GLM 5.1 vs GPT-4o

Choose GLM 5.1 if you want…

• ✓Higher intelligence (Artificial Analysis index 51)
• ✓Lower price ($2.15 / 1M blended)
• ✓Larger context window (200K)

Choose GPT-4o if you want…

• ✓Faster output (~198.3 tokens/sec)

GLM 5.1

GLM-5.1 from Z.ai is built for one thing above all else: software engineering that runs on its own. A 754-billion parameter Mixture-of-Experts model, it tops the SWE-Bench Pro leaderboard at 58.4%, edging out both GPT-5.4 and Claude Opus 4.6 on real-world coding tasks. What sets it apart in practice is stamina — it can pursue a single engineering goal autonomously for up to eight hours, sustaining hundreds of iterations and thousands of tool calls without human intervention. Users consistently praise this long-horizon execution for agent-based workflows where other models stall. It also delivers fast responses, with a time-to-first-token of 1.33 seconds against a class median of 2.37 seconds. The honest trade-off: GLM-5.1 accepts text only, with no image input, making it a poor fit for visual debugging or UI-centric tasks. It also tends toward verbosity in practice, which can inflate token costs. For teams building autonomous coding pipelines, though, it earns its place at the top of the leaderboard.

GPT-4o

Speed is GPT-4o's defining trait. Where comparable models average 61 tokens per second, GPT-4o delivers nearly 200 — and its native audio pipeline hits 320ms response latency, making it the practical choice for voice interfaces and real-time chat. It also collapses text, image, and audio processing into a single unified model rather than routing across separate systems, which produces more coherent multimodal reasoning without the awkward handoffs. Users feel this difference acutely. When OpenAI tried to retire GPT-4o in early 2026, the backlash was fierce enough to reverse the decision — petitions, mass unsubscribe threats, and user surveys suggesting 95% found no adequate replacement. That kind of loyalty comes from how the model feels in practice: snappy, versatile, fluent across 50+ languages, and capable of web search that reasoning-focused models like o1 lack. The honest caveat: GPT-4o trades raw reasoning depth for speed. It scores below average on Artificial Analysis's Intelligence Index and struggles with complex multi-step logic. For hard reasoning or large-document tasks, newer models outclass it. For fast, general-purpose, multimodal work, few match it.