Tutorials, deep dives and product notes — built for developers.
GLM-5.2 (62.1% Pro, MIT, $4.40/1M) vs MiniMax M3 (59.0%, open-weight, $1.20/1M). GLM leads all shared benchmarks (+3.1 Pro, +15.0 TB 2.1, +2.8 MCP Atlas). But M3 is 3.7× cheaper, multimodal (video+image+desktop), and leads BrowseComp (83.5%). Text-only powerhouse vs the Swiss Army knife. Full comparison.
Claude Opus 4.8 (69.2% Pro, $25/1M, AA Index #1) vs MiniMax M3 (59.0%, $1.20/1M, open-weight + video). Opus dominates 5 of 6 shared benchmarks by 8-13 points. But M3 is 21× cheaper, open-weight, and wins BrowseComp (-4.2). Full comparison with VP of VentureBeat research plus MiniMax/Minimax blog data.
MiniMax M3 (59.0% Pro, $1.20/1M, 1M ctx) vs GLM 5.1 (58.4%, $4.40/1M, 200K ctx). Both Huawei Ascend, both MIT, both Chinese. 0.6 pts apart on Pro. M3 leads context + multimodal. GLM leads reasoning + CyberGym #1 + pure MIT + $3/mo plan. Full comparison.
MiniMax M3 (59.0% SWE-bench Pro, $1.20/1M) beats GPT-5.5 (58.6%, $30/1M) on the hardest coding benchmark at 25× less cost. But GPT-5.5 dominates Terminal-Bench (+16.7), OSWorld (+8.7), GPQA and HLE. 1M context, native video, MSA architecture, open-weight vs proprietary. Full comparison.
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?