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Models2026-09-11 · source-backed
North Small Translate is a mixture-of-experts model with 218B total and 25B active parameters, covering 50 languages. It scores 83.60 on WMT26, and an agentic multi-pass variant scores 84.36. DeepL NextGen scores 81.37 and Google Translate 68.20. On book-length translation in a single call it scores 48.9 to Google's 21.3. The weights are CC BY-NC 4.0, so commercial use goes through Cohere or RWS. YuE2-3B, a new open music model whose best-of-8 score edges past Suno v5, has the same non-commercial license.
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Open-weight trackers put it at 77.2% on MMLU-Pro, surpassing the prior-gen 27B model. If it holds, it's another small open model matching a previous flagship and lowering the bar for on-prem deployment. Single-source benchmark, so verify the numbers before you build on the exa...
Announced July 30, Gemini 3.1 Flash-Lite and 3.5 Flash join Cohere and Meta options, with Oracle explicitly framing model selection as per-scenario price-performance. The incumbent ERP vendor is conceding the model layer entirely and defending the data and workflow layer. That...
Google's HF org lists diffusiongemma-26B-A4B-it (~4B active), an image-text-to-text Gemma member that's diffusion-style rather than purely autoregressive (Hugging Face). No detailed announcement yet, which is why I'm flagging it low. But a diffusion approach inside the Gemma o...
Cohere launched North Mini Code on June 9 under Apache 2.0, its first developer-focused model. The shape is the pitch: 30B parameters, mixture-of-experts, only ~3B active, and it runs on a single H100. It scores 33.4 on the Artificial Analysis Coding Index, competes on SWE-Ben...
In its Q3 FY2026 earnings ($82.9B revenue, +18%), Microsoft disclosed something more important than the revenue number: a structural shift in how software gets sold. The company's AI business crossed $37B annual run rate, up 123% year-over-year. But the real signal is the pric...
poetiq.ai — Detailed technical breakdown of how a $40K-hardware startup achieved 54% on ARC-AGI-2 (vs. Google's 45% at nearly 3x the cost). The key innovation: "learned test-time reasoning" — an iterative refinement meta-system where solutions are generated, receive structured...
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