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Anthropic logo
Model A
Claude Opus 4.6

Anthropic

69.84/100

Supported · Public rank #24

90% interval 60.579.2

Claude Opus 4.6 vs Trinity-Large-Preview

Updated September 4, 2026. Public scores include evidence status and uncertainty. They are not guarantees for a specific workload.

Arcee AI logo
Model B
Trinity-Large-Preview

Arcee AI

55.39/100

Estimated · Public rank #105

90% interval 43.966.9

Decision reading

Claude Opus 4.6 has the higher public score estimate, 69.84 versus 55.39, but the 90% score intervals overlap. Treat that as a lead, not a settled winner.

3 results are shared. Category rows resting on Estimated evidence or different benchmark sets are marked directional and do not name a winner.

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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

    Claude Opus 4.6 has the larger documented context window.

    Confidence: documented

  • Chat turn cost

    1K fresh input + 500 output tokens

    Trinity-Large-Preview

    Trinity-Large-Preview has the lower estimated token cost for this stated workload. Costs use the listed standard API rates.

    Confidence: listed-rates

  • Cache-heavy agent loop cost

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

    Trinity-Large-Preview

    Trinity-Large-Preview has the lower estimated token cost for this stated workload. Claude Opus 4.6 has no published cached-input rate, so cached tokens use its listed input rate. Trinity-Large-Preview has no published cached-input rate, so cached tokens use its listed input rate.

    Confidence: rate-fallback

Show secondary and unsupported calls
  • Repository review cost

    50K fresh input + 3K output tokens

    Trinity-Large-Preview

    Trinity-Large-Preview 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

    Trinity-Large-Preview is not ranked on the public lane for coding, so no winner is named for coding.

    Confidence: limited

  • Agentic work

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

    Not enough matched evidence

    Trinity-Large-Preview is not ranked on the public lane for agentic, so no winner is named for agentic.

    Confidence: limited

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
3
Claude Opus 4.6 only
30
Trinity-Large-Preview only
1
Like-for-like categories
0 / 8

Category results, on a stated basis

Each row shows the public-lane category score for both models: the BenchAlign 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

Not comparable
Claude Opus 4.6
54.5
Supported · #39/151
Trinity-Large-Preview
Not ranked
Basis
BenchAlign lane · 9 vs 0 public rows
Reading
Not comparable

Coding

Not comparable
Claude Opus 4.6
56.4
Supported · #40/183
Trinity-Large-Preview
Not ranked
Basis
BenchAlign lane · 8 vs 0 public rows
Reading
Not comparable

Reasoning

Not comparable
Claude Opus 4.6
65.8
Unranked · 2 rankable rows
Trinity-Large-Preview
Not ranked
Basis
Provisional lane · 0 vs 0 weighted rows
Reading
Not comparable

Knowledge

Not comparable
Claude Opus 4.6
61.7
Estimated · #33/181
Trinity-Large-Preview
Not ranked
Basis
BenchAlign lane · 9 vs 3 public rows
Reading
Not comparable

Math

Not comparable
Claude Opus 4.6
58.6
Unranked · 3 rankable rows
Trinity-Large-Preview
Not ranked
Basis
Provisional lane · 2 vs 0 weighted rows
Reading
Not comparable

Multilingual

Not comparable
Claude Opus 4.6
Not ranked
Trinity-Large-Preview
Not ranked
Basis
Provisional lane · 0 vs 0 weighted rows
Reading
Not comparable

Multimodal

Not comparable
Claude Opus 4.6
58.8
#28/48
Trinity-Large-Preview
Not ranked
Basis
Provisional lane · 1 vs 0 weighted rows
Reading
Not comparable

Instruction following

Not comparable
Claude Opus 4.6
52.3
#76/120
Trinity-Large-Preview
Not ranked
Basis
Provisional lane · 0 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) differ from the provisional-lane categories. Unranked scores sit on the lane’s scale but never name a winner. Like-for-like rows within 0.5 points read as a practical tie.

