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BenchLM
Data

Claude Opus 5.5 vs Sage-A1.5

Updated October 20, 2026. Rank says Claude Opus 5.5 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 5.5 has the higher public point estimate, 86.68 versus 62.95. Their conditional score ranges do not overlap. These ranges do not establish rank confidence. 3 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 logo
Claude Opus 5.5

Anthropic

86.68/100

Supported · Public rank #1

90% interval 81.8–91.6

Model B
InternScience logo
Sage-A1.5

InternScience

62.95/100

Estimated · Public rank #44

Conditional range 48.6–77.3

Shared results
3
Claude Opus 5.5 only
60
Sage-A1.5 only
9
Like-for-like categories
0 / 8
Supported: Claude Opus 5.5 · Estimated: Sage-A1.5. 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.

  • Long documents

    Prompts that approach the documented context limit

    Claude Opus 5.5

    Claude Opus 5.5 has the larger documented context window.

    Confidence: documented
Show secondary and unsupported calls

  • Coding work

    Code generation, repair, and software-engineering tasks

    Not enough matched evidence

    Sage-A1.5 is scored on Estimated evidence for coding, so the reading is directional rather than like-for-like.

    Confidence: limited

  • Agentic work

    Tool use, computer use, and multi-step task completion

    Not enough matched evidence

    Sage-A1.5 is scored on Estimated evidence for agentic, so the reading is directional rather than like-for-like.

    Confidence: limited

  • Chat turn cost

    1K fresh input + 500 output tokens

    Not enough matched evidence

    A complete comparable API-rate estimate is not available for both models.

    Confidence: listed-rates

  • Cache-heavy agent loop cost

    200K cached + 20K fresh input + 10K output tokens

    Not enough matched evidence

    A complete comparable API-rate estimate is not available for both models.

    Confidence: listed-rates

  • Repository review cost

    50K fresh input + 3K output tokens

    Not enough matched evidence

    A complete comparable API-rate estimate is not available for both models.

    Confidence: listed-rates

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.

82.7Claude Opus 5.554.0Sage-A1.5

Directional only · BenchAlign v5.8

Claude Opus 5.5 has the higher coding point estimate. Conditional score ranges do not establish rank confidence.

Coding scores combine specific tasks and setups. Match the editor, harness, and effort to your workflow.

Open the coding leaderboardShortlist models for this job
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.

2 categories rest 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.

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 5.5
90.4
Supported · #1/132
Sage-A1.5
57.7
Estimated · #36/132
Basis
BenchAlign v5.8 lane · 15 vs 6 public rows
Reading
Directional only

Coding

Directional only
Claude Opus 5.5
82.7
Supported · #2/153
Sage-A1.5
54.0
Estimated · #34/153
Basis
BenchAlign v5.8 lane · 11 vs 3 public rows
Reading
Directional only

Reasoning

Not comparable
Claude Opus 5.5
86.1
#4/27
Sage-A1.5
80.6
Unranked · 2 rankable rows
Basis
Provisional lane · 1 vs 0 weighted rows
Reading
Not comparable

Multimodal

Not comparable
Claude Opus 5.5
92.2
#3/55
Sage-A1.5
Not ranked
Basis
Provisional lane · 1 vs 0 weighted rows
Reading
Not comparable

Knowledge

Not comparable
Claude Opus 5.5
90.3
Supported · #1/187
Sage-A1.5
Not ranked
Basis
BenchAlign v5.8 lane · 16 vs 1 public rows
Reading
Not comparable

Multilingual

Not comparable
Claude Opus 5.5
Not ranked
Sage-A1.5
Not ranked
Basis
Provisional lane · 0 vs 0 weighted rows
Reading
Not comparable

Instruction following

Not comparable
Claude Opus 5.5
Not ranked
Sage-A1.5
91.9
#22/152
Basis
Provisional lane · 0 vs 1 weighted rows
Reading
Not comparable

Math

Not comparable
Claude Opus 5.5
97.3
Unranked · 4 rankable rows
Sage-A1.5
Not ranked
Basis
Provisional lane · 2 vs 0 weighted rows
Reading
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 5.5
$0.014
Fits in one request
Sage-A1.5
Self-hosted; infrastructure cost varies
Fits in one request

Sage-A1.5 has no comparable published API token rate.

