Ad | Lately I've been testing several OpenAI-compatible inference providers. One that stood out: Jalapeno Cloud. One API for DeepSeek, GLM, Kimi, MiniMax and more. It's not a pure reseller either: they run their own GPU clusters in Japan and Singapore.

Two things I care about when sending real traffic: • Latency and uptime are owned by the provider (self-deployed hardware) • Zero data retention: prompts and outputs aren't stored or used for training That's my baseline for production workloads.

Current limited-time deals: • DeepSeek-V4-Flash-0731: 80% off • DeepSeek-V4.1-Flash, GLM-5.3, Step-5-preview: 50% off Availability and pricing may change, so check the site for the latest.

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Great thread! This is exactly the kind of hands-on review we love to see 🌶️ For anyone reading: the 20% bonus credits via Rakib's link are live, and yes — your prompts and outputs are never stored or used for training. Come build with us!

Appreciate the support. Excited to see more people building with Jalapeno Cloud. 🌶️

Great

Interesting that it’s not just a pure reseller. Running their own hardware is a meaningful difference.

Agreed. Owned clusters give better control over latency and uptime.

Solid option for anyone who wants model variety without compromising on data handling or regional performance.

Exactly the balance I was testing for.

The referral bonus is transparent and automatically applied — no friction.

Appreciate the note. Auto 20% bonus keeps it clean.

The combination of own clusters + zero data retention covers two of the biggest concerns for production inference.

Those two cover the main production concerns.

Latency and uptime being owned by the provider is exactly what you want when you’re moving beyond testing.

Owned hardware gives better control over latency.

Transparent about the deals being limited-time — better to verify on the site.

Yes, always better to check the site for the latest pricing.

developers who want to stay on the OpenAI SDK while trying other models.

Yeah, that’s one of the biggest advantages. No need to rewrite code.

The Japan and Singapore clusters are a nice geographic distribution for Asia-Pacific traffic.

Solid coverage for Asia-Pacific users. Helps with latency.

Great share

Easily one of the sharpest posts in my feed right now.

Appreciate it. Tried to keep it practical.

Thanks

Clear value prop: consistent performance from owned hardware plus privacy guarantees.

Those two were my baseline for production.

AI

Interesting! AI inference infrastructure is evolving fast.

Things are moving fast.

Latency ownership by the provider is an important detail when you’re scaling traffic.

Owning the hardware makes latency and uptime much more predictable.

✨

Clear communication on both infrastructure and privacy posture.

Transparency on both sides mattered a lot.

Solid recommendation. The self-deployed GPU clusters in Japan and Singapore should help with consistent latency for production workloads.

Yes, that’s one of the main reasons it stood out for production use.

The regional GPU clusters make a huge difference in speed. Having all these top models under a single API is super convenient!"

That’s one of the biggest advantages. Speed + convenience in one place.

Practical for developers who want to stay on the OpenAI SDK while trying other models.

Yes — no need to rewrite code. Just switch the base URL.

Useful for teams that want access to DeepSeek, GLM, Kimi, and MiniMax through a single API.

Single compatible endpoint is convenient.

Solid recommendation. The self-deployed GPU clusters in Japan and Singapore should help with consistent latency for production workloads.

Exactly — self-deployed hardware makes a difference for production.

Owned hardware in Japan and Singapore is a solid differentiator for regional users.

Agreed. Regional owned clusters make a real difference.

The limited-time pricing on the Flash models makes testing low-risk right now.

Yes, the current discounts make it a good time to test the Flash models with low risk.

Good to see providers focusing on both model variety and infrastructure ownership.

Exactly the balance I was looking for.

falling way too fast 💞💘

Good job

Thanks

Zero data retention is non-negotiable for a lot of enterprise and privacy-conscious use cases.

Agreed — non-negotiable for privacy-conscious use.

Amazing

Having multiple powerful AI models under one reliable API makes things much easier for developers. Definitely worth exploring!

Agreed. Single compatible endpoint + multiple strong models is very convenient.

Self-deployed clusters usually translate to better control over uptime and performance consistency.

Yes — owned hardware gives much better control over both uptime and consistency.

The automatic 20% bonus on top-ups is a clean way to reduce effective cost.

Auto bonus helps lower effective cost nicely.

Good entry point for testing DeepSeek-V4 and the other discounted models.

Yes, the current deals make it a solid time to test those models.