@chiefofautism: take chinese model and fine tune it on corporate dataset, then put on runpod serverless
Summary
A tweet discusses fine-tuning a Chinese model on corporate data and deploying it on Runpod serverless as a cost-effective alternative to expensive API calls.
View Cached Full Text
Cached at: 05/25/26, 08:56 PM
take chinese model and fine tune it on corporate dataset, then put on runpod serverless
spidey (@lochan_twt): “api costs are too high, lets create our own LLM”
Similar Articles
@svpino: Serveless, but for models, is here! I stopped renting servers 12 years ago. I mostly moved everything to serverless fun…
Runpod announces FlashBoot, a serverless approach for AI models that moves idle models to cheaper storage and pages them back to GPU, achieving cold starts under 200ms and cutting costs by 90% compared to traditional clouds.
Built an open tool to calculate exact API vs. Self-Hosting (RunPod) breakeven points across 450+ models
开发者发布免费工具 ModelAnalysis.si，可跨 450+ 模型计算 API 调用与自托管（RunPod 租用 GPU）之间的成本盈亏平衡点，支持输入/输出 token 量与缓存命中率调节、VRAM 量化规格估算，以及基于实时定价和 ELO 排名的帕累托前沿分析。
@0xshimei: https://x.com/0xshimei/status/2053088751862288846
This article provides a comprehensive 2026 guide to free and low-cost large language models, comparing domestic (China) and international options.
Same AI model. Better results. Lower cost.
The author argues that AI coding harnesses and model routing are as important as the model itself, sharing tests with Oh-My-Pi and OpenCode that cut token usage and errors, and recommending tiered model subscriptions for high-volume lightweight tasks.
@heyshrutimishra: Most teams are spending 10x on models that stopped learning the day they shipped. Rented models don't improve with your…
Shruti Mishra promotes Oumi, an open-source AI platform that lets teams own and continuously improve models with their data, contrasting with rented APIs that don't learn.