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Performance comparisons are based on third-party benchmarking or internal testing. Observed inference speed improvements versus GPU-based systems may vary depending on workload, configuration, date and models being tested.
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AI inference is the process of running a trained AI model on new input to produce an output.
Time to first token, often abbreviated TTFT, is the delay between sending a request to an AI model and receiving the first generated output token.
Cost per token is the price charged to process or generate tokens with an AI model.
An inference API is a hosted interface that lets an application send input to a trained AI model and receive generated output without managing the underlying model-serving infrastructure.
The fastest AI is not a single chatbot, model, or chip.
Latency is the amount of time it takes an AI system to return a response for a specific request.
Tokens per second measure how quickly an AI model generates tokens, usually after the model has started responding.
LLM inference is the process of running a trained large language model to generate text, code, structured data, reasoning traces, or tool calls in response to a prompt.
Real-time AI is AI that responds quickly enough to support an interactive human or application workflow.
Fast AI inference is AI model serving that returns useful outputs with low latency, high tokens per second, and production throughput.
