Quantum Junction is purpose-built to host both task-specific SLMs and frontier LLMs — with the same enterprise-grade reliability, security, and observability.
From one-click deployment to fine-tuning to observability — all in one platform.
Deploy any HuggingFace-compatible model in under 60 seconds. SLMs, LoRA adapters, quantized GGUF, or full frontier checkpoints — same API surface, same endpoint format.
Route each request to the right model automatically. Query complexity scoring sends simple tasks to your SLM and complex reasoning to your LLM — cutting average costs by 70%.
Upload your dataset, choose a base model, and launch a supervised fine-tuning run. DPO, RLHF, and LoRA supported. Your data never leaves your VPC.
Run your SLM and LLM head-to-head on your actual production tasks before going live. Export structured accuracy, latency, and cost comparison reports.
Private VPC deployment, end-to-end encryption, SOC 2 Type II certified, HIPAA BAA available. Complete audit logs for every inference call.
Token-level latency, cost-per-request, hallucination detection scores, and model drift alerts — all in one dashboard with Prometheus and Grafana export.
Quantum Junction runs on A10G and H100 GPU fleets purpose-built for inference, not repurposed cloud VMs.
24GB VRAM per GPU. Optimal for SLMs up to 13B parameters. p50 latency of 12ms for 3B models at 100 concurrent requests.
80GB VRAM per GPU. For frontier LLMs up to 70B parameters. Multi-GPU tensor parallelism for 405B+ models with NVLink interconnects.
Scale from zero to 10,000 RPS in seconds. Predictive pre-warming based on your historical traffic patterns means no cold-start latency spikes.
OpenAI-compatible API · Python, TypeScript, Go SDKs · REST
Start free in under 60 seconds. No GPU reservations. No minimum commits.