Claude Opus 4.7
Released
Claude Opus 4.7 is an AI model released by Anthropic on Thursday, Apr 16 2026, 58 days after Claude Sonnet 4.6. It has a 1M token context window. Benchmark results (shown below) cover BullshitBench v2, ProgramBench, SWE-Bench Pro, SWE-Bench Verified, SWE-Bench Multilingual, Next.js Evals, and 17 more.
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API pricing
- InputWhat you pay for everything you send the model — your question, plus any documents or earlier conversation you include with it.
- $5.00
- Cached inputA reduced rate for text you send over and over. If every request starts with the same instructions or the same document, the provider keeps a copy ready and charges less to read it again.
- $0.50
- 5 min cache writeA one-off charge for storing text so later requests can reuse it at the cheaper cached rate. This option keeps it for five minutes.
- $6.25
- 1 hr cache writeA one-off charge for storing text so later requests can reuse it at the cheaper cached rate. This option keeps it for an hour, so it costs more than the five-minute one.
- $10.00
- OutputWhat you pay for the text the model writes back. It is normally the dearer half: producing an answer costs more than reading one.
- $25.00
Available from
| Amazon Bedrock | global | $5.00 | $25.00 | 1M |
|---|---|---|---|---|
| Azure | global | $5.00 | $25.00 | 1M |
| global | $5.00 | $25.00 | 1M | |
| Amazon Bedrock | eu-west-1 | $5.50 | $27.50 | 1M |
| eu | $5.50 | $27.50 | 1M | |
| us | $5.50 | $27.50 | 1M |
Benchmarks
Coding
ProgramBenchProgram reconstruction — The AI receives a working program and its documentation, then builds a replacement from scratch without the original source code, internet access or decompilation. The score is the percentage of 200 programs that pass every behavioral test. We record each model's best published mini-SWE-agent result, including higher reasoning efforts where available. Partial test-pass rates and almost-solved programs do not count toward this score. Equal scores share a rank here; the official board also uses partial progress to break ties. Higher is better.
0%
via ProgramBench
#5 of 17Best: Claude Opus 5 · 4.5%
SWE-Bench ProAgentic coding — Can the AI fix real bugs in real software? It's handed actual problems from open-source projects and has to write code that genuinely solves them. Higher is better.
64.3%
#7 of 23Best: Claude Fable 5.1 · 81.2%
SWE-Bench VerifiedCoding — Real coding tasks pulled from open-source projects — the AI has to find and fix actual bugs. A human-checked version of the original SWE-Bench. Higher is better.
87.6%
via BenchLM
#5 of 57Best: Claude Opus 5 · 96%
SWE-Bench MultilingualMultilingual coding — Like SWE-Bench, but the coding problems span many programming languages, not just one. Tests how broadly the AI can code. Higher is better.
80.5%
#6 of 14Best: Claude Opus 5 · 89.5%
Next.js EvalsNext.js coding — Vercel's open eval of how well AI coding agents build and migrate real Next.js apps — measured as the share of tasks the agent completes successfully. Higher is better.
58%
#19 of 28Best: Claude Fable 5.1 · 97%
Terminal & CLI
Terminal-Bench 2.1Agentic terminal coding — Can the AI work in a command-line terminal — running commands and finishing technical setup tasks the way a developer would? Higher is better.
66.1%
#27 of 30Best: DeepSeek-V4.1-Flash · 90.6%
Terminal-Bench 2.0Agentic terminal coding — Can the AI work in a command-line terminal — running commands and finishing technical setup tasks the way a developer would? (Version 2.0 of the test.) Higher is better.
69.4%
#5 of 14Best: Claude Mythos 5 · 88%
Agentic & tool use
MCP AtlasMulti-step tool use — Can the AI chain together many tools and steps to complete one bigger task, rather than doing just a single thing? Higher is better.
79.1%
#5 of 11Best: Muse Spark 1.1 · 88.1%
BrowseCompWeb browsing — Can the AI browse the web and track down hard-to-find answers? Higher is better.
79.3%
#20 of 28Best: GPT-5.6 Sol · 92.2%
CyberGymCybersecurity — Tests the AI on cybersecurity challenges — finding and exploiting software weaknesses inside a safe sandbox. Higher is better.
