Llama 4 Maverick
Meta's Llama 4 Maverick packs 400B total parameters into a 128-expert MoE architecture with only 17B active per token, beating GPT-4o on Chatbot Arena while matching DeepSeek V3 on reasoning at half the active parameters.
Articles Tagged "MoE"
Llama 4 Scout
Meta's Llama 4 Scout is a 109B-total, 17B-active MoE model with 16 experts and a 10M-token context window - the longest of any open-weight model - with native multimodal support for text and images.
Mistral Large 3
Mistral Large 3 is a 675B-parameter MoE model activating 41B per token with native multimodal support, a 256K context window, and Apache 2.0 licensing - Europe's first frontier-class open-weight model.
Nemotron 3 Nano 30B-A3B
NVIDIA's hybrid Mamba2+MoE model packs 31.6B total parameters but activates only 3.2B per token, delivering frontier-class reasoning with 3.3x the throughput of comparable models on a single H200 GPU.
Qwen3.5-122B-A10B vs DeepSeek V3.2: Efficiency vs Raw Power in Open-Weight AI
A benchmark-by-benchmark comparison of Qwen3.5-122B-A10B and DeepSeek V3.2 - the efficiency-optimized underdog versus the brute-force open-source heavyweight.
Qwen3.5-122B-A10B vs Llama 4 Maverick: The Efficiency Gap Nobody Expected
A data-driven comparison of Alibaba's Qwen3.5-122B-A10B and Meta's Llama 4 Maverick - two open-weight MoE models with radically different approaches to parameter efficiency and benchmark performance.
Qwen3.5-122B-A10B vs Mistral Large 3: When 4x More Parameters Buys You Less
A data-driven comparison of Qwen3.5-122B-A10B and Mistral Large 3 - two Apache 2.0 MoE models where the smaller one dominates text benchmarks despite a 4x active parameter disadvantage.
Qwen3.5-35B-A3B vs GLM-4.7-Flash: Two Chinese MoE Models, Very Different Strengths
Head-to-head comparison of Qwen3.5-35B-A3B and GLM-4.7-Flash - two Chinese-origin 30B-A3B MoE models with Apache 2.0/MIT licenses that dominate different benchmarks despite near-identical parameter budgets.
Qwen3.5-35B-A3B vs Llama 4 Scout: 3B Active Parameters vs 17B - Does 5.7x More Compute Actually Win?
David vs Goliath: Qwen3.5-35B-A3B activates 3B parameters and beats Llama 4 Scout's 17B active on MMLU-Pro, GPQA, and coding benchmarks - but Scout's 10M context window and native multimodal support tell a different story.
Qwen3.5-35B-A3B vs Nemotron 3 Nano 30B-A3B: Benchmarks vs Throughput in the 3B Active Parameter Class
A data-driven comparison of Alibaba's Qwen3.5-35B-A3B and NVIDIA's Nemotron 3 Nano 30B-A3B - two ~30B MoE models activating ~3B parameters that take fundamentally different architectural approaches to the same problem.
MiniMax M2.5
MiniMax M2.5 is a 230B MoE model (10B active) that scores 80.2% on SWE-Bench Verified while costing 1/10th to 1/20th of frontier competitors like Claude Opus 4.6 and GPT-5.2.
Qwen 3.5 Medium Series Drops Four Models That Make the 235B Flagship Obsolete
Alibaba releases four Qwen 3.5 medium models - Flash, 35B-A3B, 122B-A10B, and 27B - that match or beat the previous 235B flagship at a fraction of the compute. The 35B model activates just 3 billion parameters and still outperforms Qwen3-235B-A22B.
