Prism

Teams building coding agents need to run frontier-class language models in their agent loop but standing up and operating their own GPU infrastructure is costly and complex. Developers who want access to open-weight models like DeepSeek-V4.1-Flash or Gemma 4 31B otherwise face slower inference, higher cost from major cloud providers, and the burden of managing hardware themselves. Switching providers or scaling from prototype to production also typically requires rewriting client code against different API formats.

Prism offers a serverless inference API that is compatible with both OpenAI Chat Completions and Anthropic Messages formats, letting developers keep their existing client code and just change the base URL, API key, and model id. It serves DeepSeek-V4.1-Flash (552B MoE, 1M context) and Gemma 4 31B (31B dense, BF16, 32K context) through a single key, with claims of up to 5.8x faster token throughput than major providers and up to 50% lower price. The platform spans serverless APIs, elastic and dedicated endpoints, and GPU control, so customers can scale from an API call to a dedicated cluster, and it states 99.99% uptime SLA, 50ms P50 latency, and global points of presence. Prism also states it applies zero data retention to API inputs and outputs and does not train on them, and offers private or dedicated deployments in its cloud or the customer's.