"The next AI economy will not be won by people with the most prompts. It will be won by people with the most defendable assets."

Swarm Inference — OpenAI-compatible API, served from sovereign baremetal.

Vertical-trained Swarm models served via vLLM behind an OpenAI-compatible HTTPS API. Same SDKs, same client libraries, same /v1/chat/completions shape — but the weights are ours, the compute is ours, and the data the models were trained on carries defendable.eth receipts.

Models on the rack

• Atlas-Qwen-27B · CRE underwriter · final loss 0.4186 · trained on 19.8K unique CRE pairs on the Gold Standard QLoRA config.
• SwarmCurator-9B · the curator/auditor model · final loss 0.707 · the model that grades Royal Jelly tiers on inbound corpora.
• SwarmSignal-9B v3 · signal classifier · trained on multi-source intake.
• SwarmPharma-35B · pharma-domain reasoner · trained on 25.6K medical pairs · final loss 0.337.
• SwarmJelly-4B · small-model jelly-tier reasoner · 225K pairs · in active production cook.

Compatibility

The endpoint at https://inference.swarmandbee.ai/v1/chat/completions accepts OpenAI SDK calls verbatim. Set base_url in any OpenAI-compatible client (Python SDK, LangChain, llama-index, custom HTTP) and authenticate with your Swarm API key.

Pricing

Per-token billing in line with comparable model-tier OpenAI pricing. Volume discounts at >1M tokens/day. Settlement in Stripe or USDC (swarmusdc.eth on Ethereum L1). BTC available on request. Reserved-capacity contracts available for committed throughput on the sovereign fleet (234 GPUs, ~18.6 TB VRAM, $0.10/kWh).

Why bakery-trained inference

Every Swarm model carries a defendable.eth-anchored training-data lineage. For regulated AI buyers (pharma, healthcare, defense, fintech), this turns the model itself into a Defendable AI Asset — auditable, attestable, and acceptable to procurement/legal/model-risk teams that would otherwise reject a black-box vendor. Inquire: [email protected].