Cross-Provider Speculative Decoding: Acceptance Rate Collapses Past 32K Context
hoyasgirl25 · reddit · 2026-08-13
A developer experimenting with cross-provider speculative decoding (local draft model + third-party verifier) reports a severe bottleneck: acceptance rates plummet from 0.71 to 0.18 when the prefix exceeds 32K tokens.
Although next-token KL divergence remains stable during independent sampling and common issues like tokenizer skew and precision differences are ruled out, the divergence appears strongly position-dependent. The author suspects the provider's API might be applying a different RoPE scaling implementation or hidden context preprocessing, and is seeking advice on debugging this black-box issue without building a complex position-by-position logit fingerprinting harness.
More from Infra
- Enthusiasts Discuss Running Massive Qwen3.8-2.4T Models Locally — segmond · 2026-08-13
- Running DeepSeek V4 Flash Locally on 2x DGX Sparks Delivers Prosumer-Grade Performance — andrewchen · 2026-08-13
- Is Local Generative AI Worth It Anymore? Developers Struggle Against Closed Cloud Models — ImaginaryEffective63 · 2026-08-13
- Intel Razor Lake AX Info Surfaces, Targeting AMD's Future Local AI Chips — Terminator857 · 2026-08-13
- Investor Burry Shorts Compute Stocks, Sparking Debate Over AI Compute Shortage — inductionheads · 2026-08-13
- $14.6B AI Compute Bet: Jane Street Needs 20.3% Annual Yield to Break Even — adrianscottcom · 2026-08-13