GPT-5.6 Sol wins on coding (97 vs 96) and price ($2 vs $5/1M input). For most workflows, GPT-5.6 Sol is the stronger default — best openai flagship — leads terminal coding and agentic browsing.
The safest GPT-5.6 Sol vs GPT-5.5 default, the cheaper option worth trying first, and the specialist pick — before you read the detail below.
GPT-5.6 Sol is the strongest answer here for GPT-5.6 Sol vs GPT-5.5 — pick it when quality of output matters more than the $4.00/1M/1M input you pay for it.
GPT-5.1-Codex-Max handles the same job for about 53% 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-5.6 Sol vs GPT-5.5 — worth it when latency is what the reader notices, not the last few points of reasoning depth.
GPT-5.6 Sol leads on coding with a score of 97 vs 96 for GPT-5.5.
GPT-5.6 Sol has the larger context window: 1.05M vs 1M for GPT-5.5.
GPT-5.6 Sol is cheaper at $2/1M input tokens vs $5/1M for GPT-5.5.
GPT-5.6 Sol is the safer default: it is built for frontier agentic coding, deep research, and hardest reasoning tasks, which covers most of what people bring to this comparison.
GPT-5.5 earns its place when your work is mostly agentic coding and computer-use workflows, even though it loses the overall count here.
Both models serve different primary workflows — GPT-5.6 Sol for frontier agentic coding and deep research, GPT-5.5 for agentic coding and computer-use workflows — so running each where it has a clear edge often beats forcing one to do both.
Switch the scoring lens to see whether the GPT-5.6 Sol vs GPT-5.5 answer changes when cost, speed, or long-document depth leads the decision.
OpenAI / Premium / Sep 19, 2026
Best OpenAI flagship — leads terminal coding and agentic browsing.
Ranks models by the broadest mix of coding, writing, research, and long-context usefulness.
Repo-level coding is the main job — Opus 5 leads SWE-bench Pro by ~15 points — or you're cost-sensitive (Terra is 60% cheaper at 1–4 points off).
Where the GPT-5.6 Sol vs GPT-5.5 recommendation shifts once you weigh price or latency differently.
Best OpenAI flagship — leads terminal coding and agentic browsing.
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-5.6 SolOpenAI | $4.00/1M | $20.00/1M | $80 | 1.1M tokens | Deliberate | 97 | 94 | 97 |
| 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-5.6 Sol vs GPT-5.5, what it is genuinely good at, and where we would steer you away from it.
Ranked first here for GPT-5.6 Sol vs GPT-5.5: 97/100 on coding, with the widest margin of anything in this line-up.
The flagship of OpenAI's GPT-5.6 family — its most capable reasoning and agentic-coding model, with an 'ultra' mode that spawns sub-agents for long autonomous workflows.
Repo-level coding is the main job — Opus 5 leads SWE-bench Pro by ~15 points — or you're cost-sensitive (Terra is 60% cheaper at 1–4 points off).
OpenAI's strongest model and the terminal-workflow leader. Sol beats everything on Terminal-Bench and agentic browsing, but Claude Opus 5 remains the better pick for repository-level software engineering.
Full pricing, benchmark table and release notes on the GPT-5.6 Sol page.
Here for latency: it answers fastest of anything listed for GPT-5.6 Sol vs GPT-5.5, at 96/100 on coding.
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-5.6 Sol wins on more of the categories we score — coding, research, reasoning — 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-5.6 Sol is aimed at frontier agentic coding and deep research, GPT-5.5 at agentic coding and computer-use workflows.
GPT-5.6 Sol is cheaper at $2/1M input and $10/1M output. GPT-5.5 costs $5/1M input and $30/1M output.
GPT-5.6 Sol has the larger context window at 1.05M tokens vs GPT-5.5's 1M. For large document analysis, GPT-5.6 Sol is the stronger pick.
GPT-5.6 Sol is better for coding with a score of 97 vs GPT-5.5's 96 (out of 100). GPT-6 Astra 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-5.6 Sol's deliberate rating (score: 2). Speed matters most for interactive and high-throughput work; for batch jobs the GPT-5.6 Sol latency penalty is usually invisible.
Trails Claude Opus 5 badly on repository-level engineering (SWE-bench Pro 64.6% vs 79.2%). Long-context surcharge ($10/$45 above 272K) and 2–3x ultra-mode costs stack up fast. Avoid it if repo-level coding is the main job — Opus 5 leads SWE-bench Pro by ~15 points — or you're cost-sensitive (Terra is 60% cheaper at 1–4 points off). That is the main case for looking at GPT-5.5 instead.
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. Against GPT-5.6 Sol specifically, the gap shows up most on coding (97 vs 96).
Take a moderate workload of 10M input and 2M output tokens a month. GPT-5.6 Sol runs $40.00 (at $2/1M in and $10/1M out); GPT-5.5 runs $110.00 (at $5/1M in and $30/1M out). That is a $70.00/month difference — GPT-5.6 Sol 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-5.6 Sol for frontier agentic coding and deep research, with GPT-5.5 handling agentic coding and computer-use workflows. Since GPT-5.6 Sol is both the stronger and the cheaper option here, a split mainly makes sense if GPT-5.5 covers a capability you specifically need.