Long documents
Prompts that approach the documented context limit
Claude Opus 4.7 (Adaptive)
Claude Opus 4.7 (Adaptive) has the larger documented context window.
Confidence: documented
Claude Opus 4.7 (Adaptive) vs Claude Sonnet 4.5
Updated October 20, 2026. Rank says Claude Opus 4.7 (Adaptive) is ahead. Price, access, and your workload can each overturn that. Public scores include evidence status and uncertainty.
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Decision reading
Claude Opus 4.7 (Adaptive) has the higher public point estimate, 68.67 versus 47.93. Their conditional score ranges overlap. These ranges do not establish rank confidence. 7 results are shared. Category rows resting on Estimated evidence or different benchmark sets are marked directional and do not name a winner.
Model A
Anthropic
68.67/100
Estimated · Public rank #23
Conditional range 54.3–83.0
- Shared results
- 7
- Claude Opus 4.7 (Adaptive) only
- 14
- Claude Sonnet 4.5 only
- 5
- Like-for-like categories
- 0 / 8
Estimated: Claude Opus 4.7 (Adaptive) and Claude Sonnet 4.5. Conditional ranges do not establish rank confidence.How the comparison works
Which one for your work
Recommendations appear only when a shared evidence basis or an explicit operating constraint supports the call. Secondary and unsupported use cases stay disclosed below the initial list.
Chat turn cost
1K fresh input + 500 output tokens
Claude Sonnet 4.5
Claude Sonnet 4.5 has the lower estimated token cost for this stated workload. Costs use the listed standard API rates.
Confidence: listed-rates
Show secondary and unsupported calls
Repository review cost
50K fresh input + 3K output tokens
Claude Sonnet 4.5
Claude Sonnet 4.5 has the lower estimated token cost for this stated workload. Costs use the listed standard API rates.
Confidence: listed-ratesCoding work
Code generation, repair, and software-engineering tasks
Not enough matched evidence
Claude Sonnet 4.5 is not ranked on the public lane for coding, so no winner is named for coding.
Confidence: limitedAgentic work
Tool use, computer use, and multi-step task completion
Not enough matched evidence
Claude Sonnet 4.5 is scored on Estimated evidence for agentic, so the reading is directional rather than like-for-like.
Confidence: limitedCache-heavy agent loop cost
200K cached + 20K fresh input + 10K output tokens
Not enough matched evidence
The page does not recommend a cost winner because at least one model cannot fit the stated workload in one request. Claude Sonnet 4.5 does not fit this workload in one request. Claude Opus 4.7 (Adaptive) has no published cached-input rate, so cached tokens use its listed input rate. Claude Sonnet 4.5 has no published cached-input rate, so cached tokens use its listed input rate.
Confidence: rate-fallback
Which one for a specific job
Choose a job from the LLM Selector's task catalog to see the category row it rests on, under the same basis rules as the table below. A directional row stays directional; choosing a job never creates a winner.
The same task catalog as the LLM Selector. Each job names the evidence surface it rests on; nothing here adds a new score.
55.5Claude Opus 4.7 (Adaptive)—Claude Sonnet 4.5
Not comparable · BenchAlign v5.8
The coding row is not comparable on the public lane: at least one model is not measured or not ranked there.
Coding scores combine specific tasks and setups. Match the editor, harness, and effort to your workflow.
Same basis rules as the category table below
What is actually comparable
Shared results can support a head-to-head reading. Results present for only one model describe coverage, not superiority.
14 Claude Opus 4.7 (Adaptive) only
7 Shared
5 Claude Sonnet 4.5 only
1 category rests on Estimated evidence or different evidence sets. Those rows remain visible for coverage context but do not name a winner.
Shape of the matched evidence
Only shared public evidence is shown. Sparse evidence stays a ruled list rather than being closed into a radar shape.
Too few matched category axes support a radar. The ruled list below shows only shared benchmark results; positions use each benchmark’s normalized display scale when available.
ARC-AGI-2Reasoning
Normalized gap 62.2Claude Opus 4.7 (Adaptive):75.8%Claude Sonnet 4.5:13.6%Terminal-Bench 2.0Agentic
Normalized gap 19.4Claude Opus 4.7 (Adaptive):69.4%Claude Sonnet 4.5:50%OSWorld-VerifiedAgentic
Normalized gap 16.6Claude Opus 4.7 (Adaptive):78%Claude Sonnet 4.5:61.4%GPQAKnowledge
Normalized gap 10.8Claude Opus 4.7 (Adaptive):94.2%Claude Sonnet 4.5:83.4%SWE-bench VerifiedCoding
Normalized gap 10.4Claude Opus 4.7 (Adaptive):87.6%Claude Sonnet 4.5:77.2%
Bars run 0–100 on each benchmark’s normalized display scale
Category results, on a stated basis
Each row shows the public-lane category score for both models: the BenchAlign v5.8 lane for agentic, coding, and knowledge, and the weighted public rows elsewhere, with the same rank each model page reports. A row is like-for-like only when both scores rest on Supported evidence or the same weighted set. Directional and not-comparable rows remain visible, but they never receive a winner.
