Claude Opus 4.7 released
Anthropic · Model release
Source confirmed
Data as of October 13, 2026 · How the score is built
EstablishedProprietaryNon-Reasoning
Claude Opus 4.7
Decision readingClaude Opus 4.7 scores 65.2 out of 100 and ranks #33 of 221. This profile shows 15 source-displayable benchmark rows; its strongest eligible category is Coding at #30. API pricing is $5 input and $25 output per million tokens.
Released Apr 16, 2026 — see all recent releases
Claude Opus 4.7 will be repriced, updated or retired. Get each notice with its source and date. Follow model changes
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
65.2/100
field median 49.8#33 of 221 ranked models
Public
#33of 221
Verified —
Price
$5input / $25 output
input median $0.75blended $15
Speed
50tok/s
field median 90 tok/sFirst token 21.49 s
Context
1Mtokens
field median 256,000Maximum output length is tracked separately
Strongest published evidence
Coding ranks #30. Particularly well-suited for software development and code generation tasks.
Validate before choosing
15 published rows leave some tracked benchmark slots empty. Agentic is its lowest eligible category at #40.
Source-linked · 15 displayable benchmark rows
Follow model changesCheck the published record for the model and serving route you use.
Check this modelCategory 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 | Score | Rank | Percentile | Weight | Benchmarks | Evidence |
|---|---|---|---|---|---|---|
| AgenticRank #40 of 124Percentile 68thWeight 22%5 benchmarksVerified | 54.0 | 5 benchmarks | Verified | |||
| CodingRank #30 of 149Percentile 80thWeight 20%6 benchmarksVerified | 55.6 | 6 benchmarks | Verified | |||
| ReasoningWeight 17%0 benchmarksNot measured | Not measured | 0 benchmarks | Not measured | |||
| MultimodalWeight 12%0 benchmarksNot measured | Not measured | 0 benchmarks | Not measured | |||
| KnowledgeRank #30 of 181Percentile 84thWeight 12%2 benchmarksVerified | 65.3 | 2 benchmarks | Verified | |||
| MultilingualWeight 7%0 benchmarksNot measured | Not measured | 0 benchmarks | Not measured | |||
| Inst. FollowingWeight 5%0 benchmarksNot measured | Not measured | 0 benchmarks | Not measured | |||
| MathRank Not rankedWeight 5%2 benchmarksVerified | 72.9 | 2 benchmarks | Verified |
15 of 670 tracked benchmark slots have displayable evidence · bars run 0–100
Coverage detailsHow 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.
- Agentic5/5 verified
- Coding6/6 verified
- ReasoningNot measured
- MultimodalNot measured
- Knowledge2/2 verified
- MultilingualNot measured
- Inst. FollowingNot measured
- Math2/2 verified
Verified sourceProvisionalNot measured
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 category percentile values
- Agentic68th percentile
- Coding80th percentile
- ReasoningNot eligible
- MultimodalNot eligible
- Knowledge84th percentile
- MultilingualNot eligible
- Instruction followingNot eligible
- MathNot eligible
The dashed outline is median of 6 nearest peers.
Eligible category ranks
- Agentic#40/124
- Coding#30/149
- ReasoningNot ranked
- MultimodalNot ranked
- Knowledge#30/181
- MultilingualNot ranked
- Inst. FollowingNot ranked
- MathNot ranked
Top decileTop quartileMid-fieldNot eligible
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.
Coding6 rows
| Benchmark | Score | Versus best verified row | Gap | Weight | Evidence |
|---|---|---|---|---|---|
| LiveCodeBench (Vals)LiveCodeBench, Vals AI run | Score85.1% | Versus best verified row Best verified: Claude Fable 5.1 · 90.5% | Gap5.4 behind | Weight8% ref. weight | |
| FrontierCode 1.1 Main | Score38.5% | Versus best verified row Best verified: Claude Opus 5.5 · 54.4% | Gap15.9 behind | Weight4% ref. weight | Benchmark exact |
| Vibe Code BenchVibe Code Bench v1.1 | Score71.00% | Versus best verified row Best verified: Gemini 4 Argon · 91.90% | Gap20.9 behind | WeightDisplay only | Benchmark exact |
| React Native Evals | Score82.8% | Versus best verified row Best verified: Composer 2 · 96.1% | Gap13.3 behind | WeightDisplay only | Benchmark exact |
| SWE-bench (Vals)SWE-bench, Vals AI run | Score82.0% | Versus best verified row Best verified: Claude Opus 5 · 97.0% | Gap15 behind | WeightDisplay only | Verified |
| PostTrainBench v1.1 | Score28.6% | Versus best verified row Best verified: Claude Opus 5.5 · 49.3% | Gap20.7 behind | WeightDisplay only | Benchmark exact |
Agentic5 rows
| Benchmark | Score | Versus best verified row | Gap | Weight | Evidence |
|---|---|---|---|---|---|
| OSWorld 2.0 | Score13.9% | Versus best verified row Best verified: GPT-6 Astra · 72.6% | Gap58.7 behind | Weight10% ref. weight | Benchmark exact |
| Terminal-Bench 2.1 (Vals)Terminal-Bench 2.1, Vals AI run | Score68.5% | Versus best verified row Best verified: GPT-6 Astra · 87.3% | Gap18.8 behind | Weight3% ref. weight | |
| Gert LabsGert Labs Composite Game Benchmark | Score65.59% | Versus best verified row Best verified: Claude Opus 4.8 · 72.97% | Gap7.4 behind | WeightDisplay only | Benchmark exact |
| ResearchClawBench | Score20.7% | Versus best verified row Best verified: Claude Opus 4.8 · 21.1% | Gap0.4 behind | WeightDisplay only | Benchmark exact |
