SIE (Superlinked Inference Engine)
#4 in LLM Inference & ServingSuperlinked · 2× · last seen Sep 10, 2026
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Momentum
SIE (Superlinked Inference Engine) is an Open Source Inference server by Superlinked that provides over 100 small AI models (Embeddings, Reranking, Sparse-Retrieval, Extraction, OCR, and Text Generation) through a unified API on shared GPU resources. Instead of operating a separate server for each model type, SIE loads models on-demand and manages them via LRU-Eviction in a single cluster. The core product is released under Apache-2.0 license for Self-Hosting (from laptop to Kubernetes), and Superlinked additionally offers a managed Cloud version of the same Engine. The API is partially OpenAI-compatible, enabling simple migration.
Momentum trend
15.06.13.09.
Features
| Throughput/Latency | Self-hosted embedding returns results 3–7x faster than hosted frontier APIs; p99 latency close to p50; batch-then-route reaches ~89% GPU efficiency vs ~51% for route-then-batch (~1.8x throughput per GPU) |
| License | Open source, Apache 2.0 |
| Platform | Runs on own hardware: macOS (Apple Silicon), Linux (CPU/NVIDIA GPU), Kubernetes (AWS EKS, GCP GKE, Azure AKS) |
| Price | Core engine free (open source, self-hosted); managed SIE Cloud on request/contact; free hosted capacity for selected projects via inference grant |
| Protocol Compatibility | OpenAI-compatible API endpoints: /v1/embeddings, /v1/chat/completions, /v1/completions, /v1/responses |
| Release Date | Launch blog post dated February 2026 |
| Supported Models/Providers | 100+ pre-configured models (incl. Stella, SPLADE, Qwen3, GLiNER, SigLIP, BGE-M3, ColQwen2.5, BGE-reranker, Florence-2) covering embeddings, reranking, extraction, OCR and generation |