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DeepSpec offers a full-stack codebase for speculative decoding, impacting Python developers and AI engineers. Learn how it can reshape your projects.
If you've been running models locally, you already know the drill. Every token an LLM produces...
Why Local LLMs Got Good in 2026: Multi-Token Prediction, Speculative Decoding, and the MoE Efficiency Leap
This article provides a step by step deployment guide for Gemma 4 to a Google Cloud Run hosted GPU...
DeepSeek DSpark is a hybrid speculative decoding framework that makes LLM inference up to 85% faster...
MTP Speculative Decoding with the 12B Gemma 4 QAT Model on NVIDIA L4, Cloud Run, MCP, and...
In 2023 I drafted a paper on routing between a large and small LLM via KL-divergence thresholds. Speculative decoding had already solved the problem more rigorously. Here is the post-mortem.
SpecKV (arXiv:2605.02888) shows fixed γ=4 costs 56% throughput. Adaptive gamma, KV cache compression effects, and vLLM production tuning guide.
Most LLM inference guides push speculative decoding as the silver bullet for speed. But when...
NVIDIA’s speculative decoding in NeMo RL speeds up rollout generation by 1.8× to 2.5× with no loss in output quality.