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BenchLM
Anthropic logo
Model A
Claude Opus 4.8

Anthropic

76.45/100

Supported · Public rank #8

90% interval 73.8–79.1

Claude Opus 4.8 vs o1-pro

Updated August 26, 2026. Public scores include evidence status and uncertainty. They are not guarantees for a specific workload.

OpenAI logo
Model B
o1-pro

OpenAI

46.14/100

Estimated · Public rank #161

90% interval 34.6–57.7

Decision reading

Claude Opus 4.8 has the higher public score, 76.45 versus 46.14, and the 90% score intervals do not overlap.

1 results are shared. Category rows based on different benchmark sets are marked directional and do not name a winner.

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 4.8

    Claude Opus 4.8 has the larger documented context window.

    Confidence: documented

  • Chat turn cost

    1K fresh input + 500 output tokens

    Claude Opus 4.8

    Claude Opus 4.8 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 Opus 4.8

    Claude Opus 4.8 has the lower estimated token cost for this stated workload. Costs use the listed standard API rates.

    Confidence: listed-rates

  • Coding work

    Code generation, repair, and software-engineering tasks

    Not enough matched evidence

    No shared weighted benchmark basis supports a winner.

    Confidence: limited

  • Agentic work

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

    Not enough matched evidence

    No shared weighted benchmark basis supports a winner.

    Confidence: limited

  • Cache-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. o1-pro does not fit this workload in one request. Claude Opus 4.8 has no published cached-input rate, so cached tokens use its listed input rate. o1-pro has no published cached-input rate, so cached tokens use its listed input rate.

    Confidence: rate-fallback

What is actually comparable

Shared results can support a head-to-head reading. Results present for only one model describe coverage, not superiority.

Shared results
1
Claude Opus 4.8 only
32
o1-pro only
0
Like-for-like categories
0 / 8

1 category uses different evidence sets. Those rows remain visible for coverage context but do not name a winner.

Category results, on a stated basis

Each row states whether both averages use the same weighted benchmark set. Directional and not-comparable rows remain visible, but they never receive a winner in this template.

Knowledge

Directional only
Claude Opus 4.8
62.7
o1-pro
79.0
Weighted basis
2 vs 1 rows
Reading
Directional only

Agentic

Not comparable
Claude Opus 4.8
80.3
o1-pro
Not measured
Weighted basis
3 vs 0 rows
Reading
Not comparable

Coding

Not comparable
Claude Opus 4.8
81.1
o1-pro
Not measured
Weighted basis
2 vs 0 rows
Reading
Not comparable

Reasoning

Not comparable
Claude Opus 4.8
72.1
o1-pro
Not measured
Weighted basis
1 vs 0 rows
Reading
Not comparable

Math

Not comparable
Claude Opus 4.8
53.9
o1-pro
Not measured
Weighted basis
3 vs 0 rows
Reading
Not comparable

Multilingual

Not comparable
Claude Opus 4.8
Not measured
o1-pro
Not measured
Weighted basis
0 vs 0 rows
Reading
Not comparable

Multimodal

Not comparable
Claude Opus 4.8
77.0
o1-pro
Not measured
Weighted basis
2 vs 0 rows
Reading
Not comparable

Instruction following

Not comparable
Claude Opus 4.8
Not measured
o1-pro
Not measured
Weighted basis
0 vs 0 rows
Reading
Not comparable

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.

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 4.8
$0.0175
Fits in one request
o1-pro
$0.45
Fits in one request

Claude Opus 4.8 has the lower modeled cost

Costs use the listed standard API rates.

Repository review

50K fresh input + 3K output tokens

Claude Opus 4.8
$0.325
Fits in one request
o1-pro
$9.30
Fits in one request

Claude Opus 4.8 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 4.8
$1.35
Fits in one request
Cached input priced at the published list-input rate
o1-pro
$39.00
Does not fit in one request
Cached input priced at the published list-input rate

o1-pro does not fit this workload in one request. Claude Opus 4.8 has no published cached-input rate, so cached tokens use its listed input rate. o1-pro has no published cached-input rate, so cached tokens use its listed input rate.

Specification differences

Sourced differences are shown directly. Missing facts stay explicit instead of being inferred from a model name or family.

Context window

Maximum documented context; output-token limits may be lower.

Claude Opus 4.8

1M

Anthropic model overview

o1-pro

200K

Cached-input rate

A missing cached-input rate falls back to the listed input rate only in the stated workload estimate.

Claude Opus 4.8

Not published

o1-pro

Not published

Reasoning profile

Claude Opus 4.8

Reasoning

o1-pro

Reasoning

Weight access

Claude Opus 4.8

Proprietary

o1-pro

Proprietary

License

Claude Opus 4.8

Proprietary

o1-pro

Proprietary

Release date

Claude Opus 4.8

2026-05-28

o1-pro

2024-12-01

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 4.8 has the higher public score, 76.45 versus 46.14, and the 90% score intervals do not overlap.
Workload cost
Repository review: $0.325 vs $9.30. Cache-heavy agent loop: $1.35 vs $39.00.
Context tradeoff
Claude Opus 4.8 has the larger documented window (1M).

Run the same representative tasks against both endpoints before changing production traffic.