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
$0.0175
Fits in one request
Trinity-Large-Preview
$0.00075
Fits in one request

Trinity-Large-Preview has the lower modeled cost

Costs use the listed standard API rates.

Repository review

50K fresh input + 3K output tokens

Claude Opus 4.6
$0.325
Fits in one request
Trinity-Large-Preview
$0.0155
Fits in one request

Trinity-Large-Preview 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 4.6
$1.35
Fits in one request
Cached input priced at the published list-input rate
Trinity-Large-Preview
$0.065
Fits in one request
Cached input priced at the published list-input rate

Trinity-Large-Preview has the lower modeled cost

Claude Opus 4.6 has no published cached-input rate, so cached tokens use its listed input rate. Trinity-Large-Preview 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 4.6

1M

Trinity-Large-Preview

512K

API model ID

Claude Opus 4.6

Not sourced

Trinity-Large-Preview

Not sourced

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

Not published

Trinity-Large-Preview

Not published

Documented inputs

Claude Opus 4.6

Not sourced

Trinity-Large-Preview

Not sourced

Documented outputs

Claude Opus 4.6

Not sourced

Trinity-Large-Preview

Not sourced

Provider availability

Claude Opus 4.6

Not sourced

Trinity-Large-Preview

Not sourced

Reasoning profile

Claude Opus 4.6

Non-Reasoning

Trinity-Large-Preview

Non-Reasoning

Weight access

Claude Opus 4.6

Proprietary

Trinity-Large-Preview

Open Weight

License

Claude Opus 4.6

Proprietary

Trinity-Large-Preview

Open Weight

Release date

Claude Opus 4.6

2026-02-01

Trinity-Large-Preview

2026-01-27

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 4.6 has the higher public score estimate, 69.84 versus 55.39, but the 90% score intervals overlap.
Workload cost
Repository review: $0.325 vs $0.0155. Cache-heavy agent loop: $1.35 vs $0.065.
Context tradeoff
Claude Opus 4.6 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 evidence34 rows

