Marginal vs TensorSharp

Track every LLM call's cost and slice it by customer, feature, model, any field you define.

TensorSharp is a native .NET GGUF inference engine with a CLI, Web UI, compatible APIs, Agent Skills, and optional sandboxed model-authored code.

About Marginal

Track every LLM call's cost and slice it by customer, feature, model, any field you define. Marginal tracks the cost of every LLM call and slices it by the fields you care about, customer, feature, model. Cost is computed server-side, usage in, dollars out. Every API request is logged with its outcome, accepted counts, rejected events and why, stripped keys, unpriced models. The SDKs are zero-dependency, buffered, fire-and-forget: track() never throws and never blocks your request path.

About TensorSharp

TensorSharp is a native .NET GGUF inference engine with a CLI, Web UI, compatible APIs, Agent Skills, and optional sandboxed model-authored code. TensorSharp Wiki, Local GGUF inference and agentic work for .NET Skip to content. Everything runs on your own hardware : your laptop, workstation, or server. Inference and agent work stay local by default, there are no per-token fees, and the same engine powers a quick command-line test, a shared internal chatbot, and a production REST endpoint.