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.
Qwen 3.5
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.
Qwen3.5-27B vs Gemma 3 27B: Same Parameter Count, Completely Different Models
A data-driven comparison of Alibaba's Qwen3.5-27B and Google's Gemma 3 27B - two 27B dense models that share a parameter count and almost nothing else.
Qwen3.5-27B vs Mistral Small 3.2: Apache 2.0 Heavyweights Go Head to Head
A data-driven comparison of Alibaba's Qwen3.5-27B and Mistral's Small 3.2 - two Apache 2.0 dense models in the 24-27B range with very different benchmark profiles and deployment strengths.
Qwen3.5-27B vs Phi-4: When Twice the Parameters Is Not Twice as Obvious
A data-driven comparison of Alibaba's Qwen3.5-27B and Microsoft's Phi-4 - a 27B hybrid architecture versus a 14B STEM specialist, testing whether raw parameter count or training efficiency wins in practice.