| ApprenticeBenchApprenticeBench: end-to-end computer use, continual learning, and long-horizon agency on a real accounts-payable job | Score7% | Versus best verified row Best verified: Claude Fable 5.1 · 72% | Gap65 behind | WeightDisplay only | Benchmark exact |
Knowledge2 rows
| Benchmark | Score | Versus best verified row | Gap | Weight | Evidence |
|---|---|---|---|---|---|
| MMLU-Pro (Vals)MMLU-Pro, Vals AI run | Score89.9% | Versus best verified row Best verified: Claude Fable 5.1 · 92.4% | Gap2.5 behind | Weight6% ref. weight | Verified |
| GPQA Diamond (Vals)GPQA Diamond, Vals AI run | Score90.2% | Versus best verified row Best verified: Gemini 3.1 Pro · 95.5% | Gap5.3 behind | Weight2% ref. weight |
Math2 rows
| Benchmark | Score | Versus best verified row | Gap | Weight | Evidence |
|---|---|---|---|---|---|
| FrontierMath v2 (Tiers 1-3)FrontierMath v2 Tiers 1-3 | Score70.175% | Versus best verified row Best verified: GPT-6 Astra · 93.684% | Gap23.5 behind | WeightWeighted 30% | Benchmark exact |
| FrontierMath v2 (Tier 4)FrontierMath v2 Tier 4 | Score31.707% | Versus best verified row Best verified: GPT-6.1 Sol · 100.000% | Gap68.3 behind | WeightWeighted 10% | Benchmark exact |
Bars run 0–100; the dark tick marks the best source-verified value
All 15 rowsWhat 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.
Current modelExplore all models
Claude Opus 4.7 · 65.2 score · $15 blended per million tokens
The chart opens on the current model. Scroll horizontally to inspect the full price axis.
Horizontal: blended price per million tokens, log scale · Vertical: public score
Lineage
The sequence follows explicit supersedes links. Each score is estimated for that model; a relative can inform a sparse estimate but never sets a floor, so a newer release can score below an earlier one. Scores and prices remain blank when the corresponding public row or first-party rate is unavailable.
Base entry
Claude Opus 4.7 (Adaptive) · 68.0Radar
Full release historyClaude Opus 4.7 release history
Radar confirmed these at the source. Use Claude Opus 4.7 in your work? Explore Radar to follow supported changes and choose your alerts.
Radar
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
- claude-opus-4-7Anthropic model ID documentation
- Context window
- 1MAnthropic model overview
- Maximum output
- Not sourced yet
- Knowledge cutoff
- Not sourced yet
- Input modalities
- text, imageAnthropic model overview
- Output modalities
- textAnthropic model overview
- Parameters
- Not disclosed by the provider
- Availability
- Claude APIAnthropic model overview
- Cloud regions
- Not tracked yet
- Lifecycle
- activeAnthropic model ID documentation
- 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
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 ranks #33 of 221 on the public leaderboard with a score of 65.18/100. It does not yet have enough sourced coverage for a verified position.
Claude Opus 4.7 is a proprietary model with a 1M context window. No explicit reasoning mode is documented in this profile.
Claude Opus 4.7 sits in the Claude Opus 4.7 family with Claude Opus 4.7 (Adaptive). Its explicit predecessor is Claude Opus 4.6. 15 of 670 tracked benchmark slots currently have displayable evidence. Missing categories stay blank.
Its strongest eligible category is Coding at #30, while its lowest eligible position is Agentic at #40. particularly well-suited for software development and code generation tasks.
Last updated October 13, 2026. Runtime fields remain blank until a sourced snapshot exists.
Questions
How does Claude Opus 4.7 perform overall in AI benchmarks?
Claude Opus 4.7 ranks #33 out of 221 models on the public BenchAlign leaderboard, with a score of 65.18/100. Its evidence status is Estimated, and this profile shows 15 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 good for knowledge and understanding?
Claude Opus 4.7 ranks #30 out of 181 eligible models for knowledge and understanding, 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 good for coding and programming?
Claude Opus 4.7 ranks #30 out of 149 eligible models for coding and programming, with a public category score of 55.6/100. 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 good for mathematics?
Claude Opus 4.7 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 good for agentic tool use and computer tasks?
Claude Opus 4.7 ranks #40 out of 124 eligible models for agentic tool use and computer tasks, with a public category score of 54/100. 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?
Claude Opus 4.7 belongs to the Claude Opus 4.7 family. Related tracked variants include Claude Opus 4.7 (Adaptive). 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 have full benchmark coverage on BenchLM?
No. Claude Opus 4.7 currently has 26 source-displayable rows across 670 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?
Claude Opus 4.7 has a documented context window of 1M. That figure is the maximum combined prompt and retained-conversation space reported for this exact model; it is not the maximum output length. The profile keeps output limits separate because providers often publish those limits independently.