vLLM Splits Prefill and Decode, TileRT Takes Over Decode
vllm_project · x · 2026-07-15
The vLLM team shared a specific use case: after decoupling vLLM's prefill and TileRT's decode, the decode side can be hot-swapped based on the workload.
Key Points
- The TileRT team integrated this via the vLLM V1 connector interface, requiring no changes to vLLM code.
- It defaults to vLLM's decode to ensure throughput; for scenarios prioritizing low latency, like agents or real-time assistants, it can switch to TileRT decode.
- Both sides maintain the same OpenAI-compatible interface and prefix caching; switching is essentially just a routing change.
Performance Data
- TileRT reported that on GLM-5.1-FP8, using 8× B200 + MTP, single-user decode reached around 618 tok/s.
- This is roughly 2 times faster than its baseline without MTP.
- At peak acceptance rates, speed approaches 800 tok/s.
The authors thanked TileRT and inferact for their collaboration.
Related event: vLLM and TileRT Introduce Decoupled Inference Stack(3 posts)→
More from Infra
- Ubicloud publishes "Fixing Tool-Call Accuracy in vLLM" — petrusenko_max · 2026-10-26
- Meta approves nonvoting Class C shares as 2026 capex guidance hits $135B–$145B — thione · 2026-10-26
- Unsloth Ships MiniMax-M3.1-Flash Quants: 2-bit Retains 91.5% Accuracy, Runs in 150GB RAM — danielhanchen · 2026-10-26
- Engineer with thousands of fabricated devices pours cold water on photonic crystal modulator yields — jwt0625 · 2026-10-26
- Anthropic S-1 reveals 48 cents of compute cost per dollar of Q2 revenue — nmasc_ · 2026-10-26
- Persistent AI joins UR network to route private AI inference with encrypted, IP-hidden traffic — 0xSammy · 2026-10-26