Agentic

  • Terminal-Bench 2.0

    Claude Opus 4.665.4%
    Source
    Trinity-Large-Preview

    Not directly comparable

  • BrowseComp

    Claude Opus 4.683.7%
    Source
    Trinity-Large-Preview

    Not directly comparable

  • OSWorld-Verified

    Claude Opus 4.672.7%
    Source
    Trinity-Large-Preview

    Not directly comparable

  • Claw-Eval

    Claude Opus 4.670.4%
    Source
    Trinity-Large-Preview

    Not directly comparable

  • DeepSearchQA

    Claude Opus 4.673.7%
    Source
    Trinity-Large-Preview

    Not directly comparable

  • CyberGym

    Claude Opus 4.666.6%
    Source
    Trinity-Large-Preview

    Not directly comparable

  • Gert Labs

    Claude Opus 4.661.85%
    Source
    Trinity-Large-Preview

    Not directly comparable

  • ResearchClawBench

    Claude Opus 4.619.9%
    Source
    Trinity-Large-Preview

    Not directly comparable

  • JobBench

    Claude Opus 4.636.7%
    Source
    Trinity-Large-Preview

    Not directly comparable

Coding

  • SWE-bench Verified

    Claude Opus 4.680.8%
    Source
    Trinity-Large-Preview

    Not directly comparable

  • SWE-bench Verified*

    Claude Opus 4.675.6%
    Source
    Trinity-Large-Preview

    Not directly comparable

  • LiveCodeBench Pro

    Claude Opus 4.670.7%
    Source
    Trinity-Large-Preview

    Not directly comparable

  • SWE-bench Pro

    Claude Opus 4.653.4%
    Source
    Trinity-Large-Preview

    Not directly comparable

  • SWE-Rebench

    Claude Opus 4.665.3%
    Source
    Trinity-Large-Preview

    Not directly comparable

  • React Native Evals

    Claude Opus 4.684.1%
    Source
    Trinity-Large-Preview

    Not directly comparable

  • Vibe Code Bench

    Claude Opus 4.657.57%
    Source
    Trinity-Large-Preview

    Not directly comparable

  • FrontierCode 1.1 Main

    Claude Opus 4.626.9%
    Source
    Trinity-Large-Preview

    Not directly comparable

Knowledge

  • GPQA

    Claude Opus 4.691.3%
    Source
    Trinity-Large-Preview

    Not directly comparable

  • GPQA-D

    Claude Opus 4.689.2%
    Source
    Trinity-Large-Preview63.3%
    Source

    Claude Opus 4.6 leads this result

  • SuperGPQA

    Claude Opus 4.695%
    Source
    Trinity-Large-Preview

    Not directly comparable

  • MMLU-Pro

    Claude Opus 4.682%
    Source
    Trinity-Large-Preview

    Not directly comparable

  • MMLU-Pro (Arcee)

    Claude Opus 4.689.1%
    Source
    Trinity-Large-Preview75.2%
    Source

    Claude Opus 4.6 leads this result

  • HLE

    Claude Opus 4.653%
    Source
    Trinity-Large-Preview

    Not directly comparable

  • HLE w/o tools

    Claude Opus 4.640%
    Source
    Trinity-Large-Preview

    Not directly comparable

  • HealthBench Hard

    Claude Opus 4.614.8%
    Source
    Trinity-Large-Preview

    Not directly comparable

  • MedXpertQA (Text)

    Claude Opus 4.652.1%
    Source
    Trinity-Large-Preview

    Not directly comparable

  • MMLU

    Claude Opus 4.6
    Trinity-Large-Preview87.2%
    Source

    Not directly comparable

Math

  • AIME25 (Arcee)

    Claude Opus 4.699.8%
    Source
    Trinity-Large-Preview24.0%
    Source

    Claude Opus 4.6 leads this result

  • FrontierMath v2 (Tiers 1-3)

    Claude Opus 4.640.700%
    Source
    Trinity-Large-Preview

    Not directly comparable

  • FrontierMath v2 (Tier 4)

    Claude Opus 4.622.900%
    Source
    Trinity-Large-Preview

    Not directly comparable

Multimodal

  • MMMU-Pro

    Claude Opus 4.677.3%
    Source
    Trinity-Large-Preview

    Not directly comparable

  • ERQA

    Claude Opus 4.651.6%
    Source
    Trinity-Large-Preview

    Not directly comparable

  • ScreenSpot Pro

    Claude Opus 4.683.1%
    Source
    Trinity-Large-Preview

    Not directly comparable

  • MedXpertQA (MM)

    Claude Opus 4.664.8%
    Source
    Trinity-Large-Preview

    Not directly comparable

Frequently asked questions

Which is better, Claude Opus 4.6 or Trinity-Large-Preview?

Claude Opus 4.6 has the higher public score estimate, 69.84 versus 55.39, 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 4.6 or Trinity-Large-Preview?

Trinity-Large-Preview is not ranked on the public lane for coding, so no winner is named for coding.

Which is better for agentic tasks, Claude Opus 4.6 or Trinity-Large-Preview?

Trinity-Large-Preview is not ranked on the public lane for agentic tasks, so no winner is named for agentic tasks.

Which costs less, Claude Opus 4.6 or Trinity-Large-Preview?

For the stated presets, chat costs $0.0175 on Claude Opus 4.6 and $0.00075 on Trinity-Large-Preview; repository review costs $0.325 and $0.0155; the cache-heavy agent loop costs $1.35 and $0.065. Claude Opus 4.6 has no published cached-input rate, so cached tokens use its listed input rate. Trinity-Large-Preview has no published cached-input rate, so cached tokens use its listed input rate.

Which has the larger context window, Claude Opus 4.6 or Trinity-Large-Preview?

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

Related comparisons

Last updated September 4, 2026

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