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Data

Ministral 3 14B (Reasoning) vs Nemotron 3.5 Super VL 120B A12B

Updated October 15, 2026. We do not rank this pair: at least one has no public score. Public scores include evidence status and uncertainty.

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Decision reading

The public evidence has no benchmark result shared by both models, so it does not support a quality verdict. Use the documented cost, context, and runtime rows instead. 0 results are shared. Category rows resting on Estimated evidence or different benchmark sets are marked directional and do not name a winner.

Model A
Mistral logo
Ministral 3 14B (Reasoning)

Mistral

—

Evidence status unavailable

90% interval unavailable

Model B
NVIDIA logo
Nemotron 3.5 Super VL 120B A12B

NVIDIA

49.51/100

Estimated · Public rank #97

Conditional range 35.2–63.9

Shared results
0
Ministral 3 14B (Reasoning) only
3
Nemotron 3.5 Super VL 120B A12B only
19
Like-for-like categories
0 / 8
Estimated: Nemotron 3.5 Super VL 120B A12B. Conditional ranges do not establish rank confidence.How the comparison works

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 Super VL 120B A12B

    Nemotron 3.5 Super VL 120B A12B 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

    Ministral 3 14B (Reasoning) and Nemotron 3.5 Super VL 120B A12B are not ranked on the public lane for coding, so no winner is named for coding.

    Confidence: limited

  • Agentic work

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

    Not enough matched evidence

    Ministral 3 14B (Reasoning) is not ranked on the public lane for agentic, so no winner is named for agentic.

    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: rate-fallback

  • 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

Which one for a specific job

Choose a job from the LLM Selector's task catalog to see the category row it rests on, under the same basis rules as the table below. A directional row stays directional; choosing a job never creates a winner.

The same task catalog as the LLM Selector. Each job names the evidence surface it rests on; nothing here adds a new score.

—Ministral 3 14B (Reasoning)—Nemotron 3.5 Super VL 120B A12B

Not comparable · BenchAlign v5.8

The coding row is not comparable on the public lane: at least one model is not measured or not ranked there.

Coding scores combine specific tasks and setups. Match the editor, harness, and effort to your workflow.

Open the coding leaderboardShortlist models for this job
Same basis rules as the category table below

What is actually comparable

Shared results can support a head-to-head reading. Results present for only one model describe coverage, not superiority.

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.

A shared-evidence shape is not available.

BenchLM does not draw a radar or infer missing axes when the matched evidence is too sparse.

Category results, on a stated basis

Each row shows the public-lane category score for both models: the BenchAlign v5.8 lane for agentic, coding, and knowledge, and the weighted public rows elsewhere, with the same rank each model page reports. A row is like-for-like only when both scores rest on Supported evidence or the same weighted set. Directional and not-comparable rows remain visible, but they never receive a winner.

Agentic

Not comparable
Ministral 3 14B (Reasoning)
Not ranked
Nemotron 3.5 Super VL 120B A12B
44.2
Estimated · #61/127
Basis
BenchAlign v5.8 lane · 0 vs 4 public rows
Reading
Not comparable

Coding

Not comparable
Ministral 3 14B (Reasoning)
Not ranked
Nemotron 3.5 Super VL 120B A12B
Not ranked
Basis
BenchAlign v5.8 lane · 0 vs 4 public rows
Reading
Not comparable

Reasoning

Not comparable
Ministral 3 14B (Reasoning)
Not ranked
Nemotron 3.5 Super VL 120B A12B
73.0
Unranked · 2 rankable rows
Basis
Provisional lane · 0 vs 0 weighted rows
Reading
Not comparable

Multimodal

Not comparable
Ministral 3 14B (Reasoning)
Not ranked
Nemotron 3.5 Super VL 120B A12B
62.0
Unranked · 5 rankable rows
Basis
Provisional lane · 0 vs 1 weighted rows
Reading
Not comparable

Knowledge

Not comparable
Ministral 3 14B (Reasoning)
Not ranked
Nemotron 3.5 Super VL 120B A12B
51.8
Estimated · #73/184
Basis
BenchAlign v5.8 lane · 1 vs 3 public rows
Reading
Not comparable

Multilingual

Not comparable
Ministral 3 14B (Reasoning)
Not ranked
Nemotron 3.5 Super VL 120B A12B
Not ranked
Basis
Provisional lane · 0 vs 0 weighted rows
Reading
Not comparable