Benchmark evidence

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

Browse raw public benchmark evidence33 rows

Agentic

  • Terminal-Bench 3.0

    Claude Opus 4.821.1%
    Source
    o1-pro—

    Not directly comparable

  • Terminal-Bench 2.0

    Claude Opus 4.874.6%
    Source
    o1-pro—

    Not directly comparable

  • BrowseComp

    Claude Opus 4.884.3%
    Source
    o1-pro—

    Not directly comparable

  • DeepSearchQA

    Claude Opus 4.893.1%
    Source
    o1-pro—

    Not directly comparable

  • OSWorld-Verified

    Claude Opus 4.883.4%
    Source
    o1-pro—

    Not directly comparable

  • Finance Agent v2

    Claude Opus 4.853.9%
    Source
    o1-pro—

    Not directly comparable

  • MCP Atlas

    Claude Opus 4.882.2%
    Source
    o1-pro—

    Not directly comparable

  • Toolathlon

    Claude Opus 4.859.9%
    Source
    o1-pro—

    Not directly comparable

  • Gert Labs

    Claude Opus 4.872.97%
    Source
    o1-pro—

    Not directly comparable

  • ResearchClawBench

    Claude Opus 4.821.1%
    Source
    o1-pro—

    Not directly comparable

  • OSWorld 2.0

    Claude Opus 4.820.6%
    Source
    o1-pro—

    Not directly comparable

Coding

  • SWE-bench Verified

    Claude Opus 4.888.6%
    Source
    o1-pro—

    Not directly comparable

  • SWE-bench Pro

    Claude Opus 4.869.2%
    Source
    o1-pro—

    Not directly comparable

  • SWE Multilingual

    Claude Opus 4.884.4%
    Source
    o1-pro—

    Not directly comparable

  • SWE Multimodal

    Claude Opus 4.838.4%
    Source
    o1-pro—

    Not directly comparable

  • Terminal-Bench 2.0

    Claude Opus 4.874.6%
    Source
    o1-pro—

    Not directly comparable

  • cursorBench31

    Claude Opus 4.858.4%
    Source
    o1-pro—

    Not directly comparable

  • cursorBench32

    Claude Opus 4.862.3%
    Source
    o1-pro—

    Not directly comparable

  • FrontierCode 1.1 Main

    Claude Opus 4.846.5%
    Source
    o1-pro—

    Not directly comparable

Reasoning

  • ARC-AGI-2

    Claude Opus 4.872.1%
    Source
    o1-pro—

    Not directly comparable

  • ARC-AGI-3

    Claude Opus 4.81.5%
    Source
    o1-pro—

    Not directly comparable

Knowledge

  • GPQA

    Claude Opus 4.893.6%
    Source
    o1-pro79%
    Source

    Claude Opus 4.8 leads this result

  • GPQA-D

    Claude Opus 4.893.6%
    Source
    o1-pro—

    Not directly comparable

  • HLE

    Claude Opus 4.857.9%
    Source
    o1-pro—

    Not directly comparable

  • HLE w/o tools

    Claude Opus 4.849.8%
    Source
    o1-pro—

    Not directly comparable

Math

  • USAMO 2026

    Claude Opus 4.896.7%
    Source
    o1-pro—

    Not directly comparable

  • FrontierMath v2 (Tiers 1-3)

    Claude Opus 4.847.241%
    Source
    o1-pro—

    Not directly comparable

  • FrontierMath v2 (Tier 4)

    Claude Opus 4.831.250%
    Source
    o1-pro—

    Not directly comparable

Multilingual

  • INCLUDE

    Claude Opus 4.887.6%
    Source
    o1-pro—

    Not directly comparable

Multimodal

  • OfficeQA Pro

    Claude Opus 4.866.2%
    Source
    o1-pro—

    Not directly comparable

  • ScreenSpot Pro

    Claude Opus 4.887.9%
    Source
    o1-pro—

    Not directly comparable

  • CharXiv

    Claude Opus 4.889.9%
    Source
    o1-pro—

    Not directly comparable

  • CharXiv w/o tools

    Claude Opus 4.880.5%
    Source
    o1-pro—

    Not directly comparable

Frequently asked questions

Which is better, Claude Opus 4.8 or o1-pro?

Claude Opus 4.8 has the higher public score, 76.45 versus 46.14, and the 90% score intervals do not overlap. That is the clearest overall quality signal in the current public data.

Which is better for coding, Claude Opus 4.8 or o1-pro?

The published evidence does not provide a shared weighted coding basis for both models, so BenchLM does not name a coding winner.

Which is better for agentic tasks, Claude Opus 4.8 or o1-pro?

The published evidence does not provide a shared weighted agentic tasks basis for both models, so BenchLM does not name a agentic tasks winner.

Which costs less, Claude Opus 4.8 or o1-pro?

For the stated presets, chat costs $0.0175 on Claude Opus 4.8 and $0.45 on o1-pro; repository review costs $0.325 and $9.30; the cache-heavy agent loop costs $1.35 and $39.00. o1-pro does not fit this workload in one request. Claude Opus 4.8 has no published cached-input rate, so cached tokens use its listed input rate. o1-pro has no published cached-input rate, so cached tokens use its listed input rate.

Which has the larger context window, Claude Opus 4.8 or o1-pro?

Claude Opus 4.8 has the larger documented context window: 1M, compared with 200K.

Related comparisons

Compare API pricing Read the methodology Open the model selector

Last updated August 26, 2026

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