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Superseded.Anthropic has newer models in this line:Claude Opus 4.8

Claude Opus 4.7 (Adaptive)

SupersededReleased Apr 16, 2026ProprietaryReasoning1M context

Released Apr 16, 2026 see all recent releases

Decision reading
Claude Opus 4.7 (Adaptive) scores 72.4 out of 100 and ranks #15 of 226. This profile shows 21 source-displayable benchmark rows; its strongest eligible category is Knowledge at #7. API pricing is $5 input and $25 output per million tokens.

Data as of August 26, 2026 · How the score is built

Strongest published evidence

Knowledge ranks #7. Particularly effective for knowledge-intensive tasks like research, analysis, and factual Q&A.

Validate before choosing

21 published rows leave some tracked benchmark slots empty. Independent runtime speed has not been measured.

Decision snapshot

Each value carries a field reference instead of floating alone. Markers compare this model with the current ranked and priced catalog; they are not absolute quality thresholds.

Capability

72.4/100

field median 58.3

#15 of 226 ranked models

Price

$5input / $25 output

input median $1

blended $15

Speed

Not measured

field median 97 tok/s

Time to first token not measured

Context

1Mtokens

field median 203,000

Reported for this model; direct source link not stored

Capability shape

Each axis shows percentile within that category’s eligible cohort. The comparison outline is the median of the six nearest public-score peers; a collapsed vertex means the category is not rank-eligible.

Claude Opus 4.7 (Adaptive) category percentile values

  • Agentic92nd percentile
  • Coding90th percentile
  • ReasoningNot eligible
  • Knowledge90th percentile
  • MathNot eligible
  • MultilingualNot eligible
  • Multimodal18th percentile
  • Instruction followingNot eligible

The dashed outline is median of 6 nearest peers.

Eligible category ranks

  1. Agentic#12/138
  2. Coding#16/144
  3. ReasoningNot ranked
  4. Knowledge#7/60
  5. MathNot ranked
  6. MultilingualNot ranked
  7. Multimodal#29/35
  8. Inst. FollowingNot ranked
Top decileTop quartileMid-fieldNot eligible

What it costs to get this score

Published API price against the public score. The x-axis uses a log scale; the dashed path marks models that are not beaten by a cheaper, higher-scoring option. Price uses average of published input and output rates.

Explore all models

The chart opens on the current model. Scroll horizontally to inspect the full price axis.

Current modelClaude Opus 4.7 (Adaptive) · 72.4 score · $15 blended per million tokens
405060708090$0.50$1$5$10$25$50$100↘ frontierClaude Opus 4.7 (Adaptive)

Horizontal: blended price per million tokens, log scale · Vertical: public score

How much of this is verified

Coverage is split by category so a strong number never hides a thin evidence base. Verified means the row is tied to a published source; provisional rows remain visible but separate.

  1. Agentic6/7 verified
  2. Coding3/3 verified
  3. Reasoning1/3 verified
  4. Knowledge4/4 verified
  5. Math0/1 verified
  6. MultilingualNot measured
  7. Multimodal2/3 verified
  8. Inst. FollowingNot measured
Verified sourceProvisionalNot measured

Spec sheet

Each documented value carries its source. Missing fields stay visible as not sourced or not published, rather than disappearing from the page.

API model ID
Not published
Context window
1M
Maximum output
Not sourced yet
Knowledge cutoff
Not sourced yet
Input modalities
Not sourced yet
Output modalities
Not sourced yet
Parameters
Not disclosed by the provider
Availability
Not sourced yet
Cloud regions
Not tracked yet
Lifecycle
Superseded
API capabilities
Tool calling, structured outputs, and batch support are not tracked yet
Prompt caching
Not documented in the pricing record
Self-host
Weights are not published
Rate limits
Not tracked yet

Category score record

Scores and ranks appear only where published evidence can be displayed. The table keeps the score, weight, cohort, and evidence state together.

Category scores, ranks, weighting, benchmark coverage, and evidence status
CategoryScore
AgenticRank #12 of 138Percentile 92ndWeight 22%7 benchmarksMixed sources63.7
CodingRank #16 of 144Percentile 90thWeight 20%3 benchmarksVerified65.3
ReasoningRank Not rankedWeight 17%3 benchmarksMixed sources75.2
KnowledgeRank #7 of 60Percentile 90thWeight 12%4 benchmarksVerified83.1
MathWeight 5%1 benchmarkReportedScore pending
MultilingualWeight 7%0 benchmarksNot measuredNot measured
MultimodalRank #29 of 35Percentile 18thWeight 12%3 benchmarksMixed sources48.1
Inst. FollowingWeight 5%0 benchmarksNot measuredNot measured

Benchmark ledger

Coding opens by default. The marker compares each value with the best source-verified result in the catalog; provisional leaders do not set the reference. Expand the remaining categories for every published row.

