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Model A
Claude Opus 4.6

Anthropic

68.26/100

Supported · Public rank #24

90% interval 54.6–81.9

Claude Opus 4.6 vs Inkling

Updated August 29, 2026. Public scores include evidence status and uncertainty. They are not guarantees for a specific workload.

Thinking Machines Lab logo
Model B
Inkling

Thinking Machines Lab

67.02/100

Supported · Public rank #31

90% interval 60.0–74.0

Decision reading

Claude Opus 4.6 has the higher public score estimate, 68.26 versus 67.02, but the 90% score intervals overlap. Treat that as a lead, not a settled winner.

9 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.

  • Chat turn cost

    1K fresh input + 500 output tokens

    Inkling

    Inkling 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

    Inkling

    Inkling 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.

    Confidence: rate-fallback

Show secondary and unsupported calls
  • Repository review cost

    50K fresh input + 3K output tokens

    Inkling

    Inkling 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

  • Long documents

    Prompts that approach the documented context limit

    No clear pick

    The documented context windows are equal.

    Confidence: documented

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
9
Claude Opus 4.6 only
24
Inkling only
6
Like-for-like categories
0 / 8

4 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 4.6
73.0
Inkling
69.4
Weighted basis
3 vs 2 rows
Reading
Directional only

Coding

Directional only
Claude Opus 4.6
68.1
Inkling
68.6
Weighted basis
3 vs 2 rows
Reading
Directional only

Knowledge

Directional only
Claude Opus 4.6
69.1
Inkling
51.6
Weighted basis
4 vs 2 rows
Reading
Directional only

Multimodal

Directional only
Claude Opus 4.6
77.3
Inkling
76.5
Weighted basis
1 vs 2 rows
Reading
Directional only

Reasoning

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

Math

Not comparable
Claude Opus 4.6
36.3
Inkling
97.1
Weighted basis
2 vs 1 rows
Reading
Not comparable

Multilingual

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

Instruction following

Not comparable
Claude Opus 4.6
Not measured
Inkling
79.8
Weighted basis
0 vs 1 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 4.6
$0.0175
Fits in one request
Inkling
$0.00421
Fits in one request

Inkling 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
Inkling
$0.10754
Fits in one request

Inkling 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
Inkling
$0.159
Fits in one request

Inkling has the lower modeled cost

Claude Opus 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 4.6

1M

Inkling

1M

API model ID

Claude Opus 4.6

Not sourced

Inkling

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

Inkling

$0.374 per 1M cached input tokens

Documented inputs

Claude Opus 4.6

Not sourced

Inkling

Not sourced

Documented outputs

Claude Opus 4.6

Not sourced

Inkling

Not sourced

Provider availability

Claude Opus 4.6

Not sourced

Inkling

Not sourced

Reasoning profile

Claude Opus 4.6

Non-Reasoning

Inkling

Hybrid

Weight access

Claude Opus 4.6

Proprietary

Inkling

Open Weight

License

Claude Opus 4.6

Proprietary

Inkling

Open Weight

Release date

Claude Opus 4.6

2026-02-01

Inkling

2026-07-15

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 4.6 has the higher public score estimate, 68.26 versus 67.02, but the 90% score intervals overlap.
Workload cost
Repository review: $0.325 vs $0.10754. Cache-heavy agent loop: $1.35 vs $0.159.
Context tradeoff
Both models list 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 evidence39 rows

