Your tasks are well-scoped and latency-sensitive — Sonnet 5.5 is half the price and Anthropic says it is the fastest Sonnet yet.
Strengths
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%
Weaknesses
$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
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
Ranked alternatives
Strong backups depending on your budget, workload, and preferred tradeoffs.
AnthropicPremium
Claude Fable 5.1
Anthropic's September 1, 2026 frontier release for coding, agents, and scientific work. On SWE-bench Pro the cheaper Claude Opus 5.5 now scores higher (89.9% vs 81.2% in Anthropic's table). Base pricing is unchanged at $10/$50, but cache reads dropped 75% to $0.25/1M — roughly 25% cheaper on typical workloads and up to 45% cheaper on agentic ones. 1M context, 128K output, adaptive thinking always on.
Verdict
Anthropic's highest-ceiling model — strongest on open-ended research; Opus 5.5 now leads coding.
Quality score
98%
Pricing
$10.00/1M in
$50.00/1M out
Speed
Deliberate
2/5 speed
Context
1M tokens
Released September 1, 2026 alongside Claude Mythos 5.1, the first update to the Mythos-class line since Fable 5 on June 9. API ID claude-fable-5-1; generally available on the Claude API, Amazon Bedrock, Google Cloud, and Microsoft Foundry. Published launch numbers (Fable 5.1 / Fable 5 / Opus 5 / GPT-5.6 Sol): Terminal-Bench-Science 0.1 52.6 / 24.7 / 29.0 / 22.4; Terminal-Bench 4.0 55.8 / 42.0 / 52.3 / 37.3; CursorBench 3.2.0 73.4 / 70.5 / 70.0 / 67.2; AutomationBench 31.4 / 17.1 / 26.9 / 19.6; OSWorld 2.0 strict 41.7 / 36.1 / 39.6; Humanity's Last Exam (no tools) 60.9 / 57.8 / 56.6; GDPval-AA v2 1853 / 1723 / 1824 / 1711. GDPval-AA v2 is rescaled from the v1 numbers quoted on the Fable 5 page and is not directly comparable to them.
Anthropic's June 9, 2026 Mythos-class flagship. At launch it was the most capable coding model anyone could use — 80.3% SWE-Bench Pro, an 11-point jump over Opus 4.8 — and it has since been overtaken by Claude Fable 5.1 and Claude Opus 5.5. 1M context, 128K output, native parallel subagents.
Verdict
Superseded by Fable 5.1 — still 80.3% SWE-Bench Pro, but 5.1 is better and cheaper to run.
Quality score
97%
Pricing
$10.00/1M in
$50.00/1M out
Speed
Deliberate
2/5 speed
Context
1M tokens
Launched June 9, 2026 as the public, Mythos-class release. Available on the Claude API, Microsoft Foundry, and Google Vertex AI. Free for all users until June 22, 2026. Same underlying model as Claude Mythos 5, with safeguards that block specific high-risk cyber responses. Superseded by Claude Fable 5.1 on September 1, 2026 — same $10/$50 base pricing, cache reads cut from $1.00 to $0.25 per 1M tokens.
SWE-Bench Pro 80.3%Mythos-classParallel subagentsAgenticLong contextPremiumSuperseded
Best for
The hardest coding tasks, autonomous multi-step agents, and frontier-grade reasoning
Anthropic's September 22, 2026 Opus — a step up from Opus 5 on agentic coding, long-running agent work and vision, at a lower $4/$20 list price and with fewer tokens spent per finished task.
Verdict
Anthropic's new coding default — top SWE-bench Pro score at a lower price than Opus 5.
Quality score
98%
Pricing
$4.00/1M in
$20.00/1M out
Speed
Deliberate
2/5 speed
Context
1M tokens
Released September 22, 2026. Gateway id anthropic/claude-opus-5.5. $4/$20 per 1M (cache read $0.20, cache write $5); Fast mode $8/$40. 1,000,000 context, 128,000 max output, knowledge cutoff June 2026, effort levels low to max. Launch figures as reported by Anthropic: SWE-bench Pro 89.9 (Fable 5.1 81.2, Opus 5 79.2); SWE-bench Multilingual 93.9; Terminal-Bench 4.0 66.4 (xhigh); OSWorld 2.1 81.8; Humanity's Last Exam 67.7; Toolathlon Verified 77.8 (Opus 5 80.6). Verified October 10, 2026.
CodingAgenticFlagship1M contextPremiumNew
Best for
Agentic coding, long-running agents and knowledge work where Opus 5 was the bar
Anthropic's flagship-tier Opus that comes close to Claude Fable 5's frontier intelligence at half the price — the new default for complex agentic coding and enterprise agents.
Verdict
Strong premium coder, now replaced by the cheaper Opus 5.5.
Quality score
97%
Pricing
$5.00/1M in
$25.00/1M out
Speed
Deliberate
2/5 speed
Context
1M tokens
Released July 24, 2026 at Opus 4.8's exact pricing. 1M context at standard rates, 128K max output. Anthropic's alignment audit calls it their most aligned model to date. Superseded on September 22, 2026 by Claude Opus 5.5, which is cheaper at $4/$20.
