GPT-5.5 wins on coding (96 vs 58) and writing quality and context window (1M vs 128K). GPT-4o wins on price ($2.5 vs $5/1M input). For most workflows, GPT-5.5 is the stronger default — best openai flagship for agentic coding, research, and computer-use work.
The safest GPT-5.5 vs GPT-4o default, the cheaper option worth trying first, and the specialist pick — before you read the detail below.
GPT-5.5 is the strongest answer here for GPT-5.5 vs GPT-4o — pick it when quality of output matters more than the $5.00/1M/1M input you pay for it.
GPT-4o handles the same job for about 64% less per token. Start here and only move up if the output is not good enough.
GPT-4o is the fastest of these for GPT-5.5 vs GPT-4o — worth it when latency is what the reader notices, not the last few points of reasoning depth.
GPT-5.5 leads on coding with a score of 96 vs 58 for GPT-4o.
GPT-5.5 has the larger context window: 1M vs 128K for GPT-4o.
GPT-4o is cheaper at $2.5/1M input tokens vs $5/1M for GPT-5.5.
Go with GPT-5.5 if you want one model to handle coding and research — it targets agentic coding, computer-use workflows, and complex research tasks.
Switch to GPT-4o when your work is mostly multimodal tasks and image-adjacent workflows; on that narrower brief it is the better tool.
GPT-4o is the more cost-efficient option at $2.5/1M input — GPT-5.5 costs 2x more per input token, so the gap is worth taking seriously wherever token volume rather than peak quality drives the bill.
Switch the scoring lens to see whether the GPT-5.5 vs GPT-4o answer changes when cost, speed, or long-document depth leads the decision.
OpenAI / Premium / Sep 3, 2026
Best OpenAI flagship for agentic coding, research, and computer-use work.
Ranks models by the broadest mix of coding, writing, research, and long-context usefulness.
You only care about the highest public coding benchmark score or need a cheaper high-volume model.
Where the GPT-5.5 vs GPT-4o recommendation shifts once you weigh price or latency differently.
Best OpenAI flagship for agentic coding, research, and computer-use work.
Best all-around pick for image-heavy and multimodal workflows.
List prices and published scores — the numbers this page's pick is built from.
| Model | Input | Output | Est. month | Context | Speed | Coding | Writing | Research |
|---|---|---|---|---|---|---|---|---|
| GPT-5.5OpenAI | $5.00/1M | $30.00/1M | $110 | 1M tokens | Balanced | 96 | 92 | 94 |
| GPT-4oOpenAI | $2.50/1M | $10.00/1M | $45 | 128k tokens | Fast | 58 | 76 | 65 |
Scores out of 100 — how we evaluate models. “Est. month” is 10M in / 2M out at list price: a ceiling, no discounts.
Why each one is on the shortlist for GPT-5.5 vs GPT-4o, what it is genuinely good at, and where we would steer you away from it.
The default answer for GPT-5.5 vs GPT-4o — 96/100 on the coding axis, and the model we would start with unless the price below rules it out.
OpenAI's latest agentic flagship for coding, research, computer-use workflows, and long multi-step knowledge work.
You only care about the highest public coding benchmark score or need a cheaper high-volume model.
The strongest OpenAI pick for agentic coding and knowledge work. Claude Opus 4.7 still wins on the public SWE-Bench Pro coding number, but GPT-5.5 is the better OpenAI default when ecosystem, Codex, or computer-use workflows matter.
Full pricing, benchmark table and release notes on the GPT-5.5 page.
The cost-conscious pick for GPT-5.5 vs GPT-4o, about 64% less per token than GPT-5.5 than the top choice while holding 58/100 on coding.
Versatile multimodal model that handles image-related workflows and mixed-media prompts well.
You need the latest reasoning or coding performance — GPT-5.4 replaces it for serious work.
Still a reliable multimodal pick, especially for teams already in the OpenAI ecosystem.
Full pricing, benchmark table and release notes on the GPT-4o page.
UseRightAI recommendations are based on practical decision factors people actually feel in day-to-day use.
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GPT-5.5 wins on more of the categories we score — coding, research, reasoning — so it is the better default of the two. GPT-4o is the better pick when your work is mostly multimodal tasks and image-adjacent workflows. Neither is universally "better": GPT-5.5 is aimed at agentic coding and computer-use workflows, GPT-4o at multimodal tasks and image-adjacent workflows.
GPT-4o is cheaper at $2.5/1M input and $10/1M output. GPT-5.5 costs $5/1M input and $30/1M output.
GPT-5.5 has the larger context window at 1M tokens vs GPT-4o's 128K. For large document analysis, GPT-5.5 is the stronger pick.
GPT-5.5 is better for coding with a score of 96 vs GPT-4o's 58 (out of 100). GPT-6 Astra is the overall coding leader in this directory at 100/100.
GPT-4o is faster with a fast speed rating (score: 4) vs GPT-5.5's balanced rating (score: 3). Speed matters most for interactive and high-throughput work; for batch jobs the GPT-5.5 latency penalty is usually invisible.
Claude Opus 4.7 leads GPT-5.5 on SWE-Bench Pro for pure coding ceiling. Premium API pricing makes it less attractive for high-volume low-risk work. Avoid it if you only care about the highest public coding benchmark score or need a cheaper high-volume model. That is the main case for looking at GPT-4o instead.
Outclassed by newer models on pure coding and reasoning. Gemini 3.1 Pro now handles multimodal at a lower price. Avoid it if you need the latest reasoning or coding performance — GPT-5.4 replaces it for serious work. Against GPT-5.5 specifically, the gap shows up most on coding (96 vs 58).
Take a moderate workload of 10M input and 2M output tokens a month. GPT-5.5 runs $110.00 (at $5/1M in and $30/1M out); GPT-4o runs $45.00 (at $2.5/1M in and $10/1M out). That is a $65.00/month difference — GPT-4o is the cheaper of the two at this volume, and the gap scales linearly as you send more. Output tokens dominate the bill on both, so prompt length matters far less than response length.
Yes, and for most teams that beats picking one. A common split is GPT-5.5 for agentic coding and computer-use workflows, with GPT-4o handling multimodal tasks and image-adjacent workflows. Routing high-volume, low-stakes calls to GPT-4o at $2.5/1M and reserving GPT-5.5 for the hard cases is usually the cheapest arrangement that does not cost you quality.