AI model comparison

Nano Banana Pro vs Qwen/Qwen-Image

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

This Nano Banana Pro vs Qwen/Qwen-Image