Agentic
Directional only- Claude Opus 4.7 (Adaptive)
- 59.7
- Supported · #29/131
- Claude Sonnet 4.5
- 35.3
- Estimated · #82/131
- Basis
- BenchAlign v5.8 lane · 7 vs 5 public rows
- Reading
- Directional only
Coding
Not comparable- Claude Opus 4.7 (Adaptive)
- 55.5
- Estimated · #32/152
- Claude Sonnet 4.5
- Not ranked
- Basis
- BenchAlign v5.8 lane · 3 vs 2 public rows
- Reading
- Not comparable
Reasoning
Not comparable- Claude Opus 4.7 (Adaptive)
- 57.4
- Unranked · 3 rankable rows
- Claude Sonnet 4.5
- 22.9
- Unranked · 1 rankable row
- Basis
- Provisional lane · 2 vs 1 weighted rows
- Reading
- Not comparable
Multimodal
Not comparable- Claude Opus 4.7 (Adaptive)
- 53.7
- #47/55
- Claude Sonnet 4.5
- Not ranked
- Basis
- Provisional lane · 2 vs 0 weighted rows
- Reading
- Not comparable
Knowledge
Not comparable- Claude Opus 4.7 (Adaptive)
- 66.2
- Estimated · #30/187
- Claude Sonnet 4.5
- Not ranked
- Basis
- BenchAlign v5.8 lane · 4 vs 1 public rows
- Reading
- Not comparable
Multilingual
Not comparable- Claude Opus 4.7 (Adaptive)
- Not ranked
- Claude Sonnet 4.5
- Not ranked
- Basis
- Provisional lane · 0 vs 0 weighted rows
- Reading
- Not comparable
Instruction following
Not comparable- Claude Opus 4.7 (Adaptive)
- Not ranked
- Claude Sonnet 4.5
- Not ranked
- Basis
- Provisional lane · 0 vs 0 weighted rows
- Reading
- Not comparable
Math
Not comparable- Claude Opus 4.7 (Adaptive)
- Not ranked
- Claude Sonnet 4.5
- 36.4
- Unranked · 2 rankable rows
- Basis
- Provisional lane · 0 vs 2 weighted rows
- Reading
- Not comparable
| Category | Claude Opus 4.7 (Adaptive) | Claude Sonnet 4.5 | Basis | Reading |
|---|---|---|---|---|
| Agentic | 59.7Supported · #29/131 | 35.3Estimated · #82/131 | Directional onlyBenchAlign v5.8 lane · 7 vs 5 public rows | Directional only |
| Coding | 55.5Estimated · #32/152 | Not ranked | Not comparableBenchAlign v5.8 lane · 3 vs 2 public rows | Not comparable |
| Reasoning | 57.4Unranked · 3 rankable rows | 22.9Unranked · 1 rankable row | Not comparableProvisional lane · 2 vs 1 weighted rows | Not comparable |
| Multimodal | 53.7#47/55 | Not ranked | Not comparableProvisional lane · 2 vs 0 weighted rows | Not comparable |
| Knowledge | 66.2Estimated · #30/187 | Not ranked | Not comparableBenchAlign v5.8 lane · 4 vs 1 public rows | Not comparable |
| Multilingual | Not ranked | Not ranked | Not comparableProvisional lane · 0 vs 0 weighted rows | Not comparable |
| Instruction following | Not ranked | Not ranked | Not comparableProvisional lane · 0 vs 0 weighted rows | Not comparable |
| Math | Not ranked | 36.4Unranked · 2 rankable rows | Not comparableProvisional lane · 0 vs 2 weighted rows | Not comparable |
Ranks count the models scored in each category’s lane, so the agentic, coding, and knowledge denominators (BenchAlign v5.8) differ from the provisional-lane categories. Unranked scores sit on the provisional lane’s scale but never name a winner. Like-for-like rows within 0.5 points read as a practical tie.
Supported evidence per lane · bars run 0–100Methodology
What each workload costs
Three fixed token mixes turn per-token rates into comparable decisions. Each scenario states context fit and whether cached input had to fall back to the published list-input rate.
