Skip to main content
BenchLM
Advertise

Model comparison

Ling 3.0 Flash FP8 vs Nemotron 3 Nano Omni 30B A3B

Updated August 4, 2026. Public scores include evidence status and uncertainty. They are not guarantees for a specific workload.

Ling 3.0 Flash FP8

InclusionAI

—

Evidence status unavailable

90% interval unavailable

Nemotron 3 Nano Omni 30B A3B

NVIDIA

43.3/100

Estimated · Public rank #162

90% interval 31.8–54.8

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

4 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

    Ling 3.0 Flash FP8

    Ling 3.0 Flash FP8 leads on the same 1 weighted benchmark row.

    Confidence: limited

  • Long documents

    Prompts that approach the documented context limit

    Ling 3.0 Flash FP8

    Ling 3.0 Flash FP8 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
4
Ling 3.0 Flash FP8 only
0
Nemotron 3 Nano Omni 30B A3B only
12
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.

Coding

Like-for-like
Ling 3.0 Flash FP8
40.4
Nemotron 3 Nano Omni 30B A3B
32.0
Weighted basis
1 vs 1 rows
Reading
Ling 3.0 Flash FP8 leads

Instruction following

Like-for-like
Ling 3.0 Flash FP8
73.4
Nemotron 3 Nano Omni 30B A3B
74.2
Weighted basis
1 vs 1 rows
Reading
Nemotron 3 Nano Omni 30B A3B leads

Knowledge

Directional only
Ling 3.0 Flash FP8
84.0
Nemotron 3 Nano Omni 30B A3B
76.3
Weighted basis
1 vs 2 rows
Reading
Directional only

Agentic

Not comparable
Ling 3.0 Flash FP8
Not measured
Nemotron 3 Nano Omni 30B A3B
Not measured
Weighted basis
0 vs 0 rows
Reading
Not comparable

Reasoning

Not comparable
Ling 3.0 Flash FP8
Not measured
Nemotron 3 Nano Omni 30B A3B
Not measured
Weighted basis
0 vs 0 rows
Reading
Not comparable

Math

Not comparable
Ling 3.0 Flash FP8
Not measured
Nemotron 3 Nano Omni 30B A3B
Not measured
Weighted basis
0 vs 0 rows
Reading
Not comparable

Multilingual

Not comparable
Ling 3.0 Flash FP8
Not measured
Nemotron 3 Nano Omni 30B A3B
Not measured
Weighted basis
0 vs 0 rows
Reading
Not comparable

Multimodal

Not comparable
Ling 3.0 Flash FP8
Not measured
Nemotron 3 Nano Omni 30B A3B
76.3
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

Ling 3.0 Flash FP8
API rate not published
Fits in one request
Nemotron 3 Nano Omni 30B A3B
Self-hosted; infrastructure cost varies
Fits in one request

Ling 3.0 Flash FP8 has no comparable published API token rate. Nemotron 3 Nano Omni 30B A3B has no comparable published API token rate.

Repository review

50K fresh input + 3K output tokens

Ling 3.0 Flash FP8
API rate not published
Fits in one request
Nemotron 3 Nano Omni 30B A3B
Self-hosted; infrastructure cost varies
Fits in one request

Ling 3.0 Flash FP8 has no comparable published API token rate. Nemotron 3 Nano Omni 30B A3B has no comparable published API token rate.

Cache-heavy agent loop

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

Ling 3.0 Flash FP8
API rate not published
Fits in one request
Cached-input rate unavailable
Nemotron 3 Nano Omni 30B A3B
Self-hosted; infrastructure cost varies
Fits in one request
Cached-input rate unavailable

Ling 3.0 Flash FP8 has no comparable published API token rate. Nemotron 3 Nano Omni 30B 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 FP8

Not sourced

Nemotron 3 Nano Omni 30B A3B

Not sourced

Cached-input rate

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

Ling 3.0 Flash FP8

No comparable hosted API rate

InclusionAI Ling 3.0 Flash FP8 model card

Nemotron 3 Nano Omni 30B A3B

No comparable hosted API rate

Documented inputs

Ling 3.0 Flash FP8

Not sourced

Nemotron 3 Nano Omni 30B A3B

Not sourced

Documented outputs

Ling 3.0 Flash FP8

Not sourced

Nemotron 3 Nano Omni 30B A3B

Not sourced

Provider availability

Ling 3.0 Flash FP8

Not sourced

Nemotron 3 Nano Omni 30B A3B

Not sourced

Reasoning profile

Ling 3.0 Flash FP8

Reasoning

Nemotron 3 Nano Omni 30B A3B

Reasoning

Weight access

Ling 3.0 Flash FP8

Open Weight

Nemotron 3 Nano Omni 30B A3B

Open Weight

License

Ling 3.0 Flash FP8

Open Weight

Nemotron 3 Nano Omni 30B A3B

Open Weight

Release date

Ling 3.0 Flash FP8

2026-08-04

Nemotron 3 Nano Omni 30B A3B

2026-04-28

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
Ling 3.0 Flash FP8 has the larger documented window (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 evidence16 rows

