Arcee's Trinity-Large: 398B Open Reasoning at $0.90
Arcee AI ships Trinity-Large-Thinking, a 398B sparse MoE reasoning model under Apache 2.0 that hits 91.9% on PinchBench for $0.85 per million output tokens on OpenRouter.
Articles Tagged "MoE"
Google Gemma 4
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 Gemma 4 Ships Four Open Models Under Apache 2.0
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.
Nemotron 3 Super Review: Best Open Model for Agents
NVIDIA Nemotron 3 Super is the strongest open-weight model for agentic coding as of March 2026, but its efficiency-first design means real trade-offs on general knowledge and chat quality.
Kimi K2.5 Review: Open Weights, Agent Swarms, Caveats
Moonshot AI's Kimi K2.5 delivers best-in-class open-weight math and a genuinely novel multi-agent architecture, but a brutal hallucination rate and slow inference limit its real-world reliability.
Xiaomi MiMo-V2-Pro
Xiaomi's MiMo-V2-Pro is a 1-trillion-parameter MoE model with 42B active params, 1M context, and agentic coding performance that rivals Claude Sonnet 4.6 at a fraction of the cost.
Nemotron-Cascade 2: 30B Open MoE, One GPU, Beats 120B
NVIDIA's new Nemotron-Cascade-2-30B-A3B activates just 3B parameters per token, runs on a single RTX 4090, and outscores NVIDIA's own 120B model on coding and math benchmarks.
Leanstral Outperforms Claude Sonnet at Formal Code Proofs
Mistral's new open-source Lean 4 agent scores higher than Claude Sonnet on formal proofs at one-fifteenth the cost, raising the bar for trustworthy AI code generation.
MiniMax M2.7 Claims to Automate Its Own Training
MiniMax's new 2,300B MoE model tops the Artificial Analysis Intelligence Index and claims to run 30-50% of its own RL research workflow autonomously.
Mistral Small 4 Review: One Model, Three Jobs
Mistral Small 4 packs reasoning, vision, and agentic coding into a 119B MoE under Apache 2.0 - a serious small-model contender at a price that's hard to ignore.
MiniMax M2.7
MiniMax M2.7 is a 230B MoE coding agent that handles 30-50% of MiniMax's own RL research workflow, scoring 56.22% on SWE-Pro and 78% on SWE-bench Verified at $0.30/M input tokens.
Mistral Small 4
Mistral AI's unified MoE model - 119B total parameters, 6B active per token, 128 experts, 256K context, configurable reasoning, Apache 2.0 license.
