Tutorials, deep dives and product notes — built for developers.
Head-to-head comparison of MiniMax M2.7 vs DeepSeek V4 Flash — two open-weight budget coding models. Flash wins on raw code (91.6% LiveCodeBench, 79% SWE-bench Verified), M2.7 wins on agentic value (56.22% SWE-bench Pro, 78.1 points per dollar). Full benchmarks, pricing, and speed analysis.
Head-to-head comparison of GPT-5.6 Terra vs Gemini 3.5 Flash across coding, agentic, reasoning, and multimodal benchmarks. Terra leads on terminal coding (87.4% vs 76.2%), Gemini dominates tool use (83.6% MCP Atlas) and costs 40% less. Full pricing, speed, and benchmark analysis.
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 GPT-5.4 mini compared across official coding, reasoning, tool-use, multimodal, computer-use and long-context results, plus pricing and a practical routing strategy.
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.
GPT-5.6 Luna vs DeepSeek V4 Pro: a sourced comparison of coding, 1M context, reasoning modes, MIT weights, caching, pricing, tools and deployment economics.
GPT-5.6 Luna vs GLM 5.2 compared across coding, reasoning, long context, tools, pricing, licensing and deployment. After Luna's permanent 80% price cut, Luna has the stronger managed capability and economics package; GLM 5.2 brings MIT weights and openness.
GPT‑5.6 Sol, Terra, and Luna compared across official coding, agentic, professional, science, computer-use, long-context, academic, tool-use, and cybersecurity benchmarks—with pricing tables, charts, radar, and a practical routing guide.
GPT-5.6 Sol vs Terra: a detailed family comparison across pricing, 1M context, coding, professional work, science, computer use, charts, radar, and a practical routing strategy.
GPT-5.6 Terra vs Claude Sonnet 5: nearly identical standard output pricing, 1M+ context, and a close SWE-bench Pro result—yet sharply different terminal scores, tooling, availability, and intro pricing.
Hy3 (295B MoE, Apache 2.0, $0.80/1M) vs GPT-5.5 (proprietary, $30/1M). GPT-5.5 leads coding (+11-42 pts), but Hy3 fights back on agents: wins MCP Atlas (+3.8), edges HLE w/tools (+1.0), near-ties BrowseComp (84.2 vs 84.4). All at 1/37th the cost. 5 charts, full breakdown.
Tencent's 295B MoE Hy3 just took the fight to DeepSeek's 1.6T V4 Pro — and won on 12 of 18 shared benchmarks. Pricing is close: Hy3 cheaper on fresh input/output, V4 Pro's disk caching is 16.5× cheaper on repeated contexts. Full breakdown.