Helmcode runs frontier open-model inference through one API that works like OpenAI’s. It’s aimed at teams that need production AI without moving data to hyperscalers or hiring GPU and inference specialists.
It’s especially relevant for regulated use cases where legal and security teams care about where data is processed, and engineering teams want predictable costs. Helmcode positions “unlimited tokens” as no total consumption caps, while still enforcing practical limits per key (requests per minute and concurrency).
You can choose different deployment levels depending on how much sovereignty you need. Shared EU infrastructure is managed and quickest to adopt. Dedicated reserves exclusive NVIDIA Blackwell (B200) hardware for isolation and custom modeling. On-premise deployment runs the inference stack inside your datacenter so data never leaves your network.
If your team already uses an OpenAI SDK or tools, Helmcode is built to be a drop-in replacement via the OpenAI-compatible API and model IDs you call directly. It’s also set up to support model switching across served open models such as DeepSeek V4-Flash, Qwen 3.6, Gemma 4, plus embeddings, speech, and reranking.
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