@IyegereS Building your own LLM to cut API costs is like buying a factory to save on bread.
A better option would be to run open models on an affordable OpenAI-compatible endpoint and get your Friday back.
👋 that's us. Kimchi.dev
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kimchi.dev
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kimchi.dev
@getkimchi
https://t.co/MMivQzIFaz: Run LLMs, skip the infra. Managed AI inference platform for cost-efficient, private, and scalable AI.
Katılım Nisan 2026
0 Takip Edilen5 Takipçiler
Co-founder just asked us to build our own LLM to reduce API costs
GIF
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It's available now through our serverless API with an OpenAI-compatible endpoint. No infrastructure to manage.
Give it a try: app.kimchi.dev/serverless
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With 1M context, you can process entire codebases, long documents, and multi-step agent workflows without hitting limits.
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Kimchi now supports NVIDIA Nemotron 3 Super with 1M context length.
120B parameter hybrid MoE model, 12B active per token. Fast, cheap, great for long documents and large codebases.
Try it now: app.kimchi.dev
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