Agentic

  • OSWorld

    Ling 3.0 Flash FP8—
    Nemotron 3 Nano Omni 30B A3B47.4%
    Source

    Not directly comparable

  • τ²-bench results

    Ling 3.0 Flash FP8—
    Nemotron 3 Nano Omni 30B A3B45.3%
    Source

    Not directly comparable

Coding

  • SciCode

    Ling 3.0 Flash FP840.4%
    Source
    Nemotron 3 Nano Omni 30B A3B32%
    Source

    Ling 3.0 Flash FP8 leads this result

  • LiveCodeBench v5

    Ling 3.0 Flash FP8—
    Nemotron 3 Nano Omni 30B A3B63.2%
    Source

    Not directly comparable

Knowledge

  • GPQA

    Ling 3.0 Flash FP884%
    Source
    Nemotron 3 Nano Omni 30B A3B72.2%
    Source

    Ling 3.0 Flash FP8 leads this result

  • GPQA-D

    Ling 3.0 Flash FP884.0%
    Source
    Nemotron 3 Nano Omni 30B A3B72.2%
    Source

    Ling 3.0 Flash FP8 leads this result

  • MMLU-Pro

    Ling 3.0 Flash FP8—
    Nemotron 3 Nano Omni 30B A3B77.3%
    Source

    Not directly comparable

Math

  • AIME 2025

    Ling 3.0 Flash FP8—
    Nemotron 3 Nano Omni 30B A3B82.1%
    Source

    Not directly comparable

Multimodal

  • MMMU

    Ling 3.0 Flash FP8—
    Nemotron 3 Nano Omni 30B A3B70.8%
    Source

    Not directly comparable

  • MMLongBench-Doc

    Ling 3.0 Flash FP8—
    Nemotron 3 Nano Omni 30B A3B57.5%
    Source

    Not directly comparable

  • CharXiv

    Ling 3.0 Flash FP8—
    Nemotron 3 Nano Omni 30B A3B76.3%
    Source

    Not directly comparable

  • ScreenSpot Pro

    Ling 3.0 Flash FP8—
    Nemotron 3 Nano Omni 30B A3B57.8%
    Source

    Not directly comparable

  • Video-MME (w/o subtitle)

    Ling 3.0 Flash FP8—
    Nemotron 3 Nano Omni 30B A3B72.2%
    Source

    Not directly comparable

  • AI2D_TEST

    Ling 3.0 Flash FP8—
    Nemotron 3 Nano Omni 30B A3B88.5%
    Source

    Not directly comparable

  • RefCOCO (avg)

    Ling 3.0 Flash FP8—
    Nemotron 3 Nano Omni 30B A3B90.5%
    Source

    Not directly comparable

Instruction following

  • IFBench

    Ling 3.0 Flash FP873.4%
    Source
    Nemotron 3 Nano Omni 30B A3B74.2%
    Source

    Nemotron 3 Nano Omni 30B A3B leads this result

Frequently asked questions

Which is better, Ling 3.0 Flash FP8 or Nemotron 3 Nano Omni 30B A3B?

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, Ling 3.0 Flash FP8 or Nemotron 3 Nano Omni 30B A3B?

Ling 3.0 Flash FP8 leads the like-for-like coding comparison across 1 shared weighted benchmark row.

Which is better for agentic tasks, Ling 3.0 Flash FP8 or Nemotron 3 Nano Omni 30B A3B?

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, Ling 3.0 Flash FP8 or Nemotron 3 Nano Omni 30B 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 FP8 or Nemotron 3 Nano Omni 30B A3B?

Ling 3.0 Flash FP8 has the larger documented context window: 262K, compared with 256K.

Related comparisons

Compare API pricing Read the methodology Open the model selector

Last updated August 4, 2026

Watch Ling 3.0 Flash FP8 vs Nemotron 3 Nano Omni 30B A3B

One weekly email when material rank, price, or benchmark evidence changes make this matchup worth revisiting.

Read a sample issue

Join 2,000+ readers.