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.
Updated September 23, 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.
Both of these models will change. Get the price, version and retirement notices for the pair, each with its source. Follow model changes
Claude Opus 4.7 (Adaptive) has the higher public score, 68.83 versus 45.32, and the 90% score intervals do not overlap. 5 results are shared. Category rows resting on Estimated evidence or different benchmark sets are marked directional and do not name a winner.
Anthropic
68.83/100
Estimated · Public rank #18
90% interval 57.3–80.3
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.
Prompts that approach the documented context limit
Claude Opus 4.7 (Adaptive)
Claude Opus 4.7 (Adaptive) has the larger documented context window.
Code generation, repair, and software-engineering tasks
Not enough matched evidence
Claude Opus 4.7 (Adaptive) and Hy3 Preview are scored on Estimated evidence for coding, so the reading is directional rather than like-for-like.
Tool use, computer use, and multi-step task completion
Not enough matched evidence
Hy3 Preview is not ranked on the public lane for agentic, so no winner is named for agentic.
1K fresh input + 500 output tokens
Not enough matched evidence
A complete comparable API-rate estimate is not available for both models.
200K cached + 20K fresh input + 10K output tokens
Not enough matched evidence
A complete comparable API-rate estimate is not available for both models.
50K fresh input + 3K output tokens
Not enough matched evidence
A complete comparable API-rate estimate is not available for both models.
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.
Directional only · BenchAlign v5.6
Claude Opus 4.7 (Adaptive) scores higher, but at least one score rests on Estimated evidence or a different benchmark set. Directional only, no winner.
Coding scores combine specific tasks and setups. Match the editor, harness, and effort to your workflow.
Shared results can support a head-to-head reading. Results present for only one model describe coverage, not superiority.
2 categories rest on Estimated evidence or different evidence sets. Those rows remain visible for coverage context but do not name a winner.
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.
Terminal-Bench 2.0Agentic
Normalized gap 15.0SWE-bench VerifiedCoding
Normalized gap 13.2GPQAKnowledge
Normalized gap 7.0Each row shows the public-lane category score for both models: the BenchAlign v5.6 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.
| Category | Claude Opus 4.7 (Adaptive) | Hy3 Preview | Basis | Reading |
|---|---|---|---|---|
| Coding | 56.9Estimated · #22/135 | 33.3Estimated · #85/135 | Directional onlyBenchAlign v5.6 lane · 3 vs 2 public rows | Directional only |
| Knowledge | 62.6Estimated · #28/160 | 39.1Estimated · #93/160 | Directional onlyBenchAlign v5.6 lane · 4 vs 2 public rows | Directional only |
| Agentic | 58.6Supported · #19/105 | Not ranked | Not comparableBenchAlign v5.6 lane · 7 vs 2 public rows | Not comparable |
| Reasoning | 49.7Unranked · 3 rankable rows | Not ranked | Not comparableProvisional lane · 2 vs 0 weighted rows | Not comparable |
| Multimodal | 50.1#38/50 | Not ranked | Not comparableProvisional lane · 2 vs 0 weighted rows | Not comparable |
| Multilingual | Not ranked | Not ranked | Not comparableProvisional lane · 0 vs 0 weighted rows | Not comparable |
| Instruction following | Not ranked | 46.9#86/124 | Not comparableProvisional lane · 0 vs 0 weighted rows | Not comparable |
| Math | Not ranked | Not ranked | Not comparableProvisional lane · 0 vs 0 weighted rows | Not comparable |
Ranks count the models scored in each category’s lane, so the agentic, coding, and knowledge denominators (BenchAlign v5.6) 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.
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.
1K fresh input + 500 output tokens
Hy3 Preview has no comparable published API token rate.
50K fresh input + 3K output tokens
Hy3 Preview has no comparable published API token rate.
200K cached + 20K fresh input + 10K output tokens
Claude Opus 4.7 (Adaptive) has no published cached-input rate, so cached tokens use its listed input rate. Hy3 Preview has no comparable published API token rate.
Sourced differences are shown directly. Missing facts stay explicit instead of being inferred from a model name or family.
Maximum documented context; output-token limits may be lower.
Claude Opus 4.7 (Adaptive)
1M
Hy3 Preview
256K
Claude Opus 4.7 (Adaptive)
Not sourced
Hy3 Preview
Not sourced
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
Hy3 Preview
No comparable hosted API rate
Claude Opus 4.7 (Adaptive)
Not sourced
Hy3 Preview
Not sourced
Claude Opus 4.7 (Adaptive)
Not sourced
Hy3 Preview
Not sourced
Claude Opus 4.7 (Adaptive)
Not sourced
Hy3 Preview
Not sourced
Claude Opus 4.7 (Adaptive)
Reasoning
Hy3 Preview
Reasoning
Claude Opus 4.7 (Adaptive)
Proprietary
Hy3 Preview
Open Weight
Claude Opus 4.7 (Adaptive)
Proprietary
Hy3 Preview
Open Weight
Claude Opus 4.7 (Adaptive)
2026-04-16
Hy3 Preview
2026-04-23
Claude Opus 4.7 (Adaptive) has the higher public score, 68.83 versus 45.32, and the 90% score intervals do not overlap. That is the clearest overall quality signal in the current public data.
Claude Opus 4.7 (Adaptive) scores higher for coding on the public lane, 56.9 to 33.3. Claude Opus 4.7 (Adaptive) and Hy3 Preview are scored on Estimated evidence for coding, so the reading is directional rather than like-for-like. BenchLM does not name a winner for coding from a directional reading; read the shared benchmark rows directly and test the models on the same task set.
Hy3 Preview is not ranked on the public lane for agentic tasks, so no winner is named for agentic tasks.
Both models do not have comparable published API token rates, so this page does not name a universal price winner.
Claude Opus 4.7 (Adaptive) has the larger documented context window: 1M, compared with 256K.
The full public result ledger is available for audit without forcing a wide desktop table onto a phone.
Terminal-Bench 2.0
Claude Opus 4.7 (Adaptive) leads this result
BrowseComp
Not directly comparable
MCP Atlas
Not directly comparable
OSWorld-Verified
Not directly comparable
CyberGym
Not directly comparable
OSWorld 2.0
Not directly comparable
JobBench
Not directly comparable
Gert Labs
Not directly comparable
SWE-bench Verified
Claude Opus 4.7 (Adaptive) leads this result
SWE-bench Pro
Not directly comparable
Terminal-Bench 2.0
Claude Opus 4.7 (Adaptive) leads this result
GPQA
Claude Opus 4.7 (Adaptive) leads this result
GPQA-D
Claude Opus 4.7 (Adaptive) leads this result
HLE
Not directly comparable
HLE w/o tools
Not directly comparable
FrontierMath (legacy)
Not directly comparable
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Last updated September 23, 2026