SSyncDev

AI model comparison

Nemotron Nano 9B v2 vs Grok 4 1 Fast Reasoning

Compare recorded price, context, output limits, speed, latency, capabilities, and input/output support. Every missing value stays visible, and unsourced benchmarks are excluded.

This Nemotron Nano 9B v2 vs Grok 4 1 Fast Reasoning comparison is designed for teams choosing between two production model records, not for declaring a universal winner. Nemotron Nano 9B v2 by NVIDIA currently records 131.1K context, 131.1K maximum output, $0.06 input per 1M tokens, $0.23 output per 1M tokens. Grok 4 1 Fast Reasoning by Xai via Requesty records 2M context, 30K maximum output, $0.20 input per 1M tokens, $0.50 output per 1M tokens. The tables below separate documented capabilities, commercial limits, directory measurements, and source-linked benchmark evidence so you can see where the data is complete and where independent testing is still required.

Side-by-sideSpecs and pricing, compared

NVIDIA

Nemotron Nano 9B v2

Compact Nemotron model for efficient reasoning and deployable AI agents

Context
131.1K
Max output
131.1K
Input / 1M
$0.06
Output / 1M
$0.23
Output speed
—

Accepts

  • Text input

Produces

  • Text output
Full model profileVendor docs ↗
VS

Xai via Requesty

Grok 4 1 Fast Reasoning

A frontier multimodal model optimized specifically for high-performance agentic tool calling.

Context
2M
Max output
30K
Input / 1M
$0.20
Output / 1M
$0.50
Output speed
—

Accepts

  • Text input
  • Image input

Produces

  • Text output
Full model profileVendor docs ↗

At a glance

Decision snapshot

This is a directional summary of the values recorded in this directory—not a universal quality verdict. Test the finalists on your own prompts before committing.

Where Nemotron Nano 9B v2 leads in recorded data

  • Maximum output: 131.1K
  • Input price: $0.06
  • Output price: $0.23

Where Grok 4 1 Fast Reasoning leads in recorded data

  • Context capacity: 2M

Context capacity

Higher listed limit

Nemotron Nano 9B v2:131.1K

Grok 4 1 Fast Reasoning:2M

Grok 4 1 Fast Reasoning

Maximum output

Higher listed limit

Nemotron Nano 9B v2:131.1K

Grok 4 1 Fast Reasoning:30K

Nemotron Nano 9B v2

Input price

Lower recorded price

Nemotron Nano 9B v2:$0.06

Grok 4 1 Fast Reasoning:$0.20

Nemotron Nano 9B v2

Output price

Lower recorded price

Nemotron Nano 9B v2:$0.23

Grok 4 1 Fast Reasoning:$0.50

Nemotron Nano 9B v2

Output speed

Higher recorded throughput

Nemotron Nano 9B v2:—

Grok 4 1 Fast Reasoning:—

No complete comparison

Time to first token

Lower recorded latency

Nemotron Nano 9B v2:—

Grok 4 1 Fast Reasoning:—

No complete comparison

Intelligence Index

Higher directory index

Nemotron Nano 9B v2:—

Grok 4 1 Fast Reasoning:—

No complete comparison

Evidence

Verified shared benchmarks

A score appears only when both records include a verified source. It is not treated as a universal ranking.

These two models haven't been measured on the same benchmark yet, so there's nothing meaningful to chart. Comparing scores from different tests would tell you more about the tests than the models — the specs and pricing above are the better guide here.

Specifications

Pricing, limits and capabilities

SpecificationNemotron Nano 9B v2Grok 4 1 Fast Reasoning
ProviderNVIDIAXai via Requesty
Model familynemotron—
Accepted inputstexttext, image
Produced outputstexttext
Context window131.1K2MRecorded lead
Max output131.1KRecorded lead30K
Intelligence Index——
Input price / 1M$0.06Recorded lead$0.20
Output price / 1M$0.23Recorded lead$0.50
Output speed——
Time to first token——
Reasoning modeDocumentedDocumented
Tool callingDocumentedDocumented
Image inputNot documentedDocumented
Audio inputNot documentedNot documented
Structured outputNot documentedDocumented
LicenseOpen weightsNot documented
ReleasedAug 18, 2025Nov 19, 2025

Workload guidance

Which model should you choose?

Nemotron Nano 9B v2 currently leads on larger maximum output, lower recorded input price, lower recorded output price. Grok 4 1 Fast Reasoning currently leads on larger context. Choose according to the constraints that matter to your workload, then run the same representative prompts against both models before making a production commitment. Neither the larger number nor the lower price is automatically the better choice: prompt quality, tool reliability, modality support, rate limits, data policy, and provider implementation can change the result. Use this page to build a shortlist, confirm current terms in the linked sources, and validate quality, latency, and cost with your own traffic.

Provenance

Sources and data limits

Prices and hosted performance can change. SyncDev records source references and clearly separates documented specifications from measured values; confirm commercial terms with the provider before deployment.

Questions people ask

It compares recorded context and output limits, token prices, output speed, time to first token, Intelligence Index, modality support, tool and structured-output capabilities, release information, and only source-linked benchmarks verified on both records. Missing information is labeled rather than inferred.

Compare a different pair

Choose any two approved model records and review them with the same evidence rules.

Open model comparison