Repository review

50K fresh input + 3K output tokens

Claude Opus 5.5
$0.26
Fits in one request
Sage-A1.5
Self-hosted; infrastructure cost varies
Fits in one request

Sage-A1.5 has no comparable published API token rate.

Cache-heavy agent loop

200K cached + 20K fresh input + 10K output tokens

Claude Opus 5.5
$0.32
Fits in one request
Sage-A1.5
Self-hosted; infrastructure cost varies
Fits in one request
Cached-input rate unavailable

Sage-A1.5 has no comparable published API token 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.

Reasoning profile

Claude Opus 5.5

Reasoning

Sage-A1.5

Reasoning

Weight access

Claude Opus 5.5

Proprietary

Sage-A1.5

Open Weight

License

Claude Opus 5.5

Proprietary

Sage-A1.5

Open Weight

Release date

Claude Opus 5.5

2026-09-22

Sage-A1.5

2026-10-15

If you already use one of these models

Deployment change
The models list different providers, so authentication, endpoint behavior, limits, and feature support may change.
Quality signal
Claude Opus 5.5 has the higher public point estimate, 86.68 versus 62.95. Their conditional score ranges do not overlap. These ranges do not establish rank confidence.
Workload cost
A complete comparable API-rate estimate is not available for both models.
Context tradeoff
Claude Opus 5.5 has the larger documented window (1M).
Run the same representative tasks against both endpoints before changing production traffic.

Questions

Which is better, Claude Opus 5.5 or Sage-A1.5?

Claude Opus 5.5 has the higher public point estimate, 86.68 versus 62.95. Their conditional score ranges do not 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 5.5 or Sage-A1.5?

Claude Opus 5.5 scores higher for coding on the public lane, 82.7 to 54. Sage-A1.5 is 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.

Which is better for agentic tasks, Claude Opus 5.5 or Sage-A1.5?

Claude Opus 5.5 scores higher for agentic tasks on the public lane, 90.4 to 57.7. Sage-A1.5 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 5.5 or Sage-A1.5?

Both models do not have comparable published API token rates, so this page does not name a universal price winner.

Which has the larger context window, Claude Opus 5.5 or Sage-A1.5?

Claude Opus 5.5 has the larger documented context window: 1M, compared with 262K.

Self-host vs API cost

Estimates at 50,000 req/day · 1000 tokens/req average.

Claude Opus 5.5
API / mo$18,000
Self-host / moNot listed
Break-even—
Proprietary model — self-hosting not applicable.
Sage-A1.5
API / mo$0
Self-host / mo$298
Break-even—
Model the full break-even

Benchmark evidence

The full public result ledger is available for audit without forcing a wide desktop table onto a phone.

Browse raw public benchmark evidence72 rows

Agentic

  • Terminal-Bench 4.0

    Claude Opus 5.566.40%
    Source
    Sage-A1.5—

    Not directly comparable

  • Terminal-Bench-Science 0.1

    Claude Opus 5.558.7%
    Source
    Sage-A1.5—

    Not directly comparable

  • AutomationBench

    Claude Opus 5.540.0%
    Source
    Sage-A1.5—

    Not directly comparable

  • HLE w/ tools

    Claude Opus 5.567.7%
    Source
    Sage-A1.555.1%
    Source

    Claude Opus 5.5 leads this result

  • OSWorld 2.0

    Claude Opus 5.548.7%
    Source
    Sage-A1.5—

    Not directly comparable

  • LAB all-pass (Harvey held-out)

    Claude Opus 5.58.3%
    Source
    Sage-A1.5—

    Not directly comparable

  • LAB criterion-pass (Harvey held-out)

