GPT-6 Astra is OpenAI's best model for writing — it scores 97/100 vs 94/100 for GPT-5.6 Sol, at $10/1M input tokens. Across all providers, Claude Fable 5.1 still leads writing at 98/100 — worth considering if you're not committed to OpenAI.
Last verified Sep 4, 2026/Model data modified Sep 4, 2026
Rankings refresh dailyScored on 6 criteriaNo paid rankings
OpenAIPremium
Input cost
$10.00/1M
Context
1.1M tokens
Speed
Deliberate
Clear recommendation block
The safest openai model for writing 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 writing — pick it when quality of output matters more than the $10.00/1M/1M input you pay for it.
OpenAIPremium
Best for
Computer and browser use, long-horizon agentic coding, and frontier math and science work
GPT-5.6 Luna is the fastest of these for openai model for writing — worth it when latency is what the reader notices, not the last few points of reasoning depth.
OpenAIBudget
Best for
Cheap high-throughput summarization, drafting, and routine agent steps
Price
$0.20/1M
Context
1.1M tokens
Why this page recommends it
GPT-6 Astra leads OpenAI's lineup for writing at 97/100 ($10/1M input, 1.05M context).
GPT-4o Mini is the value pick at $0.15/1M input with a writing score of 76/100.
Claude Fable 5.1 (Anthropic) is the overall writing leader at 98/100 if provider choice is open.
Decision notes
Choose GPT-6 Astra when writing quality is the priority and you're staying on OpenAI.
Choose GPT-4o Mini when token volume matters more than peak quality.
Teams open to other providers should also evaluate Claude Fable 5.1 before committing.
Interactive decision lab
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Switch the scoring lens to see whether the openai model for writing answer changes when cost, speed, or long-document depth leads the decision.
#1GPT-6 Astra91 pts
#2GPT-5.6 Sol89 pts
#3GPT-5.6 Terra89 pts
#4GPT-5.587 pts
#5GPT-5.6 Luna82 pts
Quality first
GPT-6 Astra
OpenAI / Premium / Sep 4, 2026
91
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.
Recommended comparisons
Where the openai model for writing recommendation shifts once you weigh price or latency differently.
Our pick for openai model for writing. It scores 100/100 on the coding axis we weight this page by, and nothing else in this shortlist matches it on output quality.
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.
Input
$10.00/1M
Output
$50.00/1M
Context
1.1M tokens
Speed
Deliberate
What people actually use it for
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%)
Frontier math and science — 97.6% FrontierMath Tier 4 and 64.6% Terminal-Bench Science, both well clear of every rival OpenAI tested
Where it wins
OSWorld 2.0 72.6% vs 65.7% for GPT-5.6 Sol, in roughly 47% less time per task — the new computer-use ceiling
Terminal-Bench 4.0 57.9% — ahead of Claude Fable 5.1 (55.8%), Opus 5 (52.3%) and GPT-5.6 Sol (37.3%)
FrontierMath Tier 4 (v2) 97.6% vs Fable 5.1's 87.8%; Terminal-Bench Science 64.6% vs 52.6%; GPQA Diamond 96.0%
1.05M context with 96.3% on OpenAI MRCR 8-needle at 512K–1M (Sol: 73.8%) and 128K max output
OpenAI's lowest misaligned-outcome rates to date: 2.4% on its computer-use safety benchmark vs 22.0% for Sol, 0% scope-creep on impossible cyber tasks vs 48%
Where it falls down
$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)
OpenAI published no SWE-bench Verified or SWE-bench Pro figure at launch, so it does not appear on our SWE-bench leaderboard
Rolling out over days, not instantly: Enterprise access is off by default, advanced cyber tasks are refused outside OpenAI Daybreak, and the safety layer can pause or stop legitimate agent runs
OpenAI's own system card finds its written reasoning harder to monitor than Sol's
Skip 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.
Our verdict
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 writing, 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.
Input
$2.00/1M
Output
$10.00/1M
Context
1.1M tokens
Speed
Deliberate
What people actually use it for
Tool-heavy terminal coding — 88.8% on Terminal-Bench 2.1 (91.9% in ultra mode, a state of the art)
Agentic web research at 90.4% BrowseComp with top-tier GPQA Diamond science reasoning (94.6%)
Long autonomous workflows using ultra mode's sub-agent orchestration
Where it wins
Terminal-Bench 2.1 leader at 88.8% (91.9% ultra) — the top OpenAI agentic-coding result
94.6% GPQA Diamond and 90.4% BrowseComp — frontier science reasoning and agentic browsing
Artificial Analysis Coding Agent Index leader at 80 points, near Fable 5 intelligence at roughly one-third the cost
Where it falls down
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
Skip 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).
Our verdict
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.
UseRightAI recommendations are based on practical decision factors people actually feel in day-to-day use.
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FAQ
Which OpenAI model is best for writing?
GPT-6 Astra — it scores 97/100 on writing in this directory, ahead of GPT-5.6 Sol at 94/100. OpenAI's frontier answer to Fable 5.1 — computer-use and agentic-coding leader at $10/$50.
Is GPT-6 Astra the best writing model overall?
Not overall. Claude Fable 5.1 (Anthropic) leads the directory for writing at 98/100 vs GPT-6 Astra's 97/100. GPT-6 Astra is the best pick if you're staying within OpenAI's ecosystem.
What is the cheapest OpenAI model that is still good at writing?
GPT-4o Mini at $0.15/1M input tokens (writing score: 76/100). Use it for volume work and reserve GPT-6 Astra for the tasks where quality matters most.
How much does GPT-6 Astra cost?
$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.
When is GPT-6 Astra the wrong choice for writing?
$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. If none of that is negotiable, Claude Fable 5.1 (Anthropic) is the cross-provider leader at 98/100.
What does GPT-6 Astra actually get used for?
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.
Is it worth paying up for GPT-6 Astra over GPT-4o Mini?
GPT-6 Astra scores 97/100 on writing against 76/100 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.