Agentic

  • Terminal-Bench 2.0

    Claude Opus 4.665.4%
    Source
    Inkling63.8%
    Source

    Claude Opus 4.6 leads this result

  • BrowseComp

    Claude Opus 4.683.7%
    Source
    Inkling77.1%
    Source

    Claude Opus 4.6 leads this result

  • OSWorld-Verified

    Claude Opus 4.672.7%
    Source
    Inkling

    Not directly comparable

  • Claw-Eval

    Claude Opus 4.670.4%
    Source
    Inkling

    Not directly comparable

  • DeepSearchQA

    Claude Opus 4.673.7%
    Source
    Inkling

    Not directly comparable

  • CyberGym

    Claude Opus 4.666.6%
    Source
    Inkling

    Not directly comparable

  • Gert Labs

    Claude Opus 4.661.85%
    Source
    Inkling

    Not directly comparable

  • ResearchClawBench

    Claude Opus 4.619.9%
    Source
    Inkling

    Not directly comparable

  • JobBench

    Claude Opus 4.636.7%
    Source
    Inkling

    Not directly comparable

  • MCP Atlas

    Claude Opus 4.6
    Inkling74.1%
    Source

    Not directly comparable

Coding

  • SWE-bench Verified

    Claude Opus 4.680.8%
    Source
    Inkling77.6%
    Source

    Claude Opus 4.6 leads this result

  • SWE-bench Verified*

    Claude Opus 4.675.6%
    Source
    Inkling

    Not directly comparable

  • LiveCodeBench Pro

    Claude Opus 4.670.7%
    Source
    Inkling

    Not directly comparable

  • SWE-bench Pro

    Claude Opus 4.653.4%
    Source
    Inkling54.3%
    Source

    Inkling leads this result

  • SWE-Rebench

    Claude Opus 4.665.3%
    Source
    Inkling

    Not directly comparable

  • React Native Evals

    Claude Opus 4.684.1%
    Source
    Inkling

    Not directly comparable

  • Vibe Code Bench

    Claude Opus 4.657.57%
    Source
    Inkling

    Not directly comparable

  • FrontierCode 1.1 Main

    Claude Opus 4.626.9%
    Source
    Inkling

    Not directly comparable

  • Terminal-Bench 2.0

    Claude Opus 4.6
    Inkling63.8%
    Source

    Not directly comparable

Knowledge

  • GPQA

    Claude Opus 4.691.3%
    Source
    Inkling87.9%
    Source

    Claude Opus 4.6 leads this result

  • GPQA-D

    Claude Opus 4.689.2%
    Source
    Inkling87.9%
    Source

    Claude Opus 4.6 leads this result

  • SuperGPQA

    Claude Opus 4.695%
    Source
    Inkling

    Not directly comparable

  • MMLU-Pro

    Claude Opus 4.682%
    Source
    Inkling

    Not directly comparable

  • MMLU-Pro (Arcee)

    Claude Opus 4.689.1%
    Source
    Inkling

    Not directly comparable

  • HLE

    Claude Opus 4.653%
    Source
    Inkling46%
    Source

    Claude Opus 4.6 leads this result

  • HLE w/o tools

    Claude Opus 4.640%
    Source
    Inkling30%
    Source

    Claude Opus 4.6 leads this result

  • HealthBench Hard

    Claude Opus 4.614.8%
    Source
    Inkling

    Not directly comparable

  • MedXpertQA (Text)

    Claude Opus 4.652.1%
    Source
    Inkling

    Not directly comparable

Math

  • AIME25 (Arcee)

    Claude Opus 4.699.8%
    Source
    Inkling

    Not directly comparable

  • FrontierMath v2 (Tiers 1-3)

    Claude Opus 4.640.700%
    Source
    Inkling

    Not directly comparable

  • FrontierMath v2 (Tier 4)

    Claude Opus 4.622.900%
    Source
    Inkling

    Not directly comparable

  • AIME26

    Claude Opus 4.6
    Inkling97.1%
    Source

    Not directly comparable

Multimodal

  • MMMU-Pro

    Claude Opus 4.677.3%
    Source
    Inkling73.5%
    Source

    Claude Opus 4.6 leads this result

  • ERQA

    Claude Opus 4.651.6%
    Source
    Inkling

    Not directly comparable

  • ScreenSpot Pro

    Claude Opus 4.683.1%
    Source
    Inkling

    Not directly comparable

  • MedXpertQA (MM)

    Claude Opus 4.664.8%
    Source
    Inkling

    Not directly comparable

  • CharXiv

    Claude Opus 4.6
    Inkling82%
    Source

    Not directly comparable

  • CharXiv w/o tools

    Claude Opus 4.6
    Inkling78.1%
    Source

    Not directly comparable

Instruction following

  • IFBench

    Claude Opus 4.6
    Inkling79.8%
    Source

    Not directly comparable

Frequently asked questions

Which is better, Claude Opus 4.6 or Inkling?

Claude Opus 4.6 has the higher public score estimate, 68.26 versus 67.02, 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 Inkling?

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 4.6 or Inkling?

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 4.6 or Inkling?

For the stated presets, chat costs $0.0175 on Claude Opus 4.6 and $0.00421 on Inkling; repository review costs $0.325 and $0.10754; the cache-heavy agent loop costs $1.35 and $0.159. Claude Opus 4.6 has no published cached-input rate, so cached tokens use its listed input rate.

Which has the larger context window, Claude Opus 4.6 or Inkling?

Both models list the same context window, 1M.

Related comparisons

Last updated August 29, 2026

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