Research work splits into two jobs that need different tools: synthesising a large body of fixed material, and finding what is current. For synthesis, the top tier is GPT-6 Astra and Claude Fable 5.1, both $10/$50 per million tokens with million-token context windows; Fable 5.1 leads Astra on Humanity's Last Exam with tools (65.0% vs 57.2% in OpenAI's own table), while Astra leads on frontier maths. Most research does not need that ceiling. Claude Opus 5.5 at $4/$20 and Gemini 3.1 Pro at $2/$12 both hold a million tokens — several papers, a long transcript archive or a whole knowledge base — for a fraction of the price. When the question is about something recent, use a search-first tool such as Perplexity, which cites live sources instead of relying on a training cutoff.
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Best pick right now
OpenAIPremium
GPT-6 Astra
OpenAI's frontier answer to Fable 5.1 — computer-use and agentic-coding leader at $10/$50.
GPT-6 Astra and Claude Fable 5.1 are the strongest models for hard, open-ended research questions, each with a 1M-token window for cross-document work.
Claude Opus 5.5 and Gemini 3.1 Pro deliver most of that capability at a fifth or less of the price, which matters when research means reading a great deal of text.
Perplexity is the right tool when the answer depends on current information, because it searches and cites the web instead of answering from memory.
Decision notes
Choose Claude Fable 5.1 or GPT-6 Astra for the hardest questions — literature synthesis, scientific reasoning, or analysis where depth decides the outcome and budget does not.
Choose Claude Opus 5.5 for most serious document work: large static sets such as papers, contracts, specs or transcripts, at $4/$20.
Choose Gemini 3.1 Pro when your research lives in Google Docs, Sheets and Drive, or when you want a 1M window at $2/$12.
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#1Claude Opus 5.592 pts
#2GPT-6 Astra91 pts
#3Claude Fable 5.191 pts
#4Claude Mythos 5.190 pts
#5Claude Mythos 589 pts
Quality first
Claude Opus 5.5
Anthropic / Premium / Oct 10, 2026
92
Anthropic's new coding default — top SWE-bench Pro score at a lower price than Opus 5.
Ranks models by the broadest mix of coding, writing, research, and long-context usefulness.
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 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
The unrestricted twin of Claude Fable 5.1 — the same model with safeguards lifted in high-risk areas, released September 1, 2026 to vetted cybersecurity and life-sciences organisations under Anthropic's trusted-access programme. Scores 60.9% on Terminal-Bench 4.0, the highest agentic-coding result Anthropic has published.
Verdict
Fable 5.1 with the safeguards lifted — partner-only, 60.9% Terminal-Bench 4.0.
Quality score
97%
Pricing
$10.00/1M in
$50.00/1M out
Speed
Deliberate
2/5 speed
Context
1M tokens
Released September 1, 2026 alongside Claude Fable 5.1, continuing the Mythos-class line that began with Project Glasswing's April 2026 private preview. Access is limited to vetted US cybersecurity and life-sciences professionals. Same underlying model, pricing, context window, and cache-read discount as Fable 5.1; the only published difference is the safeguard level and the resulting Terminal-Bench 4.0 score (60.9% vs 55.8%).
Anthropic's most powerful frontier model — the same underlying model as Fable 5 with safeguards lifted in some areas, restricted to vetted enterprise and research partners. The capability ceiling of mid-2026.
Verdict
Superseded by Mythos 5.1 — same model as Fable 5, safeguards lifted, partner-only.
Quality score
97%
Pricing
$10.00/1M in
$50.00/1M out
Speed
Deliberate
2/5 speed
Context
1M tokens
Launched June 9, 2026 alongside Fable 5, following the April Project Glasswing private preview on Google Cloud. Restricted to vetted enterprise and research partners due to advanced cybersecurity capabilities. Same underlying model and benchmarks as Claude Fable 5. Superseded by Claude Mythos 5.1 on September 1, 2026.
FrontierRestricted accessCybersecuritySWE-Bench Pro 80.3%Mythos-classPremiumSuperseded
Best for
Frontier cybersecurity research, autonomous vulnerability discovery, and the absolute capability ceiling
Ranked first here for research: 100/100 on research, 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 research — 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 value option for research: about 60% less per token than GPT-6 Astra, at 99/100 on research. Worth starting here and moving up only if the output disappoints.
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 research?
For research, 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 research jobs. Claude Fable 5.1 is the closest alternative if it doesn't fit your setup.
Why GPT-6 Astra for research?
Because the work it is built for overlaps closely with research: 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 research?
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 research is high-volume enough for price to lead the decision.
When is GPT-6 Astra the wrong choice for research?
$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 research 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 research?
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 research volume to Claude Opus 5.5 and keep GPT-6 Astra for the work where a wrong answer is expensive.