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Model comparison

Laguna M.1 vs Nemotron 3.5 Lightning 30B A3B NVFP4

Updated August 11, 2026. Public scores include evidence status and uncertainty. They are not guarantees for a specific workload.

Laguna M.1

Poolside

—

Evidence status unavailable

90% interval unavailable

Nemotron 3.5 Lightning 30B A3B NVFP4

NVIDIA

26.9/100

Estimated · Public rank #204

90% interval 17.1–36.8

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.

  • Long documents

    Prompts that approach the documented context limit

    Nemotron 3.5 Lightning 30B A3B NVFP4

    Nemotron 3.5 Lightning 30B A3B NVFP4 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
4
Laguna M.1 only
1
Nemotron 3.5 Lightning 30B A3B NVFP4 only
9
Like-for-like categories
0 / 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.

Agentic

Directional only
Laguna M.1
45.8
Nemotron 3.5 Lightning 30B A3B NVFP4
29.1
Weighted basis
1 vs 2 rows
Reading
Directional only

Coding

Directional only
Laguna M.1
64.8
Nemotron 3.5 Lightning 30B A3B NVFP4
42.1
Weighted basis
2 vs 2 rows
Reading
Directional only

Reasoning

Not comparable
Laguna M.1
Not measured
Nemotron 3.5 Lightning 30B A3B NVFP4
Not measured
Weighted basis
0 vs 0 rows
Reading
Not comparable

Knowledge

Not comparable
Laguna M.1
Not measured
Nemotron 3.5 Lightning 30B A3B NVFP4
80.5
Weighted basis
0 vs 2 rows
Reading
Not comparable

Math

Not comparable
Laguna M.1
Not measured
Nemotron 3.5 Lightning 30B A3B NVFP4
Not measured
Weighted basis
0 vs 0 rows
Reading
Not comparable

Multilingual

Not comparable
Laguna M.1
Not measured
Nemotron 3.5 Lightning 30B A3B NVFP4
Not measured
Weighted basis
0 vs 0 rows
Reading
Not comparable

Multimodal

Not comparable
Laguna M.1
Not measured
Nemotron 3.5 Lightning 30B A3B NVFP4
Not measured
Weighted basis
0 vs 0 rows
Reading
Not comparable

Instruction following

Not comparable
Laguna M.1
Not measured
Nemotron 3.5 Lightning 30B A3B NVFP4
72.9
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

Laguna M.1
API rate not published
Fits in one request
Nemotron 3.5 Lightning 30B A3B NVFP4
Self-hosted; infrastructure cost varies
Fits in one request

Laguna M.1 has no comparable published API token rate. Nemotron 3.5 Lightning 30B A3B NVFP4 has no comparable published API token rate.

Repository review

50K fresh input + 3K output tokens

Laguna M.1
API rate not published
Fits in one request
Nemotron 3.5 Lightning 30B A3B NVFP4
Self-hosted; infrastructure cost varies
Fits in one request

Laguna M.1 has no comparable published API token rate. Nemotron 3.5 Lightning 30B A3B NVFP4 has no comparable published API token rate.

Cache-heavy agent loop

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

Laguna M.1
API rate not published
Fits in one request
Cached-input rate unavailable
Nemotron 3.5 Lightning 30B A3B NVFP4
Self-hosted; infrastructure cost varies
Fits in one request
Cached-input rate unavailable

Laguna M.1 has no comparable published API token rate. Nemotron 3.5 Lightning 30B A3B NVFP4 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