Chat turn
1K fresh input + 500 output tokens
- Claude Opus 4.7 (Adaptive)
- $0.0175
- Fits in one request
- Claude Sonnet 4.5
- $0.0105
- Fits in one request
Claude Sonnet 4.5 has the lower modeled cost
Costs use the listed standard API rates.
Repository review
50K fresh input + 3K output tokens
- Claude Opus 4.7 (Adaptive)
- $0.325
- Fits in one request
- Claude Sonnet 4.5
- $0.195
- Fits in one request
Claude Sonnet 4.5 has the lower modeled cost
Costs use the listed standard API rates.
Cache-heavy agent loop
200K cached + 20K fresh input + 10K output tokens
- Claude Opus 4.7 (Adaptive)
- $1.35
- Fits in one request
- Cached input priced at the published list-input rate
- Claude Sonnet 4.5
- $0.81
- Does not fit in one request
- Cached input priced at the published list-input rate
Claude Sonnet 4.5 does not fit this workload in one request. Claude Opus 4.7 (Adaptive) has no published cached-input rate, so cached tokens use its listed input rate. Claude Sonnet 4.5 has no published cached-input rate, so cached tokens use its listed input rate.
Cached input falls back to the list input rate only where a cached rate is unpublished
Specification differences
Sourced differences are shown directly. Missing facts stay explicit instead of being inferred from a model name or family.
SpecificationClaude Opus 4.7 (Adaptive)Claude Sonnet 4.5
Context window
Maximum documented context; output-token limits may be lower.
Claude Opus 4.7 (Adaptive)
1M
Claude Sonnet 4.5
200K
API model ID
Claude Opus 4.7 (Adaptive)
Not sourced
Claude Sonnet 4.5
Not sourced
Cached-input rate
A missing cached-input rate falls back to the listed input rate only in the stated workload estimate.
Claude Opus 4.7 (Adaptive)
Not published
Claude Sonnet 4.5
Not published
Documented inputs
Claude Opus 4.7 (Adaptive)
Not sourced
Claude Sonnet 4.5
Not sourced
Documented outputs
Claude Opus 4.7 (Adaptive)
Not sourced
Claude Sonnet 4.5
Not sourced
Provider availability
Claude Opus 4.7 (Adaptive)
Not sourced
Claude Sonnet 4.5
Not sourced
Reasoning profile
Claude Opus 4.7 (Adaptive)
Reasoning
Claude Sonnet 4.5
Non-Reasoning
Weight access
Claude Opus 4.7 (Adaptive)
Proprietary
Claude Sonnet 4.5
Proprietary
License
Claude Opus 4.7 (Adaptive)
Proprietary
Claude Sonnet 4.5
Proprietary
Release date
Claude Opus 4.7 (Adaptive)
2026-04-16
Claude Sonnet 4.5
2025-09-29
If you already use one of these models
- Deployment change
- Both entries list Anthropic as the provider. Confirm endpoint, model ID, limits, and feature support before switching.
- Quality signal
- Claude Opus 4.7 (Adaptive) has the higher public point estimate, 68.67 versus 47.93. Their conditional score ranges overlap. These ranges do not establish rank confidence.
- Workload cost
- Repository review: $0.325 vs $0.195. Cache-heavy agent loop: $1.35 vs $0.81.
- Context tradeoff
- Claude Opus 4.7 (Adaptive) has the larger documented window (1M).
Run the same representative tasks against both endpoints before changing production traffic.
Questions
Which is better, Claude Opus 4.7 (Adaptive) or Claude Sonnet 4.5?
Claude Opus 4.7 (Adaptive) has the higher public point estimate, 68.67 versus 47.93. Their conditional score ranges overlap. These ranges do not establish rank confidence. The page therefore keeps the decision tied to the specific documented workload.
Which is better for coding, Claude Opus 4.7 (Adaptive) or Claude Sonnet 4.5?
Claude Sonnet 4.5 is not ranked on the public lane for coding, so no winner is named for coding.
Which is better for agentic tasks, Claude Opus 4.7 (Adaptive) or Claude Sonnet 4.5?
Claude Opus 4.7 (Adaptive) scores higher for agentic tasks on the public lane, 59.7 to 35.3. Claude Sonnet 4.5 is scored on Estimated evidence for agentic tasks, so the reading is directional rather than like-for-like. BenchLM does not name a winner for agentic tasks from a directional reading; read the shared benchmark rows directly and test the models on the same task set.
Which costs less, Claude Opus 4.7 (Adaptive) or Claude Sonnet 4.5?
