Skip to main content
Radar

Five or fewer confirmed AI changes, with original sources, on mornings when something changed.A free source-linked morning brief.

Start the free Radar Brief
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 Claude Sonnet 4.6

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

Anthropic logo
Model B
Claude Sonnet 4.6

Anthropic

64.62/100

Supported · Public rank #41

90% interval 51.6–77.7

Decision reading

Claude Opus 4.8 has the higher public score estimate, 76.45 versus 64.62, but the 90% score intervals overlap. Treat that as a lead, not a settled winner.

12 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 Sonnet 4.6

    Claude Sonnet 4.6 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 4.6

    Claude Sonnet 4.6 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

    The category averages use different weighted benchmark sets, so they are directional rather than like-for-like.

    Confidence: limited

  • Agentic work

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

    Not enough matched evidence

    The category averages use different weighted benchmark sets, so they are directional rather than like-for-like.

    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. Claude Sonnet 4.6 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. Claude Sonnet 4.6 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
12
Claude Opus 4.8 only
21
Claude Sonnet 4.6 only
8
Like-for-like categories
0 / 8

5 categories use 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.

Agentic

Directional only
Claude Opus 4.8
80.3
Claude Sonnet 4.6
65.2
Weighted basis
3 vs 2 rows
Reading
Directional only

Coding

Directional only
Claude Opus 4.8
81.1
Claude Sonnet 4.6
69.1
Weighted basis
2 vs 2 rows
Reading
Directional only

Knowledge

Directional only
Claude Opus 4.8
62.7
Claude Sonnet 4.6
66.0
Weighted basis
2 vs 4 rows
Reading
Directional only

Math

Directional only
Claude Opus 4.8
53.9
Claude Sonnet 4.6
26.4
Weighted basis
3 vs 2 rows
Reading
Directional only

Multimodal

Directional only
Claude Opus 4.8
77.0
Claude Sonnet 4.6
77.4
Weighted basis
2 vs 1 rows
Reading
Directional only

Reasoning

Not comparable
Claude Opus 4.8
72.1
Claude Sonnet 4.6
Not measured
Weighted basis
1 vs 0 rows
Reading
Not comparable

Multilingual

Not comparable
Claude Opus 4.8
Not measured
Claude Sonnet 4.6
Not measured
Weighted basis
0 vs 0 rows
Reading
Not comparable

Instruction following

Not comparable
Claude Opus 4.8
Not measured
Claude Sonnet 4.6
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
Claude Sonnet 4.6
$0.0105
Fits in one request

Claude Sonnet 4.6 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
Claude Sonnet 4.6
$0.195
Fits in one request

Claude Sonnet 4.6 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
Claude Sonnet 4.6
$0.81
Does not fit in one request
Cached input priced at the published list-input rate

Claude Sonnet 4.6 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. Claude Sonnet 4.6 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

Claude Sonnet 4.6

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

Claude Sonnet 4.6

Not published

Provider availability

Claude Opus 4.8

Generally Available · Claude API

Anthropic model overview

Claude Sonnet 4.6

Not sourced

Reasoning profile

Claude Opus 4.8

Reasoning

Claude Sonnet 4.6

Non-Reasoning

Weight access

Claude Opus 4.8

Proprietary

Claude Sonnet 4.6

Proprietary

License

Claude Opus 4.8

Proprietary

Claude Sonnet 4.6

Proprietary

Release date

Claude Opus 4.8

2026-05-28

Claude Sonnet 4.6

2026-02-01

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 4.8 has the higher public score estimate, 76.45 versus 64.62, but the 90% score intervals overlap.
Workload cost
Repository review: $0.325 vs $0.195. Cache-heavy agent loop: $1.35 vs $0.81.
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 evidence41 rows

