The gap between local AI and cloud AI is closing fast. Here's every runtime, every model tier, and exactly how they stack up against GPT-4, Claude, and Gemini — running on your hardware, at zero cost per query.
The runtime is the engine — it loads the model, manages memory, and serves responses. Different runtimes for different use cases. We deploy the right one for your hardware and workload.
From 7B models that run on a laptop to trillion-parameter systems that require a data center. Here's the full landscape — what they run on, what they cost, and how good they actually are.
In 2023, GPT-4 was untouchable. In 2025, DeepSeek R1 matched o1 on reasoning benchmarks — open weights, runs on your hardware, costs nothing per query. The gap is now months, not years.
| Model | Type | MMLU Score | Cost / 1M Tokens | Private |
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Announced by Jensen Huang at GTC on March 16, 2026 — NemoClaw is NVIDIA's official enterprise security layer built directly on OpenClaw. The platform we run, with NVIDIA's compliance stack on top.
Single-command install. Nemotron models. NeMo Guardrails compliance layer. Deployable on RTX PCs, DGX Spark, and DGX Station. For the client who needs to show their work — this turns your sovereign stack into an auditable, policy-enforced enterprise AI system without moving a byte to the cloud.
Answer three questions. We'll tell you exactly what to run — model, runtime, and hardware recommendation included.
Pick your hardware, pick your model, and we'll build it. Most clients are live in two weeks.