Model: "gemma-4-31b"

Apr 30
not much happened today
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gpt-5.5 claude-mythos-preview gpt-5.5-pro qwen3.6-27b hy3-preview grok-4.3 gemma-4-31b glm-5.1 deepseek-v4-flash openai anthropic x-ai tencent deepseek cybersecurity model-efficiency multimodality model-benchmarking agentic-ai model-cost-optimization context-windows model-performance open-weight-models software-integration security-updates sama scaling01 cryps1s polynoamial ajambrosino arix
OpenAI's GPT-5.5 achieves top-tier performance in long-horizon cyber tasks, matching or surpassing Claude Mythos Preview with a 71.4% pass rate and showing ongoing improvement beyond 100M tokens inference. OpenAI also released an Advanced Account Security update for ChatGPT enhancing phishing resistance. The Codex update expands beyond coding to general computer tasks, improving speed by up to 42% and introducing role-based onboarding and app integrations. Economically, GPT-5.5 Pro shows a slight SOTA improvement on CritPt with ~60% lower cost and token use compared to GPT-5.4 Pro. In open-weight models, Qwen3.6 27B leads under 150B parameters with an Intelligence Index score of 46, featuring 262K context, native multimodal input, and efficient BF16 weights. Tencent's Hy3-preview (295B total, 21B active MoE) scores 42 on the Intelligence Index with strong scientific reasoning on CritPt. xAI's Grok 4.3 shows sharp improvements on agentic benchmarks with reduced cost.
Apr 02
Gemma 4
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gemma-4 gemma-4-31b gemma-4-26b-a4b google-deepmind multimodality long-context model-architecture moe local-inference model-optimization function-calling quantization jeffdean _philschmid rasbt ggerganov clattner_llvm julien_c clementdelangue
Google DeepMind released Gemma 4, a family of open-weight, multimodal models with long-context support up to 256K tokens under an Apache 2.0 license, marking a major capability and licensing shift. The lineup includes 31B dense, 26B MoE (A4B), and two edge models (E4B, E2B) optimized for local and edge deployment with native multimodal support (text, vision, audio). Early benchmarks show Gemma-4-31B ranking #3 among open models and strong scientific reasoning performance with 85.7% GPQA Diamond. Day-0 ecosystem support includes llama.cpp, Ollama, vLLM, and LM Studio, with notable local inference performance on hardware like M2 Ultra and RTX 4090. The architecture features hybrid attention and MoE layering, diverging from standard transformers. Community and developer engagement is high, with rapid adoption and tooling integration.