GPT-6 Astra wins on coding (99 vs 96). GPT-5.5 wins on price ($5 vs $10/1M input). For most workflows, GPT-6 Astra is the stronger default — openai's frontier answer to fable 5.1 — computer-use and agentic-coding leader at $10/$50.
The safest GPT-6 Astra vs GPT-5.5 default, the cheaper option worth trying first, and the specialist pick — before you read the detail below.
GPT-6 Astra is the strongest answer here for GPT-6 Astra vs GPT-5.5 — pick it when quality of output matters more than the $10.00/1M/1M input you pay for it.
GPT-5.5 handles the same job for about 42% less per token. Start here and only move up if the output is not good enough.
GPT-5.5 is the fastest of these for GPT-6 Astra vs GPT-5.5 — worth it when latency is what the reader notices, not the last few points of reasoning depth.
GPT-6 Astra leads on coding with a score of 99 vs 96 for GPT-5.5.
GPT-6 Astra has the larger context window: 1.05M vs 1M for GPT-5.5.
GPT-5.5 is cheaper at $5/1M input tokens vs $10/1M for GPT-6 Astra.
Go with GPT-6 Astra if you want one model to handle coding and research — it targets computer and browser use, long-horizon agentic coding, and frontier math and science work.
Choose GPT-5.5 when your work is mostly agentic coding and computer-use workflows — that is the workload it was tuned for.
GPT-5.5 is the more cost-efficient option at $5/1M input — GPT-6 Astra 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-6 Astra vs GPT-5.5 answer changes when cost, speed, or long-document depth leads the decision.
OpenAI / Premium / Sep 4, 2026
OpenAI's frontier answer to Fable 5.1 — computer-use and agentic-coding leader at $10/$50.
Ranks models by the broadest mix of coding, writing, research, and long-context usefulness.
You are cost-sensitive or latency-bound — GPT-5.6 Sol is a fifth of the price — or you need it today in an Enterprise workspace, where it is off by default, or for offensive-security work, which it refuses outside OpenAI Daybreak.
Where the GPT-6 Astra vs GPT-5.5 recommendation shifts once you weigh price or latency differently.
OpenAI's frontier answer to Fable 5.1 — computer-use and agentic-coding leader at $10/$50.
Best OpenAI flagship for agentic coding, research, and computer-use work.
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-6 AstraOpenAI | $10.00/1M | $50.00/1M | $200 | 1.1M tokens | Deliberate | 100 | 97 | 100 |
| GPT-5.5OpenAI | $5.00/1M | $30.00/1M | $110 | 1M tokens | Balanced | 96 | 92 | 94 |
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-6 Astra vs GPT-5.5, what it is genuinely good at, and where we would steer you away from it.
The default answer for GPT-6 Astra vs GPT-5.5 — 100/100 on the coding axis, and the model we would start with unless the price below rules it out.
OpenAI's September 3, 2026 frontier release — the first GPT-6 model and OpenAI's answer to Claude Fable 5.1 two days earlier. State of the art on computer use (OSWorld 2.0 72.6% in ~47% less time than GPT-5.6 Sol), agentic coding (Terminal-Bench 4.0 57.9%), and frontier math (FrontierMath Tier 4 97.6%). $10/$50 per 1M tokens, 1.05M context, 128K output, knowledge cutoff April 30, 2026.
You are cost-sensitive or latency-bound — GPT-5.6 Sol is a fifth of the price — or you need it today in an Enterprise workspace, where it is off by default, or for offensive-security work, which it refuses outside OpenAI Daybreak.
The new computer-use and agentic-coding ceiling, and OpenAI's first model priced like a Mythos-class Claude. Astra beats Claude Fable 5.1 on Terminal-Bench 4.0 (57.9% vs 55.8%), Terminal-Bench Science (64.6% vs 52.6%) and FrontierMath Tier 4 (97.6% vs 87.8%), and it is the only model with a credible OSWorld 2.0 result above 70%. It loses to Fable 5.1 on Humanity's Last Exam and on Artificial Analysis's index, costs five times GPT-5.6 Sol, and ships without a SWE-bench number. If your work is computer use, browser agents or math, it is the pick; for everyday coding at scale, Sol at $2/$10 remains the value default.
Full pricing, benchmark table and release notes on the GPT-6 Astra page.
Where most budgets should land for GPT-6 Astra vs GPT-5.5 — about 42% less per token than GPT-6 Astra, and still 96/100 on the coding axis.
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.
UseRightAI recommendations are based on practical decision factors people actually feel in day-to-day use.
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GPT-6 Astra wins on more of the categories we score — coding, research, long context — so it is the better default of the two. GPT-5.5 is the better pick when your work is mostly agentic coding and computer-use workflows. Neither is universally "better": GPT-6 Astra is aimed at computer and browser use and long-horizon agentic coding, GPT-5.5 at agentic coding and computer-use workflows.
GPT-5.5 is cheaper at $5/1M input and $30/1M output. GPT-6 Astra costs $10/1M input and $50/1M output.
GPT-6 Astra has the larger context window at 1.05M tokens vs GPT-5.5's 1M. For large document analysis, GPT-6 Astra is the stronger pick.
GPT-6 Astra is better for coding with a score of 99 vs GPT-5.5's 96 (out of 100). Claude Opus 5.5 is the overall coding leader in this directory at 100/100.
GPT-5.5 is faster with a balanced speed rating (score: 3) vs GPT-6 Astra's deliberate rating (score: 2). Speed matters most for interactive and high-throughput work; for batch jobs the GPT-6 Astra latency penalty is usually invisible.
$10/$50 per 1M — two and a half times GPT-5.6 Sol's $4/$20 promotional rate, five times GPT-6.1 Sol's $2/$10, and the same premium as Claude Fable 5.1; Fast mode doubles it again. Trails Claude Fable 5.1 on Humanity's Last Exam with tools (57.2% vs 65.0%) and on the Artificial Analysis Intelligence Index (61.2 vs 65.7). OpenAI published no SWE-bench Verified or SWE-bench Pro figure at launch, so it does not appear on our SWE-bench leaderboard. Avoid it if you are cost-sensitive or latency-bound — GPT-6.1 Sol is a fifth of the price — or you need it today in an Enterprise workspace, where it is off by default, or for offensive-security work, which it refuses outside OpenAI Daybreak. That is the main case for looking at GPT-5.5 instead.
Claude models led it on SWE-Bench Pro at the time, and Claude Opus 5.5 leads coding now. 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. Against GPT-6 Astra specifically, the gap shows up most on coding (99 vs 96).
Take a moderate workload of 10M input and 2M output tokens a month. GPT-6 Astra runs $200.00 (at $10/1M in and $50/1M out); GPT-5.5 runs $110.00 (at $5/1M in and $30/1M out). That is a $90.00/month difference — GPT-5.5 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-6 Astra for computer and browser use and long-horizon agentic coding, with GPT-5.5 handling agentic coding and computer-use workflows. Routing high-volume, low-stakes calls to GPT-5.5 at $5/1M and reserving GPT-6 Astra for the hard cases is usually the cheapest arrangement that does not cost you quality.