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TokenPak — Latency

TL;DR

TokenPak runs as a proxy in front of your model provider. Like any network proxy, it can add network round-trip overhead between your application and the upstream API — how much depends entirely on your deployment path (where the proxy runs relative to your app and the provider, and whether connections are reused).

Two things are worth measuring separately, and we keep them separate here:

  • TokenPak's own processing — routing, token counting, cache lookup, and context handling. This is distinct from the network it sits on.
  • End-to-end latency — the wall-clock difference an application sees, which is dominated by network hops and connection behavior, not by TokenPak's internal work.

We do not publish specific latency numbers yet. Any figure we publish will be backed by a reproducible benchmark receipt (see Benchmarks below) rather than an ad-hoc measurement.

What affects the latency you see

  • Deployment path. Running the proxy on the same machine or local network as your application avoids most avoidable network overhead. A proxy reached over the public internet adds more round-trip time than one on localhost.
  • Connection reuse. Warm, pooled connections behave very differently from cold ones. Throughput under sustained load benefits from connection pooling.
  • Cache hits. On a cache hit, TokenPak avoids re-sending and recomputing context, which removes work from the request path.
  • Workload shape. Batch, async, and chat workloads tolerate added latency far more readily than hard real-time paths.

Minimizing avoidable overhead

  • Run it close to your app. Same-machine or same-network deployment keeps the added network round-trip small.
  • Reuse connections. Keep the proxy warm under load rather than paying cold-start costs per request.
  • Lean on caching. Repeated-context workloads benefit most, since cache hits take work off the request path.

When the proxy is a good fit

Good fits

  • Batch processing and overnight jobs
  • Chat and agent workflows, where human/interaction latency dominates
  • Development and testing
  • Production workloads where token-cost savings outweigh added latency

Be deliberate for

  • Hard real-time paths with strict, latency-sensitive SLAs
  • Latency-sensitive UIs — in these cases, run the proxy on the same machine/network, or use a deployment path that avoids extra network hops

Benchmark evidence

TokenPak requires a frozen-fixture benchmark run before publishing a latency, throughput, or cost figure so the result is reproducible rather than a one-off measurement. This page does not yet carry a validated run, so:

  • We deliberately do not quote a specific latency overhead.
  • The best way to understand TokenPak's impact on your workload is to measure it in your own environment and deployment path.

Any figure added here must include the receipt and run identity needed to reproduce it.

FAQ

Q: Does the proxy add latency vs. calling the API directly? A: It can, because it adds a network hop — how much depends on your deployment path. On cache hits, the work TokenPak would otherwise do is taken off the request path. We don't quote a specific number until it's benchmark-backed.

Q: Should I use the proxy if latency matters? A: For batch, async, agent, and chat workloads, added latency is typically not the deciding factor. For hard real-time paths, run the proxy on the same machine/network, or choose a deployment path that avoids extra network hops.

Q: How do I know what it costs me? A: Measure it in your own environment and deployment path. Receipt-backed figures from the benchmark suite will follow.