GPT-6 Astra is OpenAI's best model for research — it scores 100/100 vs 97/100 for GPT-5.6 Sol, at $10/1M input tokens. It is also the top-ranked research model across every provider we track.
The safest openai model for research 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 openai model for research — pick it when quality of output matters more than the $10.00/1M/1M input you pay for it.
GPT-5.6 Sol handles the same job for about 80% less per token. Start here and only move up if the output is not good enough.
GPT-5.5 carries 1M tokens of context, so it is the pick for openai model for research when whole documents, transcripts, or repositories go in at once.
GPT-6 Astra leads OpenAI's lineup for research at 100/100 ($10/1M input, 1.05M context).
GPT-4o Mini is the value pick at $0.15/1M input with a research score of 62/100.
GPT-6 Astra is also the #1 research model in the entire directory — no provider switch needed.
Choose GPT-6 Astra when research quality is the priority and you're staying on OpenAI.
Choose GPT-4o Mini when token volume matters more than peak quality.
Teams comparing providers can stop here — GPT-6 Astra is the current cross-provider leader.
Switch the scoring lens to see whether the openai model for research 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 openai model for research 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 — leads terminal coding and agentic browsing.
Best OpenAI flagship for agentic coding, research, and computer-use work.
Best OpenAI value — near-flagship capability at 60% off.
Best for agentic automation and desktop control workflows.
Capable but outclassed — GPT-5.4 is now cheaper and better.
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-5.6 SolOpenAI | $2.00/1M | $10.00/1M | $40 | 1.1M tokens | Deliberate | 97 | 94 | 97 |
| GPT-5.5OpenAI | $5.00/1M | $30.00/1M | $110 | 1M tokens | Balanced | 96 | 92 | 94 |
| GPT-5.6 TerraOpenAI | $2.00/1M | $12.00/1M | $44 | 1.1M tokens | Balanced | 94 | 92 | 93 |
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 openai model for research, what it is genuinely good at, and where we would steer you away from it.
The default answer for openai model for research — 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.
The cost-conscious pick for openai model for research, about 80% less per token than GPT-6 Astra than the top choice while holding 97/100 on coding.
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.
The long-document choice for openai model for research — the largest context window in this shortlist, so whole files go in at once.
Best OpenAI flagship for agentic coding, research, and computer-use work. Full GPT-5.5 review →
Also worth a look for openai model for research, at 94/100 on the coding axis.
Best OpenAI value — near-flagship capability at 60% off. Full GPT-5.6 Terra review →
UseRightAI recommendations are based on practical decision factors people actually feel in day-to-day use.
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GPT-6 Astra — it scores 100/100 on research in this directory, ahead of GPT-5.6 Sol at 97/100. OpenAI's frontier answer to Fable 5.1 — computer-use and agentic-coding leader at $10/$50.
Yes — GPT-6 Astra currently tops the entire directory for research at 100/100.
GPT-4o Mini at $0.15/1M input tokens (research score: 62/100). Use it for volume work and reserve GPT-6 Astra for the tasks where quality matters most.
$10/1M input tokens and $50/1M output tokens via the API, or through ChatGPT Plus at $20/mo for chat use. Context window: 1.05M tokens. On a moderate month — 10M input and 2M output tokens — that works out to about $200.00, against $2.70 for GPT-4o Mini.
$10/$50 per 1M — five times GPT-5.6 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). Concretely, avoid it if 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.
computer-use agents that fill forms, update CRMs, run QA in a browser — 72.6% on OSWorld 2.0 at ~40 minutes per task vs Sol's 75, agentic coding in Codex with cross-context notes — 57.9% Terminal-Bench 4.0, ahead of Claude Fable 5.1 (55.8%), and frontier math and science — 97.6% FrontierMath Tier 4 and 64.6% Terminal-Bench Science, both well clear of every rival OpenAI tested. Its 1.05M-token context window is the practical limit on how much you can hand it in one go.
GPT-6 Astra scores 100/100 on research against 62/100 for GPT-4o Mini, at 67x the input price. That premium is worth it on work where a wrong answer costs real time or money, and hard to justify on high-volume, low-stakes calls. Most teams run both and route by task rather than picking one.