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Qwen3.5-122B-A10B is a 122B-parameter MoE model activating 10B parameters per token, narrowing the gap between medium and frontier models with top scores in GPQA Diamond (86.6), MMMU (83.9), and OCRBench (92.1). Apache 2.0 licensed.
Qwen3.5-35B-A3B is a 35B-parameter MoE model activating just 3B parameters per token that surpasses the previous Qwen3-235B flagship across language, vision, and agent benchmarks. Apache 2.0 licensed.
Qwen3.5-Flash is Alibaba's hosted production model with 1M context, built-in tools, and multimodal support at $0.10/M input tokens - one of the cheapest frontier-tier APIs available.
MIT spinoff Liquid AI releases LFM2-24B-A2B, a hybrid mixture-of-experts model that activates only 2.3B parameters per token, fits in 32GB RAM, and hits 112 tokens per second on a consumer CPU.
Google DeepMind's Gemini 3.1 Pro leads on 13 of 16 benchmarks with 77.1% ARC-AGI-2, 94.3% GPQA Diamond, and a 1M-token context window at $2/M input.
Alibaba's Qwen team releases Qwen3.5-397B-A17B, an open-weight mixture-of-experts model with native multimodal support and a hybrid attention architecture that runs 8x faster than its predecessor. Apache 2.0 licensed.
Shanghai AI lab StepFun open-sources Step 3.5 Flash, a 196B sparse MoE model that activates only 11B parameters per token while matching frontier models on reasoning, coding, and agentic benchmarks.
OpenAI's open-weight 21B MoE reasoning model with 131K context, Apache 2.0 license, and o3-mini-level benchmark performance running in 16 GB of memory.
