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BenchLM
Model A
Claude Opus 4.6 (Adaptive)

Anthropic

64.7/100

Estimated · Public rank #38

90% interval 53.2–76.2

Claude Opus 4.6 (Adaptive) vs dots3-note Preview

Updated August 14, 2026. Public scores include evidence status and uncertainty. They are not guarantees for a specific workload.

Model B
dots3-note Preview

Dots Studio

—

Evidence status unavailable

90% interval unavailable

Decision reading

The public evidence has no benchmark result shared by both models, so it does not support a quality verdict. Use the documented cost, context, and runtime rows instead.

0 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 4.6 (Adaptive)

    Claude Opus 4.6 (Adaptive) 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

    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

  • 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

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
0
Claude Opus 4.6 (Adaptive) only
1
dots3-note Preview only
31
Like-for-like categories
0 / 8

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

Not comparable
Claude Opus 4.6 (Adaptive)
Not measured
dots3-note Preview
83.3
Weighted basis
0 vs 1 rows
Reading
Not comparable

Coding

Not comparable
Claude Opus 4.6 (Adaptive)
Not measured
dots3-note Preview
71.7
Weighted basis
0 vs 2 rows
Reading
Not comparable

Reasoning

Not comparable
Claude Opus 4.6 (Adaptive)
Not measured
dots3-note Preview
81.4
Weighted basis
0 vs 1 rows
Reading
Not comparable

Knowledge

Not comparable
Claude Opus 4.6 (Adaptive)
Not measured
dots3-note Preview
52.6
Weighted basis
0 vs 1 rows
Reading
Not comparable

Math

Not comparable
Claude Opus 4.6 (Adaptive)
Not measured
dots3-note Preview
Not measured
Weighted basis
0 vs 0 rows
Reading
Not comparable

Multilingual

Not comparable
Claude Opus 4.6 (Adaptive)
Not measured
dots3-note Preview
Not measured
Weighted basis
0 vs 0 rows
Reading
Not comparable

Multimodal

Not comparable
Claude Opus 4.6 (Adaptive)
Not measured
dots3-note Preview
79.1
Weighted basis
0 vs 1 rows
Reading
Not comparable

Instruction following

Not comparable
Claude Opus 4.6 (Adaptive)
Not measured
dots3-note Preview
85.1
Weighted basis
0 vs 2 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.

A shared-evidence shape is not available.

BenchLM does not draw a radar or infer missing axes when the matched evidence is too sparse.

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 4.6 (Adaptive)
API rate not published
Fits in one request
dots3-note Preview
Self-hosted; infrastructure cost varies
Fits in one request

Claude Opus 4.6 (Adaptive) has no comparable published API token rate. dots3-note Preview has no comparable published API token rate.

Repository review

50K fresh input + 3K output tokens

Claude Opus 4.6 (Adaptive)
API rate not published
Fits in one request
dots3-note Preview
Self-hosted; infrastructure cost varies
Fits in one request

Claude Opus 4.6 (Adaptive) has no comparable published API token rate. dots3-note Preview has no comparable published API token rate.

Cache-heavy agent loop

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

Claude Opus 4.6 (Adaptive)
API rate not published
Fits in one request
Cached-input rate unavailable
dots3-note Preview
Self-hosted; infrastructure cost varies
Fits in one request
Cached-input rate unavailable

Claude Opus 4.6 (Adaptive) has no comparable published API token rate. dots3-note Preview has no comparable published API token rate.

Specification differences

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

Cached-input rate

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

Claude Opus 4.6 (Adaptive)

No comparable hosted API rate

dots3-note Preview

No comparable hosted API rate

dots3-note Preview model card

Provider availability

Claude Opus 4.6 (Adaptive)

Generally Available · Claude API

Anthropic model overview

dots3-note Preview

Not sourced

Reasoning profile

Claude Opus 4.6 (Adaptive)

Reasoning

dots3-note Preview

Reasoning

Weight access

Claude Opus 4.6 (Adaptive)

Proprietary

dots3-note Preview

Open Weight

License

Claude Opus 4.6 (Adaptive)

Proprietary

dots3-note Preview

Open Weight

Release date

Claude Opus 4.6 (Adaptive)

2026-02-01

dots3-note Preview

2026-08-14

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
The public evidence has no benchmark result shared by both models, so it does not support a quality verdict.
Workload cost
A complete comparable API-rate estimate is not available for both models.
Context tradeoff
Claude Opus 4.6 (Adaptive) 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 evidence32 rows