Instruction following

Not comparable
Ministral 3 14B (Reasoning)
Not ranked
Nemotron 3.5 Super VL 120B A12B
66.6
#72/146
Basis
Provisional lane · 0 vs 1 weighted rows
Reading
Not comparable

Math

Not comparable
Ministral 3 14B (Reasoning)
Not ranked
Nemotron 3.5 Super VL 120B A12B
Not ranked
Basis
Provisional lane · 0 vs 0 weighted rows
Reading
Not comparable

Ranks count the models scored in each category’s lane, so the agentic, coding, and knowledge denominators (BenchAlign v5.8) differ from the provisional-lane categories. Unranked scores sit on the provisional lane’s scale but never name a winner. Like-for-like rows within 0.5 points read as a practical tie.

Bars run 0–100Methodology

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

Ministral 3 14B (Reasoning)
$0.0003
Fits in one request
Nemotron 3.5 Super VL 120B A12B
API rate not published
Fits in one request

Nemotron 3.5 Super VL 120B A12B has no comparable published API token rate.

Repository review

50K fresh input + 3K output tokens

Ministral 3 14B (Reasoning)
$0.0106
Fits in one request
Nemotron 3.5 Super VL 120B A12B
API rate not published
Fits in one request

Nemotron 3.5 Super VL 120B A12B has no comparable published API token rate.

Cache-heavy agent loop

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

Ministral 3 14B (Reasoning)
$0.046
Fits in one request
Cached input priced at the published list-input rate
Nemotron 3.5 Super VL 120B A12B
API rate not published
Fits in one request
Cached-input rate unavailable

Ministral 3 14B (Reasoning) has no published cached-input rate, so cached tokens use its listed input rate. Nemotron 3.5 Super VL 120B A12B has no comparable published API token rate.

Cached input falls back to the list input rate only where a cached rate is unpublished

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.

Ministral 3 14B (Reasoning)

256K

Nemotron 3.5 Super VL 120B A12B

1M

NVIDIA BF16 model card

API model ID

Ministral 3 14B (Reasoning)

Not sourced

Nemotron 3.5 Super VL 120B A12B

Not sourced

Cached-input rate

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

Ministral 3 14B (Reasoning)

Not published

Nemotron 3.5 Super VL 120B A12B

No comparable hosted API rate

NVIDIA Hugging Face model card

Documented inputs

Ministral 3 14B (Reasoning)

Not sourced

Nemotron 3.5 Super VL 120B A12B

text, image, video

NVIDIA BF16 model card

Documented outputs

Ministral 3 14B (Reasoning)

Not sourced

Nemotron 3.5 Super VL 120B A12B

text

NVIDIA BF16 model card

Provider availability

Ministral 3 14B (Reasoning)

Not sourced

Nemotron 3.5 Super VL 120B A12B

Open Weights · Hugging Face, self-hosted inference

NVIDIA BF16 model card

Reasoning profile

Ministral 3 14B (Reasoning)

Reasoning

Nemotron 3.5 Super VL 120B A12B

Reasoning

Weight access

Ministral 3 14B (Reasoning)

Open Weight

Nemotron 3.5 Super VL 120B A12B

Open Weight

License

Ministral 3 14B (Reasoning)

Open Weight

Nemotron 3.5 Super VL 120B A12B

Open Weight

Release date

Ministral 3 14B (Reasoning)

2025-12-02

Nemotron 3.5 Super VL 120B A12B

2026-10-15

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
The public evidence has no benchmark result shared by both models, so it does not support a quality verdict.
Workload cost
A complete comparable API-rate estimate is not available for both models.
Context tradeoff
Nemotron 3.5 Super VL 120B A12B has the larger documented window (1M).
Run the same representative tasks against both endpoints before changing production traffic.

Questions

Which is better, Ministral 3 14B (Reasoning) or Nemotron 3.5 Super VL 120B A12B?

The public evidence has no benchmark result shared by both models, so it does not support a quality verdict. The page therefore keeps the decision tied to the specific documented workload.

Which is better for coding, Ministral 3 14B (Reasoning) or Nemotron 3.5 Super VL 120B A12B?

Ministral 3 14B (Reasoning) and Nemotron 3.5 Super VL 120B A12B are not ranked on the public lane for coding, so no winner is named for coding.

Which is better for agentic tasks, Ministral 3 14B (Reasoning) or Nemotron 3.5 Super VL 120B A12B?

