Tutorials, deep dives and product notes — built for developers.
GLM-5.2 (62.1% Pro, MIT, $4.40) vs Qwen 3.7 Max (60.6%, proprietary, $7.50). Near-ties everywhere: Pro +1.5, MCP +0.6, HLE -0.9. Qwen dominates math (GPQA 92.4%) and is the Agent Frontier (35hr autonomous). GLM is MIT open-weight. Full comparison.
GLM-5.2 (62.1% Pro, $4.40/1M) vs DeepSeek V4 Pro (55.4%, $0.87/1M). GLM leads all shared benchmarks (+6.7 Pro, +6.5 HLE, +3.4 MCP). But DeepSeek dominates competitive coding: LiveCodeBench 93.5% (#1 global), Codeforces 3206, GPQA 90.1%. Both MIT, both 1M context. Full comparison.
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 leads every benchmark — but GLM-5.2 is within 0.7 pts on FrontierSWE and 0.8 pts on MCP Atlas. At $4.40 vs $25 per 1M (5.7× cheaper) with MIT open weights, GLM-5.2 is the first open-weight model that makes Opus look expensive. Full 8-benchmark comparison from Z.AI & LLM Stats data.
GLM-5.2 (62.1% Pro, MIT open-weight, $4.40/1M) beats GPT-5.5 (58.6%, $30/1M) on SWE-bench Pro by 3.5 points at 1/7 the cost. Also leads HLE w/tools (+2.5), FrontierSWE (+1.8), MCP Atlas (+1.7). GPT-5.5 counters with DeepSWE (+23.8), TB 2.1 (+3.0). Full comparison with 12 shared benchmarks from Z.AI/VentureBeat data.
SpaceX exercised its $60B option to acquire Cursor today (June 16, 2026). Here's how the AI coding tool compares to GitHub Copilot (4.7M paid users, 42% market share). Pricing, SWE-bench scores, agent capabilities, enterprise features. Plus: what the SpaceX deal means for developers.
Anthropic's two best non-Mythos models face off. Claude Opus 4.8 ($25/1M, 69.2% Pro) leads Sonnet 4.6 ($15/1M) on all benchmarks by 1-13 pts. But Sonnet handles 1M context at standard pricing, costs 1.7x less, and was preferred by devs over Opus 4.5. Full sibling comparison.
Google's two best models face off. Gemini 3.1 Pro leads on reasoning (HLE +4.2, MRCR +7.6, ARC-AGI-2 +5.0). Gemini 3.5 Flash dominates agents & coding (+14.9 Finance, +5.9 Terminal-Bench, +5.4 MCP Atlas), is 25% cheaper, and 4× faster. All data from Google DeepMind's official model card.
Claude Opus 4.8 (69.2% Pro, $25/1M) dominates every benchmark vs Kimi K2.6 (58.6%, $4/1M) by 3-11 pts. But Kimi fights back on BrowseComp (-3.9), Agent Swarm (300 sub-agents), DeepSearchQA (92.5%), and is 6.25× cheaper. Full comparison with real benchmark data, 10-point verdict.
GPT-5.5 and Kimi K2.6 are tied at 58.6% SWE-bench Pro. But Kimi leads HLE w/tools (54.0%), DeepSearchQA (+13.9), and Agent Swarm (300 sub-agents). GPT counters with OSWorld (+1.9), BrowseComp, Terminal-Bench (Codex CLI 82.7%), and 7.5× higher cost. The most evenly matched comparison of 2026.
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.
GPT-5.5 (82.7% Terminal-Bench, 58.6% Pro, $30/1M) vs Gemini 3.5 Flash (83.6% MCP Atlas, 76.2% TB 2.1, $9/1M, 152 tok/s). GPT-5.5 dominates reasoning & long context. Flash dominates tool orchestration & speed. Official Google DeepMind model card data. 10-point verdict.