GLM 5.1 vs GPT-5.4

Choose GLM 5.1 if you want…

• ✓Lower price ($2.15 / 1M blended)

Choose GPT-5.4 if you want…

• ✓Higher intelligence (Artificial Analysis index 57)
• ✓Faster output (~163.4 tokens/sec)
• ✓Larger context window (1.1M)

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-5.4

GPT-5.4 was built for the actual work that happens inside offices — financial modeling, legal analysis, complex codebases, and multi-step document workflows — rather than for chasing narrow benchmarks. That strategic shift shows in the numbers: it matched or outperformed human professionals in 83% of head-to-head comparisons, and developers have called its coding output "flawless," with some declaring it the definitive choice for complex software engineering work. Native computer-use capabilities let it operate browsers and desktop apps directly, and it scored above the human baseline on UI interaction tasks. The 1.05 million token context window handles large codebases and lengthy legal documents in a single pass, though you need to configure it explicitly — the default is 272K. Where GPT-5.4 falls short is nuance: it tends to interpret requests too literally, missing the intent behind ambiguous prompts in ways that Claude handles more naturally. Writing personality is another common frustration, with verbose follow-up suggestions that can feel mechanical. For structured professional tasks where thoroughness and tool integration matter more than prose feel, it is the strongest model in the GPT-5 line prior to the release of GPT-5.5.