Taking Tokenization off the Host for Agentic LLM Serving
Agentic workloads resend long contexts that barely change between calls. Prefix caching now skips most of their prefill, yet every request must still be tokenized in full before the cache can even be consulted. Tokenization, a CPU stage long treated as negligible, becomes the largest part of time-to-first-token (TTFT), and a frontend that tokenizes for a whole GPU fleet limits how many GPUs it can feed. We present GraphTok, a GPU tokenizer that runs the entire encoding pipeline, from pre-tokenization through byte-pair encoding (BPE) merging to token-ID assembly, as one replayable CUDA graph. GraphTok reproduces the reference token IDs bit-for-bit on GPT-2, Llama 3, Qwen 2.5, DeepSeek-V3, ...
| Authors | Mohammad Siavashi, Pascal Schwinte, Ali Banaei et al. |
|---|---|
| Primary category | cs.DC |
| Published | 9 October 2026 |
| Last updated at source | 9 October 2026 |
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