Agentic

  • Claw-Eval

    Claude Opus 4.6 (Adaptive)—
    dots3-note Preview73.4%
    Source

    Not directly comparable

  • Terminal-Bench 2.1

    Claude Opus 4.6 (Adaptive)—
    dots3-note Preview75.1%
    Source

    Not directly comparable

  • Toolathlon-Verified

    Claude Opus 4.6 (Adaptive)—
    dots3-note Preview55.6%
    Source

    Not directly comparable

  • skillsBench

    Claude Opus 4.6 (Adaptive)—
    dots3-note Preview52.8%
    Source

    Not directly comparable

  • APEX-Agents

    Claude Opus 4.6 (Adaptive)—
    dots3-note Preview30.8%
    Source

    Not directly comparable

  • BrowseComp

    Claude Opus 4.6 (Adaptive)—
    dots3-note Preview83.3%
    Source

    Not directly comparable

  • HLE w/ tools

    Claude Opus 4.6 (Adaptive)—
    dots3-note Preview52.6%
    Source

    Not directly comparable

  • DeepSearchQA

    Claude Opus 4.6 (Adaptive)—
    dots3-note Preview92.1%
    Source

    Not directly comparable

  • WideResearch

    Claude Opus 4.6 (Adaptive)—
    dots3-note Preview78.9%
    Source

    Not directly comparable

Coding

  • Vibe Code Bench

    Claude Opus 4.6 (Adaptive)53.50%
    Source
    dots3-note Preview—

    Not directly comparable

  • Codeforces

    Claude Opus 4.6 (Adaptive)—
    dots3-note Preview3056.0
    Source

    Not directly comparable

  • LiveCodeBench v6

    Claude Opus 4.6 (Adaptive)—
    dots3-note Preview91.5%
    Source

    Not directly comparable

  • Terminal-Bench 2.1

    Claude Opus 4.6 (Adaptive)—
    dots3-note Preview75.1%
    Source

    Not directly comparable

  • SWE-bench Verified

    Claude Opus 4.6 (Adaptive)—
    dots3-note Preview78.4%
    Source

    Not directly comparable

  • SWE Multilingual

    Claude Opus 4.6 (Adaptive)—
    dots3-note Preview75.7%
    Source

    Not directly comparable

  • SWE-bench Pro

    Claude Opus 4.6 (Adaptive)—
    dots3-note Preview61%
    Source

    Not directly comparable

  • NL2Repo

    Claude Opus 4.6 (Adaptive)—
    dots3-note Preview49.8%
    Source

    Not directly comparable

Reasoning

  • ARC-AGI-2

    Claude Opus 4.6 (Adaptive)—
    dots3-note Preview81.4%
    Source

    Not directly comparable

Knowledge

  • HLE

    Claude Opus 4.6 (Adaptive)—
    dots3-note Preview52.6%
    Source

    Not directly comparable

Math

  • IMOAnswerBench

    Claude Opus 4.6 (Adaptive)—
    dots3-note Preview90.9%
    Source

    Not directly comparable

Multimodal

  • SimpleVQA

    Claude Opus 4.6 (Adaptive)—
    dots3-note Preview72.5%
    Source

    Not directly comparable

  • MMMU-Pro

    Claude Opus 4.6 (Adaptive)—
    dots3-note Preview79.1%
    Source

    Not directly comparable

  • MathVision

    Claude Opus 4.6 (Adaptive)—
    dots3-note Preview87.7%
    Source

    Not directly comparable

  • ZeroBench

    Claude Opus 4.6 (Adaptive)—
    dots3-note Preview19.0%
    Source

    Not directly comparable

  • CharXiv w/o tools

    Claude Opus 4.6 (Adaptive)—
    dots3-note Preview83.1%
    Source

    Not directly comparable

  • GDP.pdf (no tools)

    Claude Opus 4.6 (Adaptive)—
    dots3-note Preview60.7%
    Source

    Not directly comparable

  • PerceptionBench

    Claude Opus 4.6 (Adaptive)—
    dots3-note Preview53.4%
    Source

    Not directly comparable

  • BabyVision

    Claude Opus 4.6 (Adaptive)—
    dots3-note Preview50.0%
    Source

    Not directly comparable

  • MMVU

    Claude Opus 4.6 (Adaptive)—
    dots3-note Preview79.9%
    Source

    Not directly comparable

  • VideoMMMU

    Claude Opus 4.6 (Adaptive)—
    dots3-note Preview86.8%
    Source

    Not directly comparable

Instruction following

  • IFBench

    Claude Opus 4.6 (Adaptive)—
    dots3-note Preview80.4%
    Source

    Not directly comparable

  • IFEval

    Claude Opus 4.6 (Adaptive)—
    dots3-note Preview93.9%
    Source

    Not directly comparable

Frequently asked questions

Which is better, Claude Opus 4.6 (Adaptive) or dots3-note Preview?

The public evidence has no benchmark result shared by both models, so it does not support a quality verdict. The page therefore keeps the decision tied to the specific documented workload.

Which is better for coding, Claude Opus 4.6 (Adaptive) or dots3-note Preview?

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 4.6 (Adaptive) or dots3-note Preview?

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 4.6 (Adaptive) or dots3-note Preview?

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 4.6 (Adaptive) or dots3-note Preview?

Claude Opus 4.6 (Adaptive) has the larger documented context window: 1M, compared with 512K.

Related comparisons

Compare API pricing Read the methodology Open the model selector

Last updated August 14, 2026

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