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Models2026-04-21 · source-backed
Google's MoE model jumped from 6.6% to 86.4% on τ2-bench Retail for tool use. Math +330%, coding +175%. Runs at ~150 tok/s on consumer GPUs. Apache 2.0. The efficiency story here is the real news: 3.8B active parameters achieving Arena AI #6.
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Google DeepMind released Gemma 4 on April 2 with four model sizes (E2B, E4B, 26B MoE, 31B Dense) under Apache 2.0. Multimodal (text, vision, audio). 256K context. Native thinking and tool-calling optimized for agentic workflows. Day-zero ecosystem support across vLLM, llama.cp...
The models are good. The license is the real story. Google released Gemma 4 on April 2 with four variants: E2B, E4B, 26B MoE, and 31B Dense. All built on the Gemini 3 architecture. The 31B Dense variant claimed #3 on Arena AI's text leaderboard, beating models 20x its size. Th...
Google released Gemma 4 on April 2 with four model variants: E2B, E4B, 26B MoE, and 31B Dense. The license change is the first thing worth noting. Every previous Gemma had restrictions that made lawyers nervous. Gemma 4 is Apache 2.0. Full stop. Use it in any product, any way...
GLM-5.1 from Zhipu AI scored 58.4% on SWE-bench Pro. GPT-5.4 scored 57.7%. Claude Opus 4.6 scored 57.3%. That's the first time an open-weight model has ever topped a major coding benchmark against the best proprietary models. The specs matter. GLM-5.1 is a 754B-parameter mixtu...
Google dropped Gemma 4 and it's not incremental. The 31B dense model ranks #3 on Arena AI with an ELO of 1,452, scores 85.2% on MMLU Pro, 89.2% on AIME 2026, and 80.0% on LiveCodeBench v6. It outperforms models 20x its size. Under Apache 2.0. At $0.20 per run. Only Opus 4.6 an...
Amid a week of pricing and commerce stories, here's hard tech you can actually download. Google released DiffusionGemma on June 10, a 26B-parameter Mixture-of-Experts model (3.8B active) that generates text by diffusion instead of left-to-right decoding. The architecture is th...
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