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.
Articles Tagged "MoE"
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.
Mistral Small 4: 128 Experts, 6B Active, Apache 2.0
Mistral AI releases Small 4 - a 119B MoE with only 6B active parameters, 256K context, configurable reasoning, and Apache 2.0 license. Plus a new NVIDIA partnership to co-develop frontier open models.
NVIDIA Nemotron 3 Super 120B-A12B
NVIDIA Nemotron 3 Super is a 120B-parameter open model with 12B active at inference, combining Mamba-2, LatentMoE, and Multi-Token Prediction for agentic workloads with a 1M token context window.
NVIDIA Ships Nemotron 3 Super - 120B Open Model for Agents
NVIDIA releases Nemotron 3 Super, a 120B-parameter open model with only 12B active at inference, combining Mamba-2 and Transformer layers for agentic AI workloads with a 1M token context window.
vLLM 0.17 Ships FlashAttention 4 and Live MoE Scaling
vLLM v0.17.0 adds FlashAttention 4, elastic expert parallelism for live MoE rescaling, full Qwen3.5 support, and a performance-mode flag, all in 699 commits from 272 contributors.
Qwen3.5 MoE vs Kimi K2.5 for Coding - Price Breakdown
Kimi K2.5 leads every coding benchmark, but Qwen3.5-35B-A3B delivers 87-93% of that performance at 3-4x lower cost and runs on a single consumer GPU. Here is the full breakdown.
