Speculative Decoding in 2026: EAGLE-3, Medusa-V2, and Self-Speculation
Speculative decoding is now standard for LLM inference. The 2026 algorithms — EAGLE-3, Medusa-V2, MTP — and how to choose between them.
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From the blog
Speculative decoding is now standard for LLM inference. The 2026 algorithms — EAGLE-3, Medusa-V2, MTP — and how to choose between them.
The three production-grade native speech-to-speech LLMs of 2026, side by side. Latency, prosody quality, function calling, and where each one breaks.
The "just paste the whole repo into the context window" era was a phase. Code-Review-Graph proves graphs of code intelligence outperform brute-force context dumps.
The state of streaming TTS in 2026 — ElevenLabs, OpenAI, Cartesia, Sesame, Deepgram Aura, and Inworld benchmarked on the metrics that matter.
Where every millisecond goes in a real voice-agent pipeline, and the 2026 techniques that get you under 500ms reliably.
Swarm-style multi-agent systems are trendy. Production data in 2026 says hierarchical orchestration wins on most real workloads. Why and when.
Synthetic data is now most of the post-training corpus at frontier labs. The 2026 pipelines — Magpie, Nemotron, Self-Taught — and how to build one.
A practical engineering deep dive into Claude Code 2.1 vs Cursor, covering architecture, tradeoffs, and what production teams need to know about AI coding tools.
Infrastructure-level look at Claude Haiku 4.5 Azure, including Azure Anthropic, deployment topology, region availability, and cost considerations.
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