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BenchLM
Model A
Inkling-Small

Thinking Machines Lab

65.6/100

Supported · Public rank #35

90% interval 58.9–72.3

Inkling-Small vs Ornith-1.5-9B

Updated August 19, 2026. Public scores include evidence status and uncertainty. They are not guarantees for a specific workload.

Model B
Ornith-1.5-9B

Ornith AI

37.0/100

Estimated · Public rank #205

90% interval 27.1–46.8

Decision reading

Inkling-Small has the higher public score, 65.57 versus 36.95, and the 90% score intervals do not overlap.

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.

  • Long documents

    Prompts that approach the documented context limit

    Inkling-Small

    Inkling-Small 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

    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

  • 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
9
Inkling-Small only
11
Ornith-1.5-9B only
7
Like-for-like categories
1 / 8

2 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.

Knowledge

Like-for-like
Inkling-Small
53.4
Ornith-1.5-9B
29.1
Weighted basis
2 vs 2 rows
Reading
Inkling-Small leads

Agentic

Directional only
Inkling-Small
70.1
Ornith-1.5-9B
56.4
Weighted basis
2 vs 1 rows
Reading
Directional only

Coding

Directional only
Inkling-Small
62.4
Ornith-1.5-9B
61.7
Weighted basis
3 vs 2 rows
Reading
Directional only

Reasoning

Not comparable
Inkling-Small
40.1
Ornith-1.5-9B
Not measured
Weighted basis
1 vs 0 rows
Reading
Not comparable

Math

Not comparable
Inkling-Small
92.9
Ornith-1.5-9B
Not measured
Weighted basis
2 vs 0 rows
Reading
Not comparable

Multilingual

Not comparable
Inkling-Small
Not measured
Ornith-1.5-9B
Not measured
Weighted basis
0 vs 0 rows
Reading
Not comparable

Multimodal

Not comparable
Inkling-Small
76.6
Ornith-1.5-9B
Not measured
Weighted basis
2 vs 0 rows
Reading
Not comparable

Instruction following

Not comparable
Inkling-Small
82.2
Ornith-1.5-9B
Not measured
Weighted basis
1 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

Inkling-Small
$0.0013
Fits in one request
Ornith-1.5-9B
Self-hosted; infrastructure cost varies
Fits in one request

Ornith-1.5-9B has no comparable published API token rate.

Repository review

50K fresh input + 3K output tokens

Inkling-Small
$0.03332
Fits in one request
Ornith-1.5-9B
Self-hosted; infrastructure cost varies
Fits in one request

Ornith-1.5-9B has no comparable published API token rate.

Cache-heavy agent loop

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

Inkling-Small
$0.0492
Fits in one request
Ornith-1.5-9B
Self-hosted; infrastructure cost varies
Fits in one request
Cached-input rate unavailable

Ornith-1.5-9B 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.

Inkling-Small

1M

Ornith-1.5-9B

262K

Ornith-1.5-9B model card

API model ID

Inkling-Small

Not sourced

Ornith-1.5-9B

Not sourced

Cached-input rate

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

Inkling-Small

$0.116 per 1M cached input tokens

Ornith-1.5-9B

No comparable hosted API rate

Ornith-1.5-9B model card

Documented inputs

Inkling-Small

Not sourced

Ornith-1.5-9B

Not sourced

Documented outputs

Inkling-Small

Not sourced

Ornith-1.5-9B

Not sourced

Provider availability

Inkling-Small

Not sourced

Ornith-1.5-9B

Not sourced

Reasoning profile

Inkling-Small

Hybrid

Ornith-1.5-9B

Reasoning

Weight access

Inkling-Small

Open Weight

Ornith-1.5-9B

Open Weight

License

Inkling-Small

Open Weight

Ornith-1.5-9B

Open Weight

Release date

Inkling-Small

2026-07-30

Ornith-1.5-9B

2026-08-18

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
Inkling-Small has the higher public score, 65.57 versus 36.95, and the 90% score intervals do not overlap.
Workload cost
A complete comparable API-rate estimate is not available for both models.
Context tradeoff
Inkling-Small 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 evidence27 rows

