An agent is a dependency chain
A chat response can feel acceptable even when it starts slowly, provided the answer streams smoothly. An agent may need to finish one generation before it knows which tool to call, then wait for the result before generating the next step.
That dependency makes each decoding delay part of the critical path. A few hundred milliseconds repeated across planning, tool selection, verification and sub-agent coordination can become seconds or minutes of additional wall-clock time.
Separate prefill, decode and tools
Prefill processes the input context and strongly depends on prompt length and memory bandwidth. Decode produces new tokens sequentially. External tools add their own network, database or execution latency.
Measure time to first token, output tokens per second, tool duration and idle orchestration separately. A fast decoder will not repair an agent that repeatedly rereads unnecessary context or waits on a slow external API.
When specialized decode helps
Specialized acceleration is most valuable when output generation is a large, repeated share of the critical path and the workload has enough sustained demand to use the hardware efficiently. Coding, research and multi-agent systems can fit that pattern.
The benefit may be smaller for workflows dominated by retrieval, browser actions or long-running jobs. In those cases, better caching, parallel tool execution and context compression can improve completion time without changing accelerators.
A practical tracing plan
Give every agent turn a trace ID and capture input length, first-token latency, decode rate, output length, tool calls and outcome. Plot the slowest successful and failed sessions rather than relying only on averages.
Optimize the largest measured component, then repeat. The goal is not maximum tokens per second in isolation; it is faster correct completion while preserving the permissions, review and evidence that make the agent safe to use.
Sources & further reading
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