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BenchLM
Model A
dots3-note Preview

Dots Studio

—

Evidence status unavailable

90% interval unavailable

dots3-note Preview vs Ornith-1.0-35B

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

Model B
Ornith-1.0-35B

DeepReinforce AI

—

Evidence status unavailable

90% interval unavailable

Decision reading

At least one model is not scored in the current public ranking lane, so the page does not name an overall quality winner.

5 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.

  • Coding work

    Code generation, repair, and software-engineering tasks

    dots3-note Preview

    dots3-note Preview leads on the same 2 weighted benchmark rows.

    Confidence: limited

  • Long documents

    Prompts that approach the documented context limit

    dots3-note Preview

    dots3-note Preview has the larger documented context window.

    Confidence: documented

Show secondary and unsupported calls

  • 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
5
dots3-note Preview only
26
Ornith-1.0-35B only
2
Like-for-like categories
1 / 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.

Coding

Like-for-like
dots3-note Preview
71.7
Ornith-1.0-35B
65.9
Weighted basis
2 vs 2 rows
Reading
dots3-note Preview leads

Agentic

Not comparable
dots3-note Preview
83.3
Ornith-1.0-35B
64.2
Weighted basis
1 vs 1 rows
Reading
Not comparable

Reasoning

Not comparable
dots3-note Preview
81.4
Ornith-1.0-35B
Not measured
Weighted basis
1 vs 0 rows
Reading
Not comparable

Knowledge

Not comparable
dots3-note Preview
52.6
Ornith-1.0-35B
Not measured
Weighted basis
1 vs 0 rows
Reading
Not comparable

Math

Not comparable
dots3-note Preview
Not measured
Ornith-1.0-35B
Not measured
Weighted basis
0 vs 0 rows
Reading
Not comparable

Multilingual

Not comparable
dots3-note Preview
Not measured
Ornith-1.0-35B
Not measured
Weighted basis
0 vs 0 rows
Reading
Not comparable

Multimodal

Not comparable
dots3-note Preview
79.1
Ornith-1.0-35B
Not measured
Weighted basis
1 vs 0 rows
Reading
Not comparable

Instruction following

Not comparable
dots3-note Preview
85.1
Ornith-1.0-35B
Not measured
Weighted basis
2 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

dots3-note Preview
Self-hosted; infrastructure cost varies
Fits in one request
Ornith-1.0-35B
Self-hosted; infrastructure cost varies
Fits in one request

dots3-note Preview has no comparable published API token rate. Ornith-1.0-35B has no comparable published API token rate.

Repository review

50K fresh input + 3K output tokens

dots3-note Preview
Self-hosted; infrastructure cost varies
Fits in one request
Ornith-1.0-35B
Self-hosted; infrastructure cost varies
Fits in one request

dots3-note Preview has no comparable published API token rate. Ornith-1.0-35B has no comparable published API token rate.

Cache-heavy agent loop

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

dots3-note Preview
Self-hosted; infrastructure cost varies
Fits in one request
Cached-input rate unavailable
Ornith-1.0-35B
Self-hosted; infrastructure cost varies
Fits in one request
Cached-input rate unavailable

dots3-note Preview has no comparable published API token rate. Ornith-1.0-35B 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.

API model ID

dots3-note Preview

Not sourced

Ornith-1.0-35B

Not sourced

Cached-input rate

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

dots3-note Preview

No comparable hosted API rate

dots3-note Preview model card

Ornith-1.0-35B

No comparable hosted API rate

Documented inputs

dots3-note Preview

Not sourced

Ornith-1.0-35B

Not sourced

Documented outputs

dots3-note Preview

Not sourced

Ornith-1.0-35B

Not sourced

Provider availability

dots3-note Preview

Not sourced

Ornith-1.0-35B

Not sourced

Reasoning profile

dots3-note Preview

Reasoning

Ornith-1.0-35B

Reasoning

Weight access

dots3-note Preview

Open Weight

Ornith-1.0-35B

Open Weight

License

dots3-note Preview

Open Weight

Ornith-1.0-35B

Open Weight

Release date

dots3-note Preview

2026-08-14

Ornith-1.0-35B

2026-06-01

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
At least one model is not scored in the current public ranking lane, so the page does not name an overall quality winner.
Workload cost
A complete comparable API-rate estimate is not available for both models.
Context tradeoff
dots3-note Preview has the larger documented window (512K).