Agentic

  • Terminal-Bench 2.0

    Inkling-Small64.7%
    Source
    Ornith-1.5-9B—

    Not directly comparable

  • BrowseComp

    Inkling-Small77.4%
    Source
    Ornith-1.5-9B56.4%
    Source

    Inkling-Small leads this result

  • MCP Atlas

    Inkling-Small79.6%
    Source
    Ornith-1.5-9B54.2%
    Source

    Inkling-Small leads this result

  • Toolathlon-Verified

    Inkling-Small54.4%
    Source
    Ornith-1.5-9B41.2%
    Source

    Inkling-Small leads this result

  • Terminal-Bench 2.1

    Inkling-Small—
    Ornith-1.5-9B46.2%
    Source

    Not directly comparable

  • HLE w/ tools

    Inkling-Small—
    Ornith-1.5-9B30.5%
    Source

    Not directly comparable

  • WideResearch

    Inkling-Small—
    Ornith-1.5-9B59.5%
    Source

    Not directly comparable

  • Claw-Eval

    Inkling-Small—
    Ornith-1.5-9B66.5%
    Source

    Not directly comparable

Coding

  • SWE-bench Verified

    Inkling-Small80.2%
    Source
    Ornith-1.5-9B70.6%
    Source

    Inkling-Small leads this result

  • SWE-bench Pro

    Inkling-Small55.9%
    Source
    Ornith-1.5-9B47.5%
    Source

    Inkling-Small leads this result

  • Terminal-Bench 2.0

    Inkling-Small64.7%
    Source
    Ornith-1.5-9B—

    Not directly comparable

  • SciCode

    Inkling-Small48.7%
    Source
    Ornith-1.5-9B—

    Not directly comparable

  • Terminal-Bench 2.1

    Inkling-Small—
    Ornith-1.5-9B46.2%
    Source

    Not directly comparable

  • SWE Multilingual

    Inkling-Small—
    Ornith-1.5-9B54.4%
    Source

    Not directly comparable

  • NL2Repo

    Inkling-Small—
    Ornith-1.5-9B32.4%
    Source

    Not directly comparable

Reasoning

  • ARC-AGI-2

    Inkling-Small40.1%
    Source
    Ornith-1.5-9B—

    Not directly comparable

  • CritPt

    Inkling-Small8.3%
    Source
    Ornith-1.5-9B—

    Not directly comparable

Knowledge

  • GPQA

    Inkling-Small89.5%
    Source
    Ornith-1.5-9B86.4%
    Source

    Inkling-Small leads this result

  • GPQA-D

    Inkling-Small89.5%
    Source
    Ornith-1.5-9B86.4%
    Source

    Inkling-Small leads this result

  • HLE

    Inkling-Small47.8%
    Source
    Ornith-1.5-9B20.2%
    Source

    Inkling-Small leads this result

  • HLE w/o tools

    Inkling-Small31.6%
    Source
    Ornith-1.5-9B20.2%
    Source

    Inkling-Small leads this result

Math

  • AIME26

    Inkling-Small95.5%
    Source
    Ornith-1.5-9B—

    Not directly comparable

  • HMMT Feb 2026

    Inkling-Small90.2%
    Source
    Ornith-1.5-9B—

    Not directly comparable

Multimodal

  • MMMU-Pro

    Inkling-Small74%
    Source
    Ornith-1.5-9B—

    Not directly comparable

  • CharXiv

    Inkling-Small81.3%
    Source
    Ornith-1.5-9B—

    Not directly comparable

  • CharXiv w/o tools

    Inkling-Small77.4%
    Source
    Ornith-1.5-9B—

    Not directly comparable

Instruction following

  • IFBench

    Inkling-Small82.2%
    Source
    Ornith-1.5-9B—

    Not directly comparable

Frequently asked questions

Which is better, Inkling-Small or Ornith-1.5-9B?

Inkling-Small has the higher public score, 65.57 versus 36.95, and the 90% score intervals do not overlap. That is the clearest overall quality signal in the current public data.

Which is better for coding, Inkling-Small or Ornith-1.5-9B?

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, Inkling-Small or Ornith-1.5-9B?

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, Inkling-Small or Ornith-1.5-9B?

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, Inkling-Small or Ornith-1.5-9B?

Inkling-Small has the larger documented context window: 1M, compared with 262K.

Related comparisons

Compare API pricing Read the methodology Open the model selector

Last updated August 19, 2026

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