Tutorials, deep dives and product notes — built for developers.
GPT-5.6 Luna vs Qwen 3.6 Flash, the Alibaba API alias for Qwen3.6-35B-A3B, compared across official coding, agent, reasoning and vision benchmarks, context, multimodality and pricing.
GPT-5.6 Luna vs MiniMax M3 compared across coding, browsing, 1M context, video input, agent workflows, pricing and open-weight deployment. Luna leads published coding rows; M3 brings multimodal value.
Qwen 3.7 Max (60.6% SWE-bench Pro — highest proprietary score) vs MiniMax M3 (59.0%, $1.20/1M, open-weight + video). Just 1.6 points apart on Pro but 6.25× price gap. Alibaba's agent powerhouse vs the multimodal challenger.
MiniMax M3 (59.0% SWE-bench Pro, $1.20/1M, native video/image input) vs Gemini 3.5 Flash ($9/1M, 76.2% Terminal-Bench, 4× faster than frontier). Open-weight multimodal vs Google speed machine. Which wins for coding?
MiniMax M3 (59.0% SWE-bench Pro) vs DeepSeek V4 Pro (93.5% LiveCodeBench). M3 wins benchmarks + multimodality. DeepSeek wins price ($0.87/1M), ecosystem (2,150× more adoption), and algorithmic dominance. The generalist vs the specialist — which open-weight Chinese model fits your stack?