SSyncDev

AI model comparison

Gemini 1.5 Pro vs Llama 3.3 Nemotron Super 49B v1.5

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

This Gemini 1.5 Pro vs Llama 3.3 Nemotron Super 49B v1.5 comparison is designed for teams choosing between two production model records, not for declaring a universal winner. Gemini 1.5 Pro by Google currently records 2M context, 8.2K maximum output, $1.25 input per 1M tokens, $5.00 output per 1M tokens, 65 t/s recorded output speed, 0.90s recorded time to first token. Llama 3.3 Nemotron Super 49B v1.5 by NVIDIA records 131.1K context, 131.1K maximum output, $0.00 input per 1M tokens, $0.00 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

Google

Gemini 1.5 Pro

Google's long-context multimodal model with up to 2M token windows.

Context
2M
Max output
8.2K
Input / 1M
$1.25
Output / 1M
$5.00
Output speed
65 t/s

Accepts

  • Text input
  • Image input
  • Audio input
  • Video input

Produces

  • Text output
Full model profileVendor docs ↗
VS

NVIDIA

Llama 3.3 Nemotron Super 49B v1.5

Nemotron model for efficient reasoning, coding, and specialized AI agents

Context
131.1K
Max output
131.1K
Input / 1M
$0.00
Output / 1M
$0.00
Output speed
—

Accepts

  • Text 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 Gemini 1.5 Pro leads in recorded data

  • Context capacity: 2M

Where Llama 3.3 Nemotron Super 49B v1.5 leads in recorded data

  • Maximum output: 131.1K
  • Input price: $0.00
  • Output price: $0.00

Context capacity

Higher listed limit

Gemini 1.5 Pro:2M

Llama 3.3 Nemotron Super 49B v1.5:131.1K

Gemini 1.5 Pro

Maximum output

Higher listed limit

Gemini 1.5 Pro:8.2K

Llama 3.3 Nemotron Super 49B v1.5:131.1K

Llama 3.3 Nemotron Super 49B v1.5

Input price

Lower recorded price

Gemini 1.5 Pro:$1.25

Llama 3.3 Nemotron Super 49B v1.5:$0.00

Llama 3.3 Nemotron Super 49B v1.5

Output price

Lower recorded price

Gemini 1.5 Pro:$5.00

Llama 3.3 Nemotron Super 49B v1.5:$0.00

Llama 3.3 Nemotron Super 49B v1.5

Output speed

Higher recorded throughput

Gemini 1.5 Pro:65 t/s

Llama 3.3 Nemotron Super 49B v1.5:—

No complete comparison

Time to first token

Lower recorded latency

Gemini 1.5 Pro:0.90s

Llama 3.3 Nemotron Super 49B v1.5:—

No complete comparison

Intelligence Index

Higher directory index

Gemini 1.5 Pro:75.8

Llama 3.3 Nemotron Super 49B v1.5:—

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

SpecificationGemini 1.5 ProLlama 3.3 Nemotron Super 49B v1.5
ProviderGoogleNVIDIA
Model familyGemini 1.5nemotron
Accepted inputstext, image, audio, videotext
Produced outputstexttext
Context window2MRecorded lead131.1K
Max output8.2K131.1KRecorded lead
Intelligence Index75.8—
Input price / 1M$1.25$0.00Recorded lead
Output price / 1M$5.00$0.00Recorded lead
Output speed65 t/s—
Time to first token0.90s—
Reasoning modeNot documentedDocumented
Tool callingDocumentedDocumented
Image inputDocumentedNot documented
Audio inputDocumentedNot documented
Structured outputDocumentedNot documented
LicenseProprietaryOpen weights
ReleasedMay 14, 2024Jul 25, 2025

Workload guidance

Which model should you choose?

Gemini 1.5 Pro currently leads on larger context. Llama 3.3 Nemotron Super 49B v1.5 currently leads on larger maximum output, lower recorded input price, lower recorded output price. 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