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BenchLM
Model A
Ling 3.0 Flash

InclusionAI

53.8/100

Estimated · Public rank #105

90% interval 42.3–65.3

Ling 3.0 Flash vs Ornith-1.5-35B-A3B

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

Model B
Ornith-1.5-35B-A3B

Ornith AI

49.3/100

Estimated · Public rank #136

90% interval 39.4–59.1

Decision reading

Ling 3.0 Flash has the higher public score estimate, 53.76 versus 49.27, but the 90% score intervals overlap. Treat that as a lead, not a settled winner.

8 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.

  • Agentic work

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

    Ling 3.0 Flash

    Ling 3.0 Flash leads on the same 1 weighted benchmark row.

    Confidence: limited

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

  • Long documents

    Prompts that approach the documented context limit

    No clear pick

    The documented context windows are equal.

    Confidence: documented

  • 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
8
Ling 3.0 Flash only
9
Ornith-1.5-35B-A3B only
10
Like-for-like categories
2 / 8

1 category uses 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

Like-for-like
Ling 3.0 Flash
72.2
Ornith-1.5-35B-A3B
67.6
Weighted basis
1 vs 1 rows
Reading
Ling 3.0 Flash leads

Knowledge

Like-for-like
Ling 3.0 Flash
31.1
Ornith-1.5-35B-A3B
34.2
Weighted basis
2 vs 2 rows
Reading
Ornith-1.5-35B-A3B leads

Coding

Directional only
Ling 3.0 Flash
47.1
Ornith-1.5-35B-A3B
71.5
Weighted basis
2 vs 2 rows
Reading
Directional only

Reasoning

Not comparable
Ling 3.0 Flash
Not measured
Ornith-1.5-35B-A3B
Not measured
Weighted basis
0 vs 0 rows
Reading
Not comparable

Math

Not comparable
Ling 3.0 Flash
90.1
Ornith-1.5-35B-A3B
Not measured
Weighted basis
2 vs 0 rows
Reading
Not comparable

Multilingual

Not comparable
Ling 3.0 Flash
Not measured
Ornith-1.5-35B-A3B
Not measured
Weighted basis
0 vs 0 rows
Reading
Not comparable

Multimodal

Not comparable
Ling 3.0 Flash
Not measured
Ornith-1.5-35B-A3B
Not measured
Weighted basis
0 vs 0 rows
Reading
Not comparable

Instruction following

Not comparable
Ling 3.0 Flash
74.5
Ornith-1.5-35B-A3B
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

Ling 3.0 Flash
API rate not published
Fits in one request
Ornith-1.5-35B-A3B
Self-hosted; infrastructure cost varies
Fits in one request

Ling 3.0 Flash has no comparable published API token rate. Ornith-1.5-35B-A3B has no comparable published API token rate.

Repository review

50K fresh input + 3K output tokens

Ling 3.0 Flash
API rate not published
Fits in one request
Ornith-1.5-35B-A3B
Self-hosted; infrastructure cost varies
Fits in one request

Ling 3.0 Flash has no comparable published API token rate. Ornith-1.5-35B-A3B has no comparable published API token rate.

Cache-heavy agent loop

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

Ling 3.0 Flash
API rate not published
Fits in one request
Cached-input rate unavailable
Ornith-1.5-35B-A3B
Self-hosted; infrastructure cost varies
Fits in one request
Cached-input rate unavailable

Ling 3.0 Flash has no comparable published API token rate. Ornith-1.5-35B-A3B 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

Ling 3.0 Flash

Not sourced

Ornith-1.5-35B-A3B

Not sourced

Documented inputs

Ling 3.0 Flash

Not sourced

Ornith-1.5-35B-A3B

Not sourced

Documented outputs

Ling 3.0 Flash

Not sourced

Ornith-1.5-35B-A3B

Not sourced

Provider availability

Ling 3.0 Flash

Not sourced

Ornith-1.5-35B-A3B

Not sourced

Reasoning profile

Ling 3.0 Flash

Reasoning

Ornith-1.5-35B-A3B

Reasoning

Weight access

Ling 3.0 Flash

Open Weight

Ornith-1.5-35B-A3B

Open Weight

License

Ling 3.0 Flash

Open Weight

Ornith-1.5-35B-A3B

Open Weight

Release date

Ling 3.0 Flash

2026-07-23

Ornith-1.5-35B-A3B

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
Ling 3.0 Flash has the higher public score estimate, 53.76 versus 49.27, but the 90% score intervals overlap.
Workload cost
A complete comparable API-rate estimate is not available for both models.
Context tradeoff
Both models list 262K.

