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25 AI models battle in 8 brutal, objective rounds – perfect for powering OpenClaw agents in 2026. Which LLM crushes tool calling, code gen, debugging, and long context for your autonomous agents? Surprises: Budget models like GPT-5 Nano and Claude Haiku 4.5 dominate real agent workflows, GLM-5 ties flagships at 1/5th the cost, and every model now aces 'long context' that matters for agent memory. Ideal for OpenClaw users picking backends (Claude Opus, GPT-5.4, Gemini Flash, Grok, Kimi, DeepSeek, GLM-5 & more). Surprises everywhere: Budget Claude Haiku 4.5 scores perfect 10/10 on complex Express.js API + Dijkstra + event sourcing "Coder"-named models score 0/10 on code gen but 10/10 on debugging Every single model aces 73KB long context (long context is basically solved in 2026) GLM-5 ties Claude Sonnet & Opus at 9.89… but costs ~1/5th the price GPT-5 Nano crushes at just $0.35 per million tokens Watch to see the full leaderboard, epic fails, value kings, and my top picks for 2026. Timestamps: 00:00 – Intro: 25 Models, 8 Rounds, 1 Winner 00:09 – How We Tested + Model Tiers (A/B/C) 00:37 – Round Breakdown (What Each Tests) 01:31 – Round 1: Code Generation (Express.js API Beast) 02:23 – Round 2: Debugging Python Pipeline 03:11 – Round 3: Pure Math & Logic (Einstein Puzzle Fail) 04:21 – Round 4: Strict Nested JSON Instruction Following 05:18 – Round 5: 73KB Long Context Comprehension (Everyone Wins) 05:57 – Round 6: Tool/Function Calling with Traps 06:54 – Round 7: Graduate-Level CS Knowledge 07:36 – Round 8: Constrained Creative Writing (Judged by Claude Opus) 08:28 – Spectacular Failures Montage 09:06 – Head-to-Head Value Matchups (GLM-5 vs Sonnet, Grok 4.1 Fast vs Grok 3) 09:53 – Final Leaderboard Reveal 11:01 – Value Chart & Bang-for-Buck Kings 11:31 – Top Picks: Best Overall, Best Budget, Best Value, Sleeper Hits 12:04 – Outro + Reproducible Harness + Subscribe! Which model surprised you most? Drop it in the comments + suggest the next one to test! #LLM #AI #Claude #GPT5 #Gemini #Grok #DeepSeek #GLM5 #2026AI Twitter: @smhumair