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Model A
GPT-5.6 Cyber

OpenAI

Evidence status unavailable

90% interval unavailable

GPT-5.6 Cyber vs Inkling

Updated August 13, 2026. Public scores include evidence status and uncertainty. They are not guarantees for a specific workload.

Model B
Inkling

Thinking Machines Lab

66.8/100

Supported · Public rank #24

90% interval 59.8–73.7

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.

No workload recommendation clears the current evidence threshold.

Use the matched evidence, workload costs, and sourced specifications below instead of treating a point score as a universal answer.

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

  • Long documents

    Prompts that approach the documented context limit

    Not enough matched evidence

    A complete context comparison is not sourced.

    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
GPT-5.6 Cyber only
0
Inkling only
15
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
GPT-5.6 Cyber
Not measured
Inkling
69.4
Weighted basis
0 vs 2 rows
Reading
Not comparable

Coding

Not comparable
GPT-5.6 Cyber
Not measured
Inkling
68.6
Weighted basis
0 vs 2 rows
Reading
Not comparable

Reasoning

Not comparable
GPT-5.6 Cyber
Not measured
Inkling
Not measured
Weighted basis
0 vs 0 rows
Reading
Not comparable

Knowledge

Not comparable
GPT-5.6 Cyber
Not measured
Inkling
51.6
Weighted basis
0 vs 2 rows
Reading
Not comparable

Math

Not comparable
GPT-5.6 Cyber
Not measured
Inkling
97.1
Weighted basis
0 vs 1 rows
Reading
Not comparable

Multilingual

Not comparable
GPT-5.6 Cyber
Not measured
Inkling
Not measured
Weighted basis
0 vs 0 rows
Reading
Not comparable

Multimodal

Not comparable
GPT-5.6 Cyber
Not measured
Inkling
76.5
Weighted basis
0 vs 2 rows
Reading
Not comparable

Instruction following

Not comparable
GPT-5.6 Cyber
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.

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

GPT-5.6 Cyber
API rate not published
Fit state unavailable
Inkling
$0.00421
Fits in one request

GPT-5.6 Cyber has no comparable published API token rate.

Repository review

50K fresh input + 3K output tokens

GPT-5.6 Cyber
API rate not published
Fit state unavailable
Inkling
$0.10754
Fits in one request

GPT-5.6 Cyber has no comparable published API token rate.

Cache-heavy agent loop

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

GPT-5.6 Cyber
API rate not published
Fit state unavailable
Cached-input rate unavailable
Inkling
$0.159
Fits in one request

GPT-5.6 Cyber 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.

Context window

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

GPT-5.6 Cyber

Not sourced

Inkling

1M

Cached-input rate

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

GPT-5.6 Cyber

No comparable hosted API rate

OpenAI Daybreak overview

Inkling

$0.374 per 1M cached input tokens

Documented inputs

GPT-5.6 Cyber

Not sourced

Inkling

Not sourced

Documented outputs

GPT-5.6 Cyber

Not sourced

Inkling

Not sourced

Provider availability

GPT-5.6 Cyber

Not sourced

Inkling

Not sourced

Reasoning profile

GPT-5.6 Cyber

Reasoning

Inkling

Hybrid

Weight access

GPT-5.6 Cyber

Proprietary

Inkling

Open Weight

License

GPT-5.6 Cyber

Proprietary

Inkling

Open Weight

Release date

GPT-5.6 Cyber

2026-08-10

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
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
A complete documented context comparison is not available.

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 evidence15 rows

Agentic

  • Terminal-Bench 2.0

    GPT-5.6 Cyber
    Inkling63.8%
    Source

    Not directly comparable

  • BrowseComp

    GPT-5.6 Cyber
    Inkling77.1%
    Source

    Not directly comparable

  • MCP Atlas

    GPT-5.6 Cyber
    Inkling74.1%
    Source

    Not directly comparable

Coding

  • SWE-bench Verified

    GPT-5.6 Cyber
    Inkling77.6%
    Source

    Not directly comparable

  • SWE-bench Pro

    GPT-5.6 Cyber
    Inkling54.3%
    Source

    Not directly comparable

  • Terminal-Bench 2.0

    GPT-5.6 Cyber
    Inkling63.8%
    Source

    Not directly comparable

Knowledge

  • GPQA

    GPT-5.6 Cyber
    Inkling87.9%
    Source

    Not directly comparable

  • GPQA-D

    GPT-5.6 Cyber
    Inkling87.9%
    Source

    Not directly comparable

  • HLE

    GPT-5.6 Cyber
    Inkling46%
    Source

    Not directly comparable

  • HLE w/o tools

    GPT-5.6 Cyber
    Inkling30%
    Source

    Not directly comparable

Math

  • AIME26

    GPT-5.6 Cyber
    Inkling97.1%
    Source

    Not directly comparable

Multimodal

  • MMMU-Pro

    GPT-5.6 Cyber
    Inkling73.5%
    Source

    Not directly comparable

  • CharXiv

    GPT-5.6 Cyber
    Inkling82%
    Source

    Not directly comparable

  • CharXiv w/o tools

    GPT-5.6 Cyber
    Inkling78.1%
    Source

    Not directly comparable

Instruction following

  • IFBench

    GPT-5.6 Cyber
    Inkling79.8%
    Source

    Not directly comparable

Frequently asked questions

Which is better, GPT-5.6 Cyber or Inkling?

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, GPT-5.6 Cyber or Inkling?

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, GPT-5.6 Cyber or Inkling?

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, GPT-5.6 Cyber or Inkling?

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, GPT-5.6 Cyber or Inkling?

A complete documented context-window comparison is not available.

Related comparisons

Last updated August 13, 2026

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