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Comparison · 3 models · Updated Oct 4, 2026

Nemotron Nano 12B v2 VL vs Grok 4.1 Fast vs Ministral 3 14B

Grok 4.1 Fast comes out ahead, 71 to 63 and 63 on our weighted score, and it is the cheaper option too.

  1. NVIDIA

    Nemotron Nano 12B v2 VL

    Released Oct 28, 2025Deprecated

    63/100
    • ECI—
    • Price$0.20 / $0.60
    • Context128K
  2. Our pick

    xAI

    Grok 4.1 Fast

    Released Nov 19, 2025

    71/100
    • ECI—
    • Price$0.20 / $0.50
    • Context2M
  3. Mistral AI

    Ministral 3 14B

    Released Dec 2, 2025

    63/100
    • ECI—
    • Price$0.268 / $0.325
    • Context262K
01 — Verdict

Grok 4.1 Fast is our pick

Grok 4.1 Fast is the better all-round choice, scoring 71/100 against Ministral 3 14B (63) and Nemotron Nano 12B v2 VL (63). It leads on context window. Nemotron Nano 12B v2 VL wins on inputs & features. The score weighs price 50%, inputs & features 30%, context window 20%. None of the shared benchmarks cover every model here yet, so capability is left out of this verdict.

  • CapabilityNot enough dataNo independent benchmark covers every model here yet
  • Lowest priceGrok 4.1 FastGrok 4.1 Fast $0.275 · Ministral 3 14B $0.282 · Nemotron Nano 12B v2 VL $0.30 per 1M tokens (3:1 blend)
  • Longest contextGrok 4.1 FastGrok 4.1 Fast 2,000,000 · Ministral 3 14B 262,144 · Nemotron Nano 12B v2 VL 128,000 tokens
  • Widest inputsNemotron Nano 12B v2 VLNemotron Nano 12B v2 VL: Text, Images, Video · Grok 4.1 Fast: Text, Images · Ministral 3 14B: Text, Images
  • Self-hostingNemotron Nano 12B v2 VL and Ministral 3 14BPublishes downloadable weights (Apache 2.0)
How the score is built
MeasureWeightNemotron Nano 12B v2 VLGrok 4.1 FastMinistral 3 14B
Price50%757676
Inputs & features30%706060
Context window20%247237
Overall100%63/10071/10063/100

Left out because at least one model lacks the data: capability. The remaining weights were rescaled.

02 — Side by side

Every spec in one table

Highlighted cells lead their row. Dashes mean the data is not published.

Nemotron Nano 12B v2 VL vs Grok 4.1 Fast vs Ministral 3 14B specifications side by side
SpecificationNemotron Nano 12B v2 VLNVIDIAGrok 4.1 FastxAIMinistral 3 14BMistral AI
Capability
Capabilities Index (ECI)———
ECI rank———
Price per million tokens
Input$0.20 (best)$0.20 (best)$0.268
Output$0.60$0.50$0.325 (best)
Cached input———
Blended (3:1)$0.30$0.275 (best)$0.282
Long-context rateSame rateSame rateSame rate
Price sourceMedian of 3 providersMedian of 2 providersMedian of 2 providers
Limits
Context window128,000 tokens2,000,000 tokens (best)262,144 tokens
Max output128,000 tokens30,000 tokens262,144 tokens (best)
Inputs and features
TextYesYesYes
ImagesYesYesYes
PDFsNoNoNo
AudioNoNoNo
VideoYesNoNo
ReasoningYesNoNo
Tool callingYesYesYes
Structured outputNoYesYes
Availability
WeightsOpenProprietaryOpenApache 2.0
API model IDnvidia/nemotron-nano-12b-v2-vl——
API providers4 (best)22
ReleasedOct 28, 2025Nov 19, 2025Dec 2, 2025
Knowledge cutoff———
03 — Cost

What would a month cost?

Enter your expected volume in millions of tokens. List prices only; caching and batch discounts would lower these.

  • Nemotron Nano 12B v2 VL$3.20
  • Grok 4.1 Fast$3.00
  • Ministral 3 14B$3.33
04 — Questions

Which should you choose?

Which is better: Nemotron Nano 12B v2 VL, Grok 4.1 Fast or Ministral 3 14B?

Grok 4.1 Fast is the better all-round choice, scoring 71/100 against Ministral 3 14B (63) and Nemotron Nano 12B v2 VL (63). It leads on context window. Nemotron Nano 12B v2 VL wins on inputs & features. The score weighs price 50%, inputs & features 30%, context window 20%. None of the shared benchmarks cover every model here yet, so capability is left out of this verdict.

Which is cheaper, Nemotron Nano 12B v2 VL, Grok 4.1 Fast or Ministral 3 14B?

Grok 4.1 Fast is cheaper at $0.20 input / $0.50 output per million tokens (median across 2 API providers). Ministral 3 14B costs $0.268 input / $0.325 output per million tokens (median across 2 API providers); Nemotron Nano 12B v2 VL costs $0.20 input / $0.60 output per million tokens (median across 3 API providers; free on Nvidia). At a typical mix of three input tokens to one output token, that is $0.275 per million tokens for Grok 4.1 Fast versus $0.282 for Ministral 3 14B (1× as much) and $0.30 for Nemotron Nano 12B v2 VL (1.1× as much).

Which scores higher on benchmarks?

There is no independent benchmark that covers all three models yet. Nemotron Nano 12B v2 VL has not been scored yet, Grok 4.1 Fast has not been scored yet and Ministral 3 14B has not been scored yet.

Which is better for coding?

There are no published SWE-bench Verified results for Nemotron Nano 12B v2 VL, Grok 4.1 Fast and Ministral 3 14B yet, so there is no like-for-like coding score. Test both on a sample of your own tasks. All three support tool calling for agent workflows.

Which has the bigger context window?

Grok 4.1 Fast has the largest context window at 2,000,000 tokens, against 262,144 for Ministral 3 14B and 128,000 for Nemotron Nano 12B v2 VL. Maximum output per response: Nemotron Nano 12B v2 VL up to 128,000, Grok 4.1 Fast up to 30,000, Ministral 3 14B up to 262,144 tokens.

Which can read images, PDFs, audio or video?

Nemotron Nano 12B v2 VL accepts text, images and video; Grok 4.1 Fast accepts text and images; Ministral 3 14B accepts text and images. Nemotron Nano 12B v2 VL handles the widest range of inputs.

Are any of these open source?

Nemotron Nano 12B v2 VL and Ministral 3 14B publishes its weights (Apache 2.0) and can be self-hosted; Grok 4.1 Fast is proprietary.

Which is newer?

Ministral 3 14B is the newest, released Dec 2, 2025. Grok 4.1 Fast came out Nov 19, 2025; Nemotron Nano 12B v2 VL came out Oct 28, 2025.

How do you decide the winner?

Each model gets a 0–100 score on capability (50%, independent benchmark results); price (25%, blended price per million tokens (3 input : 1 output), log scale); inputs & features (15%, image, PDF, audio and video input, tool calling, structured output and reasoning); context window (10%, maximum tokens per request, log scale). Dimensions missing for any model are dropped and the remaining weights rescaled, so every model is judged on the same evidence. Specs and prices come from public model listings and the labs’ own API pages; capability scores come from independent benchmark runs. Data updated Oct 4, 2026.