Coding3 rows
Coding benchmark values, best verified comparison, weight, and source status
SWE-bench VerifiedSoftware Engineering Benchmark VerifiedScore87.6%Versus best verified row

Best verified: Claude Opus 5 · 96%

Gap8.4 behindWeightWeighted 16%
SWE-bench ProScore64.3%Versus best verified row

Best verified: Claude Mythos 5 · 80.3%

Gap16 behindWeightWeighted 10%
Terminal-Bench 2.0Score69.4%Versus best verified row

Best verified: GPT-5.6 Sol · 91.9%

Gap22.5 behindWeightDisplay only
Agentic7 rows
Agentic benchmark values, best verified comparison, weight, and source status
Terminal-Bench 2.0Score69.4%Versus best verified row

Best verified: GPT-5.6 Sol · 91.9%

Gap22.5 behindWeightWeighted 38%
OSWorld-VerifiedScore78%Versus best verified row

Best verified: Qwen3.8 Max · 86.1%

Gap8.1 behindWeightWeighted 34%
BrowseCompScore79.3%Versus best verified row

Best verified: GPT-5.6 Sol · 92.2%

Gap12.9 behindWeightWeighted 28%
MCP AtlasScore77.3%Versus best verified row

Best verified: Muse Spark 1.1 · 88.1%

Gap10.8 behindWeightDisplay only
CyberGymScore73.1%Versus best verified row

Best verified: Fugu Cyber · 86.9%

Gap13.8 behindWeightDisplay only
OSWorld 2.0Score18.2%Versus best verified row

Best verified: Claude Opus 5 · 70.6%

Gap52.4 behindWeightDisplay only
Benchmark exact
JobBenchScore45.9%Versus best verified row

Best verified: Qwen3.8-Flash-Next · 55.7%

Gap9.8 behindWeightDisplay only
Benchmark exact
Reasoning3 rows
Reasoning benchmark values, best verified comparison, weight, and source status
ARC-AGI-2Abstraction and Reasoning Corpus for AGI v2Score75.8%Versus best verified row

Best verified: GPT-5.6 Sol · 92.5%

Gap16.7 behindWeightWeighted 31%
MRCR v2 128K-256KOpenAI MRCR v2 8-needle 128K-256KScore59.2%Versus best verified row

Best verified: GPT-5.5 · 87.5%

Gap28.3 behindWeightDisplay only
ARC-AGI-3Abstraction and Reasoning Corpus for AGI v3Score0.2%Versus best verified row

Best verified: Claude Opus 5 · 30.2%

Gap30 behindWeightDisplay only
Knowledge4 rows
Knowledge benchmark values, best verified comparison, weight, and source status
HLEHumanity's Last ExamScore54.7%Versus best verified row

Best verified: Claude Opus 5 · 64.7%

Gap10 behindWeightWeighted 45%
GPQAGraduate-Level Google-Proof Q&AScore94.2%Versus best verified row

Best verified: Sakana Fugu-Ultra · 95.5%

Gap1.3 behindWeightWeighted 7%
GPQA-DGPQA DiamondScore94.2%Versus best verified row

Best verified: Sakana Fugu-Ultra · 95.5%

Gap1.3 behindWeightDisplay only
HLE w/o toolsHumanity's Last Exam without toolsScore46.9%Versus best verified row

Best verified: Claude Mythos 5 · 59%

Gap12.1 behindWeightDisplay only
Math1 row
Math benchmark values, best verified comparison, weight, and source status
FrontierMath (legacy)FrontierMath legacy aggregateScore43.8%Versus best verified row

Best verified: GPT-5.6 Sol · 89%

Gap45.2 behindWeightDisplay only
Multimodal3 rows
Multimodal benchmark values, best verified comparison, weight, and source status
OfficeQA ProScore43.6%Versus best verified row

Best verified: Claude Opus 5 · 66.9%

Gap23.3 behindWeightWeighted 30%
CharXivCharXiv ReasoningScore91%Versus best verified row

Best verified: Claude Mythos 5 · 93.5%

Gap2.5 behindWeightWeighted 25%
CharXiv w/o toolsCharXiv Reasoning without toolsScore82.1%Versus best verified row

Best verified: Claude Mythos 5 · 88.9%

Gap6.8 behindWeightDisplay only

Lineage

The sequence follows explicit supersedes links. Scores and prices remain blank when the corresponding public row or first-party rate is unavailable.

  1. February 2026

    Claude Opus 4.6

    Score 68.1 · $5 / $25

  2. Apr 16, 2026 · you are here

    Claude Opus 4.7 (Adaptive)

    Score 72.4 · $5 / $25

  3. May 28, 2026

    Claude Opus 4.8

    Score 76.5 · $5 / $25

reasoning · adaptive

How to read this profile

The visual layer above carries the decisions. These notes preserve the model, ranking, coverage, and family context behind the numbers.