    Claude Opus 5.591.2%
    Source
    Sage-A1.5—

    Not directly comparable

  • Toolathlon-Verified

    Claude Opus 5.577.8%
    Source
    Sage-A1.5—

    Not directly comparable

  • Toolathlon Verified Pass@3

    Claude Opus 5.582.4%
    Source
    Sage-A1.5—

    Not directly comparable

  • Toolathlon Verified Pass³

    Claude Opus 5.572.2%
    Source
    Sage-A1.5—

    Not directly comparable

  • Toolathlon Verified avg. turns

    Claude Opus 5.526.9 turns
    Source
    Sage-A1.5—

    Not directly comparable

  • CWE-bench v1

    Claude Opus 5.567.0%
    Source
    Sage-A1.5—

    Not directly comparable

  • Hermes Index

    Claude Opus 5.563.3%
    Source
    Sage-A1.5—

    Not directly comparable

  • Hermes Bench

    Claude Opus 5.576.7%
    Source
    Sage-A1.5—

    Not directly comparable

  • MazeBench

    Claude Opus 5.513%
    Source
    Sage-A1.5—

    Not directly comparable

  • GAIA

    Claude Opus 5.5—
    Sage-A1.595.1%
    Source

    Not directly comparable

  • BrowseComp

    Claude Opus 5.5—
    Sage-A1.581.7%
    Source

    Not directly comparable

  • MLE-Bench Lite

    Claude Opus 5.5—
    Sage-A1.565.2%
    Source

    Not directly comparable

  • VITA-Bench

    Claude Opus 5.5—
    Sage-A1.545.4%
    Source

    Not directly comparable

  • PinchBench

    Claude Opus 5.5—
    Sage-A1.590.0%
    Source

    Not directly comparable

Coding

  • FrontierCode 1.1 Main

    Claude Opus 5.554.4%
    Source
    Sage-A1.5—

    Not directly comparable

  • CursorBench 4.0

    Claude Opus 5.557.8%
    Source
    Sage-A1.5—

    Not directly comparable

  • SWE-bench Pro

    Claude Opus 5.589.9%
    Source
    Sage-A1.561.2%
    Source

    Claude Opus 5.5 leads this result

  • SWE Multilingual

    Claude Opus 5.593.9%
    Source
    Sage-A1.572.7%
    Source

    Claude Opus 5.5 leads this result

  • SWE Multimodal

    Claude Opus 5.561.4%
    Source
    Sage-A1.5—

    Not directly comparable

  • DeepSWE

    Claude Opus 5.574.2%
    Source
    Sage-A1.5—

    Not directly comparable

  • FrontierCode 1.1 Extended

    Claude Opus 5.563.6%
    Source
    Sage-A1.5—

    Not directly comparable

  • FrontierSWE v2

    Claude Opus 5.562.3%
    Source
    Sage-A1.5—

    Not directly comparable

  • ProgramBench

    Claude Opus 5.591.2%
    Source
    Sage-A1.5—

    Not directly comparable

  • PostTrainBench v1.1

    Claude Opus 5.549.3%
    Source
    Sage-A1.5—

    Not directly comparable

  • Bug Hunt Bench

    Claude Opus 5.541.7 fixes
    Source
    Sage-A1.5—

    Not directly comparable

  • SciCode

    Claude Opus 5.5—
    Sage-A1.544.3%
    Source

    Not directly comparable

Reasoning

  • STEMBench

    Claude Opus 5.52.62
    Source
    Sage-A1.5—

    Not directly comparable

  • ARC-AGI-1

    Claude Opus 5.597.50%
    Source
    Sage-A1.5—

    Not directly comparable

  • ARC-AGI-2

    Claude Opus 5.591.7%
    Source
    Sage-A1.5—

    Not directly comparable

  • GraphWalks BFS 256K–1M

    Claude Opus 5.566.8%
    Source
    Sage-A1.5—

    Not directly comparable

  • CritPt

    Claude Opus 5.5—
    Sage-A1.520.0%
    Source

    Not directly comparable

Multimodal

  • ExtractBench Pro

    Claude Opus 5.551%
    Source
    Sage-A1.5—

    Not directly comparable

  • ExtractBench (LlamaIndex)

    Claude Opus 5.586.06%
    Source
    Sage-A1.5—

    Not directly comparable

  • ParseBench

    Claude Opus 5.579.85%
    Source
    Sage-A1.5—

    Not directly comparable

  • Chartography (tools)

    Claude Opus 5.589.0%
    Source
    Sage-A1.5—

    Not directly comparable

  • Chartography (no tools)

