Gemini 3.1 Pro Preview vs GPT-4o

Choose Gemini 3.1 Pro Preview if you want…

• ✓Higher intelligence (Artificial Analysis index 57)
• ✓Larger context window (1.0M)

Choose GPT-4o if you want…

• ✓Faster output (~198.3 tokens/sec)
• ✓Lower price ($4.38 / 1M blended)

Gemini 3.1 Pro Preview

At the top of the Artificial Analysis Intelligence Index — ahead of every other model evaluated — Gemini 3.1 Pro Preview earns its ranking not just on raw ability but on the economics of getting there. It ran a full benchmark suite at less than half the cost of comparable frontier models, which makes it the clearest answer to the question of whether top-tier intelligence requires top-tier spend. A 38-percentage-point drop in hallucination rate over its predecessor and a 94.3% GPQA Diamond score in graduate-level scientific reasoning make it a serious tool for complex research, deep software engineering, and agentic workflows that need to get things right. Its 1-million-token context window handles entire codebases or lengthy document sets without batching. The honest caveat: time-to-first-token averages nearly 25 seconds, well above the median for comparable models, and some developers report extended waits or reliability issues under high API load. If your work is iterative and deep rather than real-time and conversational, the trade-off is usually worth it.

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.