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Comprehensive comparison of GLM 5.3 vs Claude Opus 5 with interactive radar capability chart, direct score bars, token pricing, and benchmark analysis. Updated August 19, 2026.
GLM-5.3 vs GPT-5.6 Sol benchmark and pricing breakdown. How Z.ai's upcoming open-weight model beats OpenAI's flagship on CyberGym (84.5%) and saves 85%+ on compute, while Sol leads on exploitation chains.
Complete benchmark breakdown of GLM-5.3 vs GLM-5.2. How Z.ai extracted massive gains in DeepSWE (+45%), Terminal-Bench 3.0 (+515%), and global #1 on CyberGym purely through scaled post-training.
Claude Opus 5 vs Kimi K3: Opus 5 leads the independent BenchLM aggregate 85.88 to 79.98 and posts a 43.3–43.5% Frontier-Bench score that K3 has never even been tested on.
Interactive DeepSWE v1.1 leaderboard updated with GLM-5.3-Flash at 63.4% and Qwen3.8-Flash-Next at 58.7% added. 25+ models ranked by long-horizon software engineering ability. Updated August 28, 2026.
GLM-5.2 vs GLM-5.1: the full sibling comparison. DeepSWE +28.2 (18.0→46.2), HMMT +9.9, GPQA +5.0, Pro +3.7. 200K→1M context (5×). Single→dual thinking modes. Anthropic API native. Same MIT license, same $4.40/1M. All data from Z.ai official blog.
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.
What SWE-bench Pro actually measures, how it works (1,865 tasks, 41 repos, 123 languages), why OpenAI abandoned SWE-bench Verified, the DeepSWE audit that found 32% verifier errors, and how to use coding benchmarks correctly. The definitive explainer.