Ministral 3 14B (Reasoning) is not ranked on the public lane for agentic tasks, so no winner is named for agentic tasks.

Which costs less, Ministral 3 14B (Reasoning) or Nemotron 3.5 Super VL 120B A12B?

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, Ministral 3 14B (Reasoning) or Nemotron 3.5 Super VL 120B A12B?

Nemotron 3.5 Super VL 120B A12B has the larger documented context window: 1M, compared with 256K.

Benchmark evidence

The full public result ledger is available for audit without forcing a wide desktop table onto a phone.

Browse raw public benchmark evidence22 rows

Agentic

  • Terminal-Bench 2.1

    Ministral 3 14B (Reasoning)—
    Nemotron 3.5 Super VL 120B A12B66.7%
    Source

    Not directly comparable

  • τ²-bench Airline

    Ministral 3 14B (Reasoning)—
    Nemotron 3.5 Super VL 120B A12B76.5%
    Source

    Not directly comparable

  • τ³-bench results

    Ministral 3 14B (Reasoning)—
    Nemotron 3.5 Super VL 120B A12B18.9%
    Source

    Not directly comparable

  • BrowseComp

    Ministral 3 14B (Reasoning)—
    Nemotron 3.5 Super VL 120B A12B78%
    Source

    Not directly comparable

Coding

  • LiveCodeBench v6

    Ministral 3 14B (Reasoning)—
    Nemotron 3.5 Super VL 120B A12B88.2%
    Source

    Not directly comparable

  • SWE-bench Verified

    Ministral 3 14B (Reasoning)—
    Nemotron 3.5 Super VL 120B A12B71.1%
    Source

    Not directly comparable

  • SWE Multilingual

    Ministral 3 14B (Reasoning)—
    Nemotron 3.5 Super VL 120B A12B67.7%
    Source

    Not directly comparable

  • SWE-bench Pro

    Ministral 3 14B (Reasoning)—
    Nemotron 3.5 Super VL 120B A12B51.8%
    Source

    Not directly comparable

Reasoning

  • CritPt

    Ministral 3 14B (Reasoning)—
    Nemotron 3.5 Super VL 120B A12B10.9%
    Source

    Not directly comparable

Multimodal

  • BabyVision

    Ministral 3 14B (Reasoning)—
    Nemotron 3.5 Super VL 120B A12B29.6%
    Source

    Not directly comparable

  • MMLongBench-Doc

    Ministral 3 14B (Reasoning)—
    Nemotron 3.5 Super VL 120B A12B62.8%
    Source

    Not directly comparable

  • V*

    Ministral 3 14B (Reasoning)—
    Nemotron 3.5 Super VL 120B A12B85.6%
    Source

    Not directly comparable

  • MathVision

    Ministral 3 14B (Reasoning)—
    Nemotron 3.5 Super VL 120B A12B78.2%
    Source

    Not directly comparable

  • CharXiv

    Ministral 3 14B (Reasoning)—
    Nemotron 3.5 Super VL 120B A12B80.8%
    Source

    Not directly comparable

Knowledge

  • GPQA

    Ministral 3 14B (Reasoning)71.2%
    Source
    Nemotron 3.5 Super VL 120B A12B—

    Not directly comparable

  • GPQA-D

    Ministral 3 14B (Reasoning)—
    Nemotron 3.5 Super VL 120B A12B89.5%
    Source

    Not directly comparable

  • HLE w/o tools

    Ministral 3 14B (Reasoning)—
    Nemotron 3.5 Super VL 120B A12B31.8%
    Source

    Not directly comparable

  • HLE

    Ministral 3 14B (Reasoning)—
    Nemotron 3.5 Super VL 120B A12B29.2%
    Source

    Not directly comparable

Instruction following

  • IFBench

    Ministral 3 14B (Reasoning)—
    Nemotron 3.5 Super VL 120B A12B70.9%
    Source

    Not directly comparable

Math

  • AIME 2024

    Ministral 3 14B (Reasoning)89.8%
    Source
    Nemotron 3.5 Super VL 120B A12B—

    Not directly comparable

  • AIME 2025

    Ministral 3 14B (Reasoning)85%
    Source
    Nemotron 3.5 Super VL 120B A12B—

    Not directly comparable

  • Apex Shortlist

    Ministral 3 14B (Reasoning)—
    Nemotron 3.5 Super VL 120B A12B88.4%
    Source

    Not directly comparable

22 public results · 0 shared

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Last updated October 15, 2026