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Three separate PRs merged into llama.cpp between April 11-13 add MERaLiON-2, Gemma 4's Conformer encoder, and Qwen3-Omni/ASR - making local voice AI inference practical on consumer hardware for the first time.
A Stanford study shows frontier AI models achieve 70-80% of visual benchmark scores with no images provided, exposing a fundamental flaw in how multimodal AI is evaluated.
Alibaba's Qwen3.5-Omni handles audio, video, images, and text in a single model pass - and generates speech in real time. The Plus variant hits SOTA on 215 benchmarks and edges out Gemini 3.1 Pro on audio tasks.
Meta's first proprietary frontier model leads on HealthBench Hard and scientific reasoning but trails rivals in coding and agentic tasks - with no public API yet.
LG AI Research released EXAONE 4.5, a 33B open-weight vision-language model that posts higher STEM scores than GPT-5-mini and Claude 4.5 Sonnet - but a non-commercial license caps its real-world reach.
Meta's first closed-source frontier model scores 52 on the Artificial Analysis Intelligence Index, leads on HealthBench Hard, and ships free at meta.ai - but has no public API yet.
Meta Superintelligence Labs releases Muse Spark, its first AI model built from scratch in nine months, landing 4th on the Artificial Analysis Intelligence Index.
A deep look at Microsoft's three new in-house AI models - MAI-Transcribe-1, MAI-Voice-1, and MAI-Image-2 - and whether they live up to the hype.
Gemma 4 is Google DeepMind's most capable open model family: four variants from 2B to 31B, Apache 2.0 license, multimodal across text/image/video/audio, and the 31B Dense ranking #3 on Chatbot Arena against all open-weight models globally.
Google's Gemma 4 family - four models, full Apache 2.0 licensing, and benchmark scores that challenge models 10x their size - is the most consequential open-weight release of 2026 so far.
Google releases Gemma 4 with a 26B MoE, 31B Dense, and two edge variants under Apache 2.0 - claiming the highest intelligence-per-parameter of any open model.
A technical comparison of how Claude, GPT-4o, Gemini, Grok, Pixtral, Qwen, and DeepSeek handle image inputs - resizing pipelines, token math, and undocumented gotchas.
