5d ago · 6 min read · On May 5, 2026, Google released Multi-Token Prediction (MTP) drafters for the Gemma 4 family. The headline claim — up to 3x inference speedup — is technically accurate on specific hardware. The more realistic number for most developer setups is 1.7x ...
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May 6 · 8 min read · An 870 MB drafter model turned Dense 31B from 6.5 → 18.8 tok/s. No model swap, no training, no quality degradation. If you have a DGX Spark, there's no reason not to use this. Key Results Model Fra
Join discussionMay 2 · 8 min read · The interesting AI tool developments in April 2026 are not happening at the general-purpose chatbot layer. ChatGPT and Claude are both strong and well-documented. The tools below sit in a different category: they are specialized, they do specific thi...
Join discussionMay 2 · 10 min read · Google DeepMind released Gemma 4 on April 2, 2026, and two things make it immediately significant: Apache 2.0 licensing and hardware efficiency that no competitor at this capability level matches. Gemma 4’s 31B Dense model ranks third globally among ...
Join discussionMay 1 · 10 min read · Gemma 4 26B vs 31B: Which Model to Run Locally with Ollama If you followed our Gemma 4 Local Setup Guide, you already have Ollama running and know the four model sizes exist. But once you're past the basics, a real question stays open: between the 26...
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Apr 12 · 9 min read · Most of the Gemma 4 coverage you've seen is benchmark-focused. Gemma 4 31B scores X on MMLU. It beats Y model on HumanEval. Numbers, charts, leaderboard positions. None of that coverage answers the question I keep seeing in developer forums, Slack ch...
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