73.1%
#10 of 10Best: DeepSeek-V4.1-Flash · 88.1%
OSWorld-VerifiedAgentic computer use — Can the AI actually operate a computer — clicking, typing, and using real apps — to finish tasks on its own? Higher is better.
78%
#11 of 28Best: Qwen3.8-Max · 86.1%
Reasoning & science
Humanity's Last ExamMultidisciplinary reasoning — Humanity's Last Exam — extremely hard expert questions across many subjects, written so you can't just look up the answer. “No tools” means the AI answers on its own. Higher is better.
46.9%
no tools
54.7%
with tools
no tools
#4 of 22Best: Claude Fable 5.1 · 60.9%
with tools
#15 of 42Best: Claude Fable 5.1 · 65%
ARC-AGI-2Abstract reasoning — Puzzle-style tests of abstract reasoning and pattern-finding — the kind of thing people find easy but AIs often struggle with. Higher is better.
75.8%
#9 of 21Best: GPT-6 Astra · 95%
FrontierMathAdvanced math — Very hard, research-level math problems. Tiers 1–3 are the (still extremely difficult) lower tiers. Higher is better.
43.8%
Tier 1–3
22.9%
Tier 4
Tier 1–3
#5 of 6Best: GPT-5.5-Pro · 52.4%
Tier 4
#5 of 6Best: GPT-5.5-Pro · 39.6%
GPQA DiamondScience — Graduate-level science questions in biology, physics, and chemistry — hard enough that subject-matter PhDs score around 65%. Higher is better.
94.2%
#4 of 59Best: GPT-6 Astra · 96%
Knowledge work
GDPval-AAKnowledge work — Measures how well the AI does economically valuable knowledge work, judged against human experts. Shown as a rating (like a chess Elo) — higher is better.
1753
#4 of 9Best: Claude Fable 5 · 1932
GDPval (win/tie rate)Knowledge work — How often the AI's work matches or beats a human expert's on real knowledge-work tasks. Higher is better.
80.3%
#5 of 6Best: GPT-5.5 · 84.9%
Finance
Finance Agent v2Agentic financial analysis — Tests the AI on real financial-analysis work, like digging through reports and making sound decisions. Higher is better.
51.5%
#6 of 9Best: Gemini 3.8 Flash · 61.4%
Multimodal
CharXiv ReasoningChart reasoning — Can the AI read and reason about complex charts and figures, not just text? Higher is better.
82.1%
#11 of 16Best: Muse Spark · 88.9%
MMMU-ProMultimodal reasoning — A tougher version of MMMU — college-level questions that mix images, diagrams, and text together. Higher is better.
75.2%
#10 of 12Best: Gemini 3.5 Flash · 83.6%
Blueprint-Bench 2Spatial reasoning — Can the AI reason about space and layout — for example, understanding a floor plan or blueprint? Higher is better.
24.5%
#4 of 6Best: GPT-5.5 · 36.2%
Long context
MRCR v2 (8-needle)Long context — Tests whether the AI can find specific details buried inside a very long document (around 128k tokens — roughly a long book). Higher is better.
59.3%
128k average
#7 of 7Best: Gemini 3.7 Flash · 97%
Robustness
BullshitBench v2Nonsense detection — Given a confidently-worded but nonsensical prompt, does the AI spot that it makes no sense and push back — instead of playing along and inventing an answer? The score is how often it clearly called out the nonsense. Higher is better.
83%
#6 of 77Best: Claude Opus 4.8 · 95%
Source: ProgramBench, retrieved 11 September 2026 · Source: BenchLM, retrieved 24 August 2026. Every other score here is the figure the lab published at launch.
Compare Claude Opus 4.7 with
Suggested comparisons
Claude Opus 4.7vsClaude Fable 5.1Claude Opus 4.7vsGPT-6 AstraClaude Opus 4.7vsGemini 3.8 FlashClaude Opus 4.7vsMuse Spark 1.3Claude Opus 4.7vsGrok 4.6Claude Opus 4.7vsDeepSeek-V4.1-FlashClaude Opus 4.7vsMistral Medium 3.5Claude Opus 4.7vsKimi K3Claude Opus 4.7vsGLM-5.3-FlashClaude Opus 4.7vsQwen3.8-Max-0902Claude Opus 4.7vsNemotron 3.5 Lightning
Frequently asked questions
Claude Opus 4.7 was released by Anthropic on Thursday, Apr 16 2026.