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Pan YANG

SiliconFlow - One Platform — All Your AI Inference Needs.

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SiliconFlow provides AI infrastructure services, offering API access to a wide range of cutting-edge AI models and scalable cloud deployment solutions for developers and enterprises to build, integrate, and run AI applications efficiently.

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Pan YANG
Maker
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Hi PH Family! 😄 I’m Pan Yang, co-founder of SiliconFlow, and together with the team we’re super excited to share our brand.🚀 SiliconFlow is an AI infra platform that makes running and scaling LLMs/VLMs/Multi-modal models fast, affordable, and reliable—from a single endpoint to production-grade workloads. We built it because teams kept telling us they want great models + predictable latency + sane cost without wrestling with GPUs. What it is Unified AI API for leading open & proprietary models (text, vision, embedding, rerank). Production infra: autoscaling, low-latency routing, observability (logs, metrics), rate limits, eval hooks. Developer-friendly: OpenAI-style API, SDKs, drop-in with LangChain / LlamaIndex / Vercel AI SDK. Enterprise controls: workspace/org roles, usage caps, audit, regional routing, data privacy options. Optional BYOK: bring your own model/checkpoint when you need full control. Why now Model quality is improving weekly, but infra cost & tail latency still hurt. Many teams prototype fast, then hit the wall at scale—that’s the gap we’re focused on. Who it’s for Builders shipping AI features in apps, agents, data products. Teams moving from “demo” to “reliable production.” Supported models We currently support models from OpenAI, Qwen, Meta Llama, Moonshot AI, DeepSeek, Black Forest Labs, ByteDance, Z.ai, MiniMax, inclusionAI, Tencent, and StepFun. We keep adding new ones—tell us what you need. How to try Create an account → grab the API key → run our 60-second quickstart. Swap your current OpenAI-style client to our base URL, done. Check the live dashboard to watch latency & cost in real time. We’d love feedback from the PH community: What’s missing for your production needs? Which models or regions should we prioritize? Anything confusing in the docs or dashboard? If you test it today and hit issues, ping us in the comments. Thank you for checking out SiliconFlow! ❤️
Masum Parvej

@yangpan Is the autoscaling tuned per model type or does it follow a global config

Chloe Li

@yangpan  @masump It’s per-model (endpoint) first; if a model has no custom settings, it falls back to the global defaults.

Leo Feng

siliconflow is an API platform that I really like. It contains a lot of free APIs, some of which are also used by ListenHub, and it supports Pan!

Pan YANG
Maker

@leofeng Thank you Leo! Truly an honor to power great products like ListenHub on the backend 🙏

Chilarai M

Congrats on the launch! I've glanced over the platform, and it's really awesome.
Would love to connect

Pan YANG
Maker

@chilarai Thanks for checking it out! Glad you liked the platform — would love to connect and exchange thoughts on how you’re exploring this space.

Chilarai M

@yangpan cool. Already sent you a linkedin connect

Mohammed Maaz

This is huge for devs building AI apps. What’s been the biggest challenge in making multi-model inference seamless?

Pan YANG
Maker

@mohammed_maaz3 Thanks! The biggest challenge has been unifying inference routing across models with very different architectures, latency profiles, and tokenization quirks — while keeping the developer API consistent and latency low.
We’ve spent a lot of time optimizing that layer so it feels truly seamless to devs.