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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.
Qwen 3.7 Max (60.6% SWE-bench Pro, $7.50/1M, Anthropic API compatible) vs Kimi K2.6 (58.6%, $4.00/1M, 300 sub-agent swarms). Qwen leads all 6 shared benchmarks — but Kimi counters with open-weight, BrowseComp Agent Swarm (86.3%), and HLE w/tools (54%). Full comparison with real benchmark data.
GPT-5.5 dominates agentic coding (+14.2 Terminal-Bench, +4.4 SWE-bench Pro). Gemini 3.1 Pro wins on price (2.5× cheaper), reasoning (GPQA 94.3%), and multimodal breadth. Real benchmarks, pricing analysis, and a 9-point decision matrix for choosing the right enterprise model.
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.