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

  • MCP Atlas

    Ling 3.0 Flash65.5%
    Source
    Ornith-1.5-35B-A3B70.2%
    Source

    Ornith-1.5-35B-A3B leads this result

  • skillsBench

    Ling 3.0 Flash44.8%
    Source
    Ornith-1.5-35B-A3B—

    Not directly comparable

  • BFCL v4

    Ling 3.0 Flash73.0%
    Source
    Ornith-1.5-35B-A3B—

    Not directly comparable

  • WideResearch

    Ling 3.0 Flash73.6%
    Source
    Ornith-1.5-35B-A3B67.8%
    Source

    Ling 3.0 Flash leads this result

  • BrowseComp

    Ling 3.0 Flash72.2%
    Source
    Ornith-1.5-35B-A3B67.6%
    Source

    Ling 3.0 Flash leads this result

  • DRACO

    Ling 3.0 Flash70.4%
    Source
    Ornith-1.5-35B-A3B—

    Not directly comparable

  • Terminal-Bench 2.1

    Ling 3.0 Flash—
    Ornith-1.5-35B-A3B67.8%
    Source

    Not directly comparable

  • HLE w/ tools

    Ling 3.0 Flash—
    Ornith-1.5-35B-A3B33.4%
    Source

    Not directly comparable

  • Toolathlon-Verified

    Ling 3.0 Flash—
    Ornith-1.5-35B-A3B48.7%
    Source

    Not directly comparable

  • Claw-Eval

    Ling 3.0 Flash—
    Ornith-1.5-35B-A3B72.5%
    Source

    Not directly comparable

Coding

  • SWE-bench Pro

    Ling 3.0 Flash56.6%
    Source
    Ornith-1.5-35B-A3B59.6%
    Source

    Ornith-1.5-35B-A3B leads this result

  • SWE Multilingual

    Ling 3.0 Flash72.4%
    Source
    Ornith-1.5-35B-A3B71.4%
    Source

    Ling 3.0 Flash leads this result

  • LiveCodeBench v5

    Ling 3.0 Flash82.8%
    Source
    Ornith-1.5-35B-A3B—

    Not directly comparable

  • SciCode

    Ling 3.0 Flash41.2%
    Source
    Ornith-1.5-35B-A3B—

    Not directly comparable

  • Terminal-Bench 2.1

    Ling 3.0 Flash—
    Ornith-1.5-35B-A3B67.8%
    Source

    Not directly comparable

  • SWE-bench Verified

    Ling 3.0 Flash—
    Ornith-1.5-35B-A3B79%
    Source

    Not directly comparable

  • deepSwe

    Ling 3.0 Flash—
    Ornith-1.5-35B-A3B22%
    Source

    Not directly comparable

  • frontierBench

    Ling 3.0 Flash—
    Ornith-1.5-35B-A3B5.1%
    Source

    Not directly comparable

  • NL2Repo

    Ling 3.0 Flash—
    Ornith-1.5-35B-A3B46.2%
    Source

    Not directly comparable

Knowledge

  • GPQA

    Ling 3.0 Flash85.0%
    Source
    Ornith-1.5-35B-A3B89.2%
    Source

    Ornith-1.5-35B-A3B leads this result

  • GPQA-D

    Ling 3.0 Flash85.0%
    Source
    Ornith-1.5-35B-A3B89.2%
    Source

    Ornith-1.5-35B-A3B leads this result

  • HLE

    Ling 3.0 Flash22.7%
    Source
    Ornith-1.5-35B-A3B25.6%
    Source

    Ornith-1.5-35B-A3B leads this result

  • HLE w/o tools

    Ling 3.0 Flash—
    Ornith-1.5-35B-A3B25.6%
    Source

    Not directly comparable

Math

  • AIME26

    Ling 3.0 Flash93.2%
    Source
    Ornith-1.5-35B-A3B—

    Not directly comparable

  • HMMT Feb 2026

    Ling 3.0 Flash87.0%
    Source
    Ornith-1.5-35B-A3B—

    Not directly comparable

  • IMOAnswerBench

    Ling 3.0 Flash83.7%
    Source
    Ornith-1.5-35B-A3B—

    Not directly comparable

Instruction following

  • IFBench

    Ling 3.0 Flash74.5%
    Source
    Ornith-1.5-35B-A3B—

    Not directly comparable

Frequently asked questions

Which is better, Ling 3.0 Flash or Ornith-1.5-35B-A3B?

Ling 3.0 Flash has the higher public score estimate, 53.76 versus 49.27, but the 90% score intervals overlap. The higher estimate is not a decisive winner because the uncertainty ranges overlap.

Which is better for coding, Ling 3.0 Flash or Ornith-1.5-35B-A3B?

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, Ling 3.0 Flash or Ornith-1.5-35B-A3B?

Ling 3.0 Flash leads the like-for-like agentic tasks comparison across 1 shared weighted benchmark row.

Which costs less, Ling 3.0 Flash or Ornith-1.5-35B-A3B?

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, Ling 3.0 Flash or Ornith-1.5-35B-A3B?

Both models list the same context window, 262K.

Related comparisons

Compare API pricing Read the methodology Open the model selector

Last updated August 19, 2026

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