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.
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.
DeepSeek V4 Flash ($0.28/1M, MIT, 284B) vs Qwen 3.6 Flash ($0.90/1M, Apache 2.0, 35B/3B). V4 leads every coding benchmark (Pro +3.1, HLE +13.4, LiveCodeBench +11.2). Qwen counters with multimodal (text+image+video), speed (90-172 tok/s), and tiny 3B active params. Chinese Flash showdown.
DeepSeek V4 Flash ($0.28/1M, MIT) vs Gemini 3 Flash ($3.00/1M). Flash leads Pro (+3.0), GPQA (+6.9), MCP Atlas (+7.0). Gemini leads OSWorld (65.1%), multimodal input, and Toolathlon. 10.7× price gap. Two Flash-tier models, zero overlap.
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?
Sandboxes are the unsung foundation of agentic AI. A deep dive into what they are, why LLMs cannot act without them, how the isolation technologies differ, the 2026 provider landscape (Modal, E2B, Daytona, Cloudflare, Vercel, Northflank, Blaxel, Docker Sandboxes), the secrets problem, and how to pick one.