    Claude Opus 5.564.4%
    Source
    Sage-A1.5—

    Not directly comparable

  • BenchCAD Vision2Code (no tools)

    Claude Opus 5.50.730
    Source
    Sage-A1.5—

    Not directly comparable

  • BenchCAD Vision2Code (tools)

    Claude Opus 5.50.962
    Source
    Sage-A1.5—

    Not directly comparable

  • Biomedical image analysis

    Claude Opus 5.571.4%
    Source
    Sage-A1.5—

    Not directly comparable

  • OfficeQA

    Claude Opus 5.578.9%
    Source
    Sage-A1.5—

    Not directly comparable

  • OfficeQA Pro

    Claude Opus 5.567.7%
    Source
    Sage-A1.5—

    Not directly comparable

Knowledge

  • HLE w/o tools

    Claude Opus 5.564.4%
    Source
    Sage-A1.5—

    Not directly comparable

  • HealthBench (raw)

    Claude Opus 5.568.1%
    Source
    Sage-A1.5—

    Not directly comparable

  • HealthBench (length-adjusted)

    Claude Opus 5.560.6%
    Source
    Sage-A1.5—

    Not directly comparable

  • HealthBench Professional

    Claude Opus 5.565.6%
    Source
    Sage-A1.5—

    Not directly comparable

  • HealthBench Professional (raw)

    Claude Opus 5.577.1%
    Source
    Sage-A1.5—

    Not directly comparable

  • BioMysteryBench (human-solvable)

    Claude Opus 5.589.3%
    Source
    Sage-A1.5—

    Not directly comparable

  • BioMysteryBench (human-difficult)

    Claude Opus 5.550.0%
    Source
    Sage-A1.5—

    Not directly comparable

  • SpatialBench Verified

    Claude Opus 5.572.0%
    Source
    Sage-A1.5—

    Not directly comparable

  • SingleCellBench

    Claude Opus 5.561.2%
    Source
    Sage-A1.5—

    Not directly comparable

  • Morphology-to-molecule matching

    Claude Opus 5.534.0%
    Source
    Sage-A1.5—

    Not directly comparable

  • Medicinal chemistry

    Claude Opus 5.563.5%
    Source
    Sage-A1.5—

    Not directly comparable

  • Protein Design

    Claude Opus 5.560.2%
    Source
    Sage-A1.5—

    Not directly comparable

  • Protein Design library ranking

    Claude Opus 5.556.0%
    Source
    Sage-A1.5—

    Not directly comparable

  • De novo protein-binder design

    Claude Opus 5.582.6%
    Source
    Sage-A1.5—

    Not directly comparable

  • Protocols (troubleshooting)

    Claude Opus 5.573.7%
    Source
    Sage-A1.5—

    Not directly comparable

  • Protocols (understanding)

    Claude Opus 5.569.0%
    Source
    Sage-A1.5—

    Not directly comparable

  • FrontierScience Research

    Claude Opus 5.5—
    Sage-A1.548.3%
    Source

    Not directly comparable

Multilingual

  • GMMLU

    Claude Opus 5.594.3%
    Source
    Sage-A1.5—

    Not directly comparable

  • MILU

    Claude Opus 5.593.1%
    Source
    Sage-A1.5—

    Not directly comparable

Instruction following

  • Gray Swan IPI (15 attempts)

    Claude Opus 5.51.0%
    Source
    Sage-A1.5—

    Not directly comparable

  • IFBench

    Claude Opus 5.5—
    Sage-A1.581.6%
    Source

    Not directly comparable

Math

  • ArXivMath Aug. 2026 (no tools)

    Claude Opus 5.591.2%
    Source
    Sage-A1.5—

    Not directly comparable

  • ArXivMath Aug. 2026 (tools)

    Claude Opus 5.596.9%
    Source
    Sage-A1.5—

    Not directly comparable

  • FrontierMath v2 (Tiers 1-3)

    Claude Opus 5.591.228%
    Source
    Sage-A1.5—

    Not directly comparable

  • FrontierMath v2 (Tier 4)

    Claude Opus 5.595.000%
    Source
    Sage-A1.5—

    Not directly comparable

72 public results · 3 shared

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Last updated October 20, 2026