CodingAgenticFlagship1M contextPremium
Best for
Complex agentic coding and enterprise agent workflows
Ranked first here for long context AI: 100/100 on long-context, with the widest margin of anything in this line-up.
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 — 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
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-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.
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, GPT-6.1 Sol at $2/$10 is the value default — OpenAI says it comes close to Astra at a fifth of the price.
Full pricing, benchmark table and release notes on the GPT-6 Astra page.
The long-document choice for long context AI — the largest context window in this shortlist, so whole files go in at once.
Anthropic's September 1, 2026 frontier release for coding, agents, and scientific work. On SWE-bench Pro the cheaper Claude Opus 5.5 now scores higher (89.9% vs 81.2% in Anthropic's table). Base pricing is unchanged at $10/$50, but cache reads dropped 75% to $0.25/1M — roughly 25% cheaper on typical workloads and up to 45% cheaper on agentic ones. 1M context, 128K output, adaptive thinking always on.
Input
$10.00/1M
Output
$50.00/1M
Context
1M tokens
Speed
Deliberate
What people actually use it for
Agentic scientific research — 52.6% on Terminal-Bench-Science 0.1, more than double Fable 5's 24.7%
Long-running autonomous coding agents that plan, run, and debug across a whole repository
Cache-heavy agent loops where the 75% cache-read cut ($1.00 → $0.25 per 1M) is the real saving
Where it wins
52.6% Terminal-Bench-Science 0.1 — 2.1x Fable 5 (24.7%), well clear of Opus 5 (29.0%) and GPT-5.6 Sol (22.4%)
55.8% Terminal-Bench 4.0 agentic coding, ahead of Opus 5 (52.3%) and Fable 5 (42.0%)
Cache reads cut 75% to $0.25/1M — ~25% cheaper for typical use, ~45% for heavily agentic work
Independent Vals AI evaluation ranks it #1 of 51 on the Vals Index, #1 on LiveCodeBench (90.5%) and MMLU Pro (92.4%)
1M-token context and 128K max output at standard rates, with adaptive thinking always enabled
Where it falls down
Base rates are still $10/$50 per 1M — double Claude Opus 5 for anything that is not cache-heavy
Anthropic published no SWE-bench Verified or SWE-bench Pro figure for 5.1 at launch
On Claude Pro it only runs on pay-as-you-go credits; Max includes it up to 50% of weekly limits
Deliberate, high-latency profile — the wrong choice for interactive, latency-bound apps
Skip it if
You need low latency, or your workload is uncached and cost-sensitive — Claude Opus 5 is half the base price and within a few points on agentic coding.
Our verdict
Anthropic's highest-ceiling model, and the rare upgrade that costs less than the model it replaces — though for coding alone, Claude Opus 5.5 now scores higher at $4/$20. Base $10/$50 pricing did not move, but a 75% cut to cache reads makes typical workloads ~25% cheaper than Fable 5 and heavily agentic ones ~45% cheaper — while more than doubling Fable 5 on agentic science and beating Opus 5 on agentic coding. If you were already on Fable 5, switching is a straight win. If you were on Opus 5 for the price, it still costs 2x on uncached tokens.
The cost-conscious pick for long context AI, about 60% less per token than GPT-6 Astra than the top choice while holding 98/100 on long-context.
Input
$4.00/1M
Output
$20.00/1M
Context
1M tokens
Speed
Deliberate
Anthropic's new coding default — top SWE-bench Pro score at a lower price than Opus 5. Full Claude Opus 5.5 review →
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FAQ
What is the best AI for long context AI?
For long context AI, GPT-6 Astra (OpenAI) is our pick. OpenAI's frontier answer to Fable 5.1 — computer-use and agentic-coding leader at $10/$50. It costs $10/1M input and $50/1M output tokens, with a 1.05M-token context window — enough headroom for all but the largest long context AI jobs. Claude Fable 5.1 is the closest alternative if it doesn't fit your setup.
Why GPT-6 Astra for long context AI?
Because the work it is built for overlaps closely with long context AI: 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 and agentic coding in Codex with cross-context notes — 57.9% Terminal-Bench 4.0, ahead of Claude Fable 5.1 (55.8%). 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, GPT-6.1 Sol at $2/$10 is the value default — OpenAI says it comes close to Astra at a fifth of the price.
What does it cost to use GPT-6 Astra for long context AI?
On a moderate month — 10M input and 2M output tokens — GPT-6 Astra runs about $200.00 at list price, with no batch or caching discounts applied, so treat that as a ceiling. Claude Opus 5.5 is the cheaper route at roughly $80.00 for the same volume, if long context AI is high-volume enough for price to lead the decision.
When is GPT-6 Astra the wrong choice for long context AI?
$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). 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. None of that rules it out for long context AI on its own — but if one of those limits maps onto how you actually work, take the alternative on this page seriously rather than defaulting to the top pick.
Is there a cheaper AI that still handles long context AI?
Claude Opus 5.5 at $4/1M input is the budget option here. Anthropic's new coding default — top SWE-bench Pro score at a lower price than Opus 5. Expect a quality step down on the hardest cases — the usual pattern is to route routine long context AI volume to Claude Opus 5.5 and keep GPT-6 Astra for the work where a wrong answer is expensive.