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 evidence33 rows

Agentic

  • Claw-Eval

    dots3-note Preview73.4%
    Source
    Ornith-1.0-35B69.8%
    Source

    dots3-note Preview leads this result

  • Terminal-Bench 2.1

    dots3-note Preview75.1%
    Source
    Ornith-1.0-35B—

    Not directly comparable

  • Toolathlon-Verified

    dots3-note Preview55.6%
    Source
    Ornith-1.0-35B—

    Not directly comparable

  • skillsBench

    dots3-note Preview52.8%
    Source
    Ornith-1.0-35B—

    Not directly comparable

  • APEX-Agents

    dots3-note Preview30.8%
    Source
    Ornith-1.0-35B—

    Not directly comparable

  • BrowseComp

    dots3-note Preview83.3%
    Source
    Ornith-1.0-35B—

    Not directly comparable

  • HLE w/ tools

    dots3-note Preview52.6%
    Source
    Ornith-1.0-35B—

    Not directly comparable

  • DeepSearchQA

    dots3-note Preview92.1%
    Source
    Ornith-1.0-35B—

    Not directly comparable

  • WideResearch

    dots3-note Preview78.9%
    Source
    Ornith-1.0-35B—

    Not directly comparable

  • Terminal-Bench 2.0

    dots3-note Preview—
    Ornith-1.0-35B64.2%
    Source

    Not directly comparable

Coding

  • Codeforces

    dots3-note Preview3056.0
    Source
    Ornith-1.0-35B—

    Not directly comparable

  • LiveCodeBench v6

    dots3-note Preview91.5%
    Source
    Ornith-1.0-35B—

    Not directly comparable

  • Terminal-Bench 2.1

    dots3-note Preview75.1%
    Source
    Ornith-1.0-35B—

    Not directly comparable

  • SWE-bench Verified

    dots3-note Preview78.4%
    Source
    Ornith-1.0-35B75.6%
    Source

    dots3-note Preview leads this result

  • SWE Multilingual

    dots3-note Preview75.7%
    Source
    Ornith-1.0-35B69.3%
    Source

    dots3-note Preview leads this result

  • SWE-bench Pro

    dots3-note Preview61%
    Source
    Ornith-1.0-35B50.4%
    Source

    dots3-note Preview leads this result

  • NL2Repo

    dots3-note Preview49.8%
    Source
    Ornith-1.0-35B34.6%
    Source

    dots3-note Preview leads this result

  • Terminal-Bench 2.0

    dots3-note Preview—
    Ornith-1.0-35B64.2%
    Source

    Not directly comparable

Reasoning

  • ARC-AGI-2

    dots3-note Preview81.4%
    Source
    Ornith-1.0-35B—

    Not directly comparable

Knowledge

  • HLE

    dots3-note Preview52.6%
    Source
    Ornith-1.0-35B—

    Not directly comparable

Math

  • IMOAnswerBench

    dots3-note Preview90.9%
    Source
    Ornith-1.0-35B—

    Not directly comparable

Multimodal

  • SimpleVQA

    dots3-note Preview72.5%
    Source
    Ornith-1.0-35B—

    Not directly comparable

  • MMMU-Pro

    dots3-note Preview79.1%
    Source
    Ornith-1.0-35B—

    Not directly comparable

  • MathVision

    dots3-note Preview87.7%
    Source
    Ornith-1.0-35B—

    Not directly comparable

  • ZeroBench

    dots3-note Preview19.0%
    Source
    Ornith-1.0-35B—

    Not directly comparable

  • CharXiv w/o tools

    dots3-note Preview83.1%
    Source
    Ornith-1.0-35B—

    Not directly comparable

  • GDP.pdf (no tools)

    dots3-note Preview60.7%
    Source
    Ornith-1.0-35B—

    Not directly comparable

  • PerceptionBench

    dots3-note Preview53.4%
    Source
    Ornith-1.0-35B—

    Not directly comparable

  • BabyVision

    dots3-note Preview50.0%
    Source
    Ornith-1.0-35B—

    Not directly comparable

  • MMVU

    dots3-note Preview79.9%
    Source
    Ornith-1.0-35B—

    Not directly comparable

  • VideoMMMU

    dots3-note Preview86.8%
    Source
    Ornith-1.0-35B—

    Not directly comparable

Instruction following

  • IFBench

    dots3-note Preview80.4%
    Source
    Ornith-1.0-35B—

    Not directly comparable

  • IFEval

    dots3-note Preview93.9%
    Source
    Ornith-1.0-35B—

    Not directly comparable

Frequently asked questions

Which is better, dots3-note Preview or Ornith-1.0-35B?

At least one model is not scored in the current public ranking lane, so the page does not name an overall quality winner. The page therefore keeps the decision tied to the specific documented workload.

Which is better for coding, dots3-note Preview or Ornith-1.0-35B?

dots3-note Preview leads the like-for-like coding comparison across 2 shared weighted benchmark rows.

Which is better for agentic tasks, dots3-note Preview or Ornith-1.0-35B?

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, dots3-note Preview or Ornith-1.0-35B?

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, dots3-note Preview or Ornith-1.0-35B?

dots3-note Preview has the larger documented context window: 512K, compared with 256K.

Related comparisons

Compare API pricing Read the methodology Open the model selector

Last updated August 14, 2026

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