Product updates: Running batch jobs with 1M inputs, ephemeral apps, and a new TensorRT-LLM example

Modal has expanded its asynchronous job capabilities by allowing up to one million inputs per Function, increasing `.spawn()` submission limits, and retaining FunctionCall results for seven days. Recent client improvements include support for ephemeral apps launched from containers, more reliable Dockerfile context handling, configurable image entrypoint arguments, and Git commit visibility in the CLI and dashboard, while Modal Client v1.0 is expected to introduce cleaner APIs and deprecation guidance. The company also released a TensorRT-LLM example for sub-400-millisecond language-model inference, video walkthroughs for deploying DeepSeek and OpenAI-compatible vLLM services, and highlighted customer launches from Imbue, Phonic, and Firebender using its infrastructure. Additional updates include recognition as the second-most-promising early-stage company on the 2025 Enterprise Tech 30 list, an open-source LLM demo event with Mistral, and a San Francisco billboard campaign.

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