Claude Opus 4.7 (Adaptive) ranks #15 of 226 on the public leaderboard with a score of 72.41/100. It does not yet have enough sourced coverage for a verified position.

Claude Opus 4.7 (Adaptive) is a proprietary model with a 1M context window. It uses an explicit reasoning mode, which can improve complex problem solving while adding latency and token use.

Claude Opus 4.7 (Adaptive) sits in the Claude Opus 4.7 family with Claude Opus 4.7. Its explicit predecessor is Claude Opus 4.6. 21 of 406 tracked benchmark slots currently have displayable evidence. Missing categories stay blank.

Its strongest eligible category is Knowledge at #7, while its lowest eligible position is Multimodal & Grounded at #29. particularly effective for knowledge-intensive tasks like research, analysis, and factual Q&A.

Radar

Claude Opus 4.7 (Adaptive) release history

Full release history

Radar confirmed these at the source. Start the free Radar Brief

Frequently asked questions

How does Claude Opus 4.7 (Adaptive) perform overall in AI benchmarks?

Claude Opus 4.7 (Adaptive) ranks #15 out of 226 models on the public BenchAlign leaderboard, with a score of 72.41/100. Its evidence status is Estimated, and this profile shows 21 source-displayable benchmark rows. The label describes evidence depth, not a provider quality claim; inspect category rows before choosing a workload.

Is Claude Opus 4.7 (Adaptive) good for knowledge and understanding?

Claude Opus 4.7 (Adaptive) ranks #7 out of 60 eligible models for knowledge and understanding, with a public category score of 83.1/100. That places it in the current top ten for this category. Check the underlying rows before treating the aggregate as a workload guarantee.

Is Claude Opus 4.7 (Adaptive) good for coding and programming?

Claude Opus 4.7 (Adaptive) ranks #16 out of 144 eligible models for coding and programming, with a public category score of 65.3/100. Higher-ranked alternatives are available for workloads where this category decides the choice. Check the underlying rows before treating the aggregate as a workload guarantee.

Is Claude Opus 4.7 (Adaptive) good for mathematics?

Claude Opus 4.7 (Adaptive) has source-displayable benchmark coverage for mathematics, but the public category table does not assign it a rank there. The individual rows remain available for inspection. A missing category position means the evidence threshold was not met; it does not convert the model's unmeasured work into a zero.

Is Claude Opus 4.7 (Adaptive) good for reasoning and logic?

Claude Opus 4.7 (Adaptive) has source-displayable benchmark coverage for reasoning and logic, but the public category table does not assign it a rank there. The individual rows remain available for inspection. A missing category position means the evidence threshold was not met; it does not convert the model's unmeasured work into a zero.

Is Claude Opus 4.7 (Adaptive) good for agentic tool use and computer tasks?

Claude Opus 4.7 (Adaptive) ranks #12 out of 138 eligible models for agentic tool use and computer tasks, with a public category score of 63.7/100. Higher-ranked alternatives are available for workloads where this category decides the choice. Check the underlying rows before treating the aggregate as a workload guarantee.

Is Claude Opus 4.7 (Adaptive) good for multimodal and grounded tasks?

Claude Opus 4.7 (Adaptive) ranks #29 out of 35 eligible models for multimodal and grounded tasks, with a public category score of 48.1/100. Higher-ranked alternatives are available for workloads where this category decides the choice. Check the underlying rows before treating the aggregate as a workload guarantee.

Which sibling models are related to Claude Opus 4.7 (Adaptive)?

Claude Opus 4.7 (Adaptive) belongs to the Claude Opus 4.7 family. Related tracked variants include Claude Opus 4.7. A sibling link indicates shared lineage or a documented configuration relationship; it does not mean the variants have identical pricing, context limits, benchmark evidence, or deployment behavior. Compare before switching.

Does Claude Opus 4.7 (Adaptive) have full benchmark coverage on BenchLM?

No. Claude Opus 4.7 (Adaptive) currently has 39 source-displayable rows across 406 tracked benchmark slots. The profile exposes published, non-generated evidence and leaves missing categories blank until an exact evaluation is available. Coverage describes how much was measured; it is not a penalty added to an individual benchmark result.

What is the context window size of Claude Opus 4.7 (Adaptive)?

Claude Opus 4.7 (Adaptive) has a reported context window of 1M in the exact-model catalog record. The value stays visible, but the profile marks its source link as unavailable instead of presenting it as directly documented. Maximum output length remains separate because providers often publish a different limit.

Compare Claude Opus 4.7 (Adaptive) with every tracked model396 comparisons

Last updated August 26, 2026. Runtime fields remain blank until a sourced snapshot exists.

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