Agentic

  • Terminal-Bench 3.0

    Claude Opus 4.821.1%
    Source
    Claude Sonnet 4.6

    Not directly comparable

  • Terminal-Bench 2.0

    Claude Opus 4.874.6%
    Source
    Claude Sonnet 4.659.1%
    Source

    Claude Opus 4.8 leads this result

  • BrowseComp

    Claude Opus 4.884.3%
    Source
    Claude Sonnet 4.6

    Not directly comparable

  • DeepSearchQA

    Claude Opus 4.893.1%
    Source
    Claude Sonnet 4.6

    Not directly comparable

  • OSWorld-Verified

    Claude Opus 4.883.4%
    Source
    Claude Sonnet 4.672.1%
    Source

    Claude Opus 4.8 leads this result

  • Finance Agent v2

    Claude Opus 4.853.9%
    Source
    Claude Sonnet 4.6

    Not directly comparable

  • MCP Atlas

    Claude Opus 4.882.2%
    Source
    Claude Sonnet 4.6

    Not directly comparable

  • Toolathlon

    Claude Opus 4.859.9%
    Source
    Claude Sonnet 4.6

    Not directly comparable

  • Claude Opus 4.872.97%
    Claude Sonnet 4.662.92%

    Claude Opus 4.8 leads this result

  • ResearchClawBench

    Claude Opus 4.821.1%
    Source
    Claude Sonnet 4.6

    Not directly comparable

  • OSWorld 2.0

    Shared source
    Claude Opus 4.820.6%
    Claude Sonnet 4.68.3%

    Claude Opus 4.8 leads this result

  • Claw-Eval

    Claude Opus 4.8
    Claude Sonnet 4.667.8%
    Source

    Not directly comparable

  • CyberGym

    Claude Opus 4.8
    Claude Sonnet 4.665.2%
    Source

    Not directly comparable

  • JobBench

    Claude Opus 4.8
    Claude Sonnet 4.636.9%
    Source

    Not directly comparable

Coding

  • SWE-bench Verified

    Claude Opus 4.888.6%
    Source
    Claude Sonnet 4.679.6%
    Source

    Claude Opus 4.8 leads this result

  • SWE-bench Pro

    Claude Opus 4.869.2%
    Source
    Claude Sonnet 4.6

    Not directly comparable

  • SWE Multilingual

    Claude Opus 4.884.4%
    Source
    Claude Sonnet 4.6

    Not directly comparable

  • SWE Multimodal

    Claude Opus 4.838.4%
    Source
    Claude Sonnet 4.6

    Not directly comparable

  • Terminal-Bench 2.0

    Claude Opus 4.874.6%
    Source
    Claude Sonnet 4.6

    Not directly comparable

  • cursorBench31

    Shared source
    Claude Opus 4.858.4%
    Claude Sonnet 4.648.8%

    Claude Opus 4.8 leads this result

  • cursorBench32

    Claude Opus 4.862.3%
    Source
    Claude Sonnet 4.6

    Not directly comparable

  • FrontierCode 1.1 Main

    Shared source
    Claude Opus 4.846.5%
    Claude Sonnet 4.624.3%

    Claude Opus 4.8 leads this result

  • SWE-Rebench

    Claude Opus 4.8
    Claude Sonnet 4.660.7%
    Source

    Not directly comparable

  • React Native Evals

    Claude Opus 4.8
    Claude Sonnet 4.680.6%
    Source

    Not directly comparable

  • Vibe Code Bench

    Claude Opus 4.8
    Claude Sonnet 4.651.48%
    Source

    Not directly comparable

Reasoning

  • ARC-AGI-2

    Claude Opus 4.872.1%
    Source
    Claude Sonnet 4.6

    Not directly comparable

  • ARC-AGI-3

    Claude Opus 4.81.5%
    Source
    Claude Sonnet 4.6

    Not directly comparable

Knowledge

  • GPQA

    Claude Opus 4.893.6%
    Source
    Claude Sonnet 4.689.9%
    Source

    Claude Opus 4.8 leads this result

  • GPQA-D

    Claude Opus 4.893.6%
    Source
    Claude Sonnet 4.6

    Not directly comparable

  • HLE

    Claude Opus 4.857.9%
    Source
    Claude Sonnet 4.649%
    Source

    Claude Opus 4.8 leads this result

  • HLE w/o tools

    Claude Opus 4.849.8%
    Source
    Claude Sonnet 4.6

    Not directly comparable

  • SuperGPQA

    Claude Opus 4.8
    Claude Sonnet 4.695%
    Source

    Not directly comparable

  • MMLU-Pro

    Claude Opus 4.8
    Claude Sonnet 4.679.2%
    Source

    Not directly comparable

Math

  • USAMO 2026

    Claude Opus 4.896.7%
    Source
    Claude Sonnet 4.6

    Not directly comparable

  • FrontierMath v2 (Tiers 1-3)

    Shared source
    Claude Opus 4.847.241%
    Claude Sonnet 4.632.400%

    Claude Opus 4.8 leads this result

  • FrontierMath v2 (Tier 4)

    Shared source
    Claude Opus 4.831.250%
    Claude Sonnet 4.68.300%

    Claude Opus 4.8 leads this result

Multilingual

  • INCLUDE

    Claude Opus 4.887.6%
    Source
    Claude Sonnet 4.6

    Not directly comparable

Multimodal

  • OfficeQA Pro

    Claude Opus 4.866.2%
    Source
    Claude Sonnet 4.6

    Not directly comparable

  • ScreenSpot Pro

    Claude Opus 4.887.9%
    Source
    Claude Sonnet 4.6

    Not directly comparable

  • CharXiv

    Claude Opus 4.889.9%
    Source
    Claude Sonnet 4.677.4%
    Source

    Claude Opus 4.8 leads this result

  • CharXiv w/o tools

    Claude Opus 4.880.5%
    Source
    Claude Sonnet 4.6

    Not directly comparable

Frequently asked questions

Which is better, Claude Opus 4.8 or Claude Sonnet 4.6?

Claude Opus 4.8 has the higher public score estimate, 76.45 versus 64.62, but the 90% score intervals overlap. The higher estimate is not a decisive winner because the uncertainty ranges overlap.

Which is better for coding, Claude Opus 4.8 or Claude Sonnet 4.6?

The current coding averages use different weighted benchmark sets, so BenchLM does not name a winner from them. Read the shared benchmark rows directly and test the models on the same task set.

Which is better for agentic tasks, Claude Opus 4.8 or Claude Sonnet 4.6?

The current agentic tasks averages use different weighted benchmark sets, so BenchLM does not name a winner from them. Read the shared benchmark rows directly and test the models on the same task set.

Which costs less, Claude Opus 4.8 or Claude Sonnet 4.6?

For the stated presets, chat costs $0.0175 on Claude Opus 4.8 and $0.0105 on Claude Sonnet 4.6; repository review costs $0.325 and $0.195; the cache-heavy agent loop costs $1.35 and $0.81. Claude Sonnet 4.6 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. Claude Sonnet 4.6 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 Claude Sonnet 4.6?

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

Related comparisons

Last updated August 26, 2026

Watch Claude Opus 4.8 vs Claude Sonnet 4.6

One weekly email when material rank, price, or benchmark evidence changes make this matchup worth revisiting.

Read a sample issue

Join 2,000+ readers.