For the stated presets, chat costs $0.0175 on Claude Opus 4.7 (Adaptive) and $0.0105 on Claude Sonnet 4.5; repository review costs $0.325 and $0.195; the cache-heavy agent loop costs $1.35 and $0.81. Claude Sonnet 4.5 does not fit this workload in one request. Claude Opus 4.7 (Adaptive) has no published cached-input rate, so cached tokens use its listed input rate. Claude Sonnet 4.5 has no published cached-input rate, so cached tokens use its listed input rate.
Which has the larger context window, Claude Opus 4.7 (Adaptive) or Claude Sonnet 4.5?
Claude Opus 4.7 (Adaptive) has the larger documented context window: 1M, compared with 200K.
Benchmark evidence
The full public result ledger is available for audit without forcing a wide desktop table onto a phone.
Browse raw public benchmark evidence26 rows
Agentic
Terminal-Bench 2.0
Claude Opus 4.7 (Adaptive)69.4%SourceClaude Sonnet 4.550%SourceClaude Opus 4.7 (Adaptive) leads this result
BrowseComp
Claude Opus 4.7 (Adaptive)79.3%SourceClaude Sonnet 4.5—Not directly comparable
MCP Atlas
Claude Opus 4.7 (Adaptive)77.3%SourceClaude Sonnet 4.5—Not directly comparable
OSWorld-Verified
Claude Opus 4.7 (Adaptive)78%SourceClaude Sonnet 4.561.4%SourceClaude Opus 4.7 (Adaptive) leads this result
CyberGym
Claude Opus 4.7 (Adaptive)73.1%SourceClaude Sonnet 4.5—Not directly comparable
OSWorld 2.0
Claude Opus 4.7 (Adaptive)18.2%SourceClaude Sonnet 4.5—Not directly comparable
JobBench
Shared sourceClaude Opus 4.7 (Adaptive)45.9%Claude Sonnet 4.527.7%Claude Opus 4.7 (Adaptive) leads this result
VITA-Bench
Claude Opus 4.7 (Adaptive)—Claude Sonnet 4.517.0%SourceNot directly comparable
Gert Labs
Claude Opus 4.7 (Adaptive)—Claude Sonnet 4.548.51%SourceNot directly comparable
Coding
SWE-bench Verified
Claude Opus 4.7 (Adaptive)87.6%SourceClaude Sonnet 4.577.2%SourceClaude Opus 4.7 (Adaptive) leads this result
SWE-bench Pro
Claude Opus 4.7 (Adaptive)64.3%SourceClaude Sonnet 4.5—Not directly comparable
Terminal-Bench 2.0
Claude Opus 4.7 (Adaptive)69.4%SourceClaude Sonnet 4.550.0%SourceClaude Opus 4.7 (Adaptive) leads this result
Reasoning
MRCR v2 128K-256K
Claude Opus 4.7 (Adaptive)59.2%SourceClaude Sonnet 4.5—Not directly comparable
ARC-AGI-2
Claude Opus 4.7 (Adaptive)75.8%SourceClaude Sonnet 4.513.6%SourceClaude Opus 4.7 (Adaptive) leads this result
ARC-AGI-3
Claude Opus 4.7 (Adaptive)0.2%SourceClaude Sonnet 4.5—Not directly comparable
Multimodal
Knowledge
GPQA
Claude Opus 4.7 (Adaptive)94.2%SourceClaude Sonnet 4.583.4%SourceClaude Opus 4.7 (Adaptive) leads this result
GPQA-D
Claude Opus 4.7 (Adaptive)94.2%SourceClaude Sonnet 4.5—Not directly comparable
HLE
Claude Opus 4.7 (Adaptive)54.7%SourceClaude Sonnet 4.5—Not directly comparable
HLE w/o tools
Claude Opus 4.7 (Adaptive)46.9%SourceClaude Sonnet 4.5—Not directly comparable
Math
FrontierMath (legacy)
Claude Opus 4.7 (Adaptive)43.8%SourceClaude Sonnet 4.5—Not directly comparable
AIME 2025
Claude Opus 4.7 (Adaptive)—Claude Sonnet 4.587%SourceNot directly comparable
FrontierMath v2 (Tiers 1-3)
Claude Opus 4.7 (Adaptive)—Claude Sonnet 4.523.860%SourceNot directly comparable
FrontierMath v2 (Tier 4)
Claude Opus 4.7 (Adaptive)—Claude Sonnet 4.52.439%SourceNot directly comparable
26 public results · 7 shared
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Last updated October 20, 2026