Laguna M.1

Not sourced

Nemotron 3.5 Lightning 30B A3B NVFP4

Not sourced

Cached-input rate

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

Laguna M.1

No comparable hosted API rate

Nemotron 3.5 Lightning 30B A3B NVFP4

No comparable hosted API rate

NVIDIA Nemotron 3.5 Lightning model card

Documented inputs

Laguna M.1

Not sourced

Nemotron 3.5 Lightning 30B A3B NVFP4

Not sourced

Documented outputs

Laguna M.1

Not sourced

Nemotron 3.5 Lightning 30B A3B NVFP4

Not sourced

Provider availability

Laguna M.1

Not sourced

Nemotron 3.5 Lightning 30B A3B NVFP4

Not sourced

Reasoning profile

Laguna M.1

Reasoning

Nemotron 3.5 Lightning 30B A3B NVFP4

Reasoning

Weight access

Laguna M.1

Proprietary

Nemotron 3.5 Lightning 30B A3B NVFP4

Open Weight

License

Laguna M.1

Proprietary

Nemotron 3.5 Lightning 30B A3B NVFP4

Open Weight

Release date

Laguna M.1

2026-04-28

Nemotron 3.5 Lightning 30B A3B NVFP4

2026-08-11

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
Nemotron 3.5 Lightning 30B A3B NVFP4 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 evidence14 rows

Agentic

  • Terminal-Bench 2.0

    Laguna M.145.8%
    Source
    Nemotron 3.5 Lightning 30B A3B NVFP423.5%
    Source

    Laguna M.1 leads this result

  • PinchBench

    Laguna M.1—
    Nemotron 3.5 Lightning 30B A3B NVFP483.4%
    Source

    Not directly comparable

  • BrowseComp

    Laguna M.1—
    Nemotron 3.5 Lightning 30B A3B NVFP436.8%
    Source

    Not directly comparable

  • τ³-bench results

    Laguna M.1—
    Nemotron 3.5 Lightning 30B A3B NVFP49.5%
    Source

    Not directly comparable

Coding

  • SWE-bench Verified

    Laguna M.174.6%
    Source
    Nemotron 3.5 Lightning 30B A3B NVFP452.8%
    Source

    Laguna M.1 leads this result

  • SWE Multilingual

    Laguna M.163.1%
    Source
    Nemotron 3.5 Lightning 30B A3B NVFP436.5%
    Source

    Laguna M.1 leads this result

  • SWE-bench Pro

    Laguna M.149.2%
    Source
    Nemotron 3.5 Lightning 30B A3B NVFP4—

    Not directly comparable

  • Terminal-Bench 2.0

    Laguna M.145.8%
    Source
    Nemotron 3.5 Lightning 30B A3B NVFP423.5%
    Source

    Laguna M.1 leads this result

  • SciCode

    Laguna M.1—
    Nemotron 3.5 Lightning 30B A3B NVFP431.4%
    Source

    Not directly comparable

Knowledge

  • GPQA

    Laguna M.1—
    Nemotron 3.5 Lightning 30B A3B NVFP475.6%
    Source

    Not directly comparable

  • GPQA-D

    Laguna M.1—
    Nemotron 3.5 Lightning 30B A3B NVFP475.6%
    Source

    Not directly comparable

  • HLE w/o tools

    Laguna M.1—
    Nemotron 3.5 Lightning 30B A3B NVFP410.5%
    Source

    Not directly comparable

  • MMLU-Pro

    Laguna M.1—
    Nemotron 3.5 Lightning 30B A3B NVFP481.6%
    Source

    Not directly comparable

Instruction following

  • IFBench

    Laguna M.1—
    Nemotron 3.5 Lightning 30B A3B NVFP472.9%
    Source

    Not directly comparable

Frequently asked questions

Which is better, Laguna M.1 or Nemotron 3.5 Lightning 30B A3B NVFP4?

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, Laguna M.1 or Nemotron 3.5 Lightning 30B A3B NVFP4?

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, Laguna M.1 or Nemotron 3.5 Lightning 30B A3B NVFP4?

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, Laguna M.1 or Nemotron 3.5 Lightning 30B A3B NVFP4?

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, Laguna M.1 or Nemotron 3.5 Lightning 30B A3B NVFP4?

Nemotron 3.5 Lightning 30B A3B NVFP4 has the larger documented context window: 1M, compared with 256K.

Related comparisons

Compare API pricing Read the methodology Open the model selector

Last updated August 11, 2026

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