GPT-5.1 vs GPT-5.4

Choose GPT-5.1 if you want…

• ✓Lower price ($3.44 / 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)

GPT-5.1

GPT-5.1 earns its place through adaptive reasoning — a system that genuinely calibrates effort to the task, running roughly twice as fast on straightforward queries and digging deeper on complex ones. That mechanical intelligence shows up in the benchmarks: 94% on AIME 2025, 88.1% on GPQA Diamond, and a 76.3% solve rate on SWE-Bench Verified, making it one of the more capable off-the-shelf options for serious coding and research-level math. Users consistently praise how much cleaner the code output is — fewer logic errors, better edge-case handling — and the improved tool-calling reliability makes it a practical choice for production agentic pipelines. The catch is that the Auto-routing variant has frustrated users who found it silently redirecting requests through stricter safety filters without explanation, a criticism that turned OpenAI's own Reddit launch AMA into a notable PR setback. For teams willing to pick the right variant (Instant, Thinking, or Auto) and work within a September 2024 knowledge cutoff, GPT-5.1 offers strong price-to-capability value at $1.25 per million input tokens — cheaper than its GPT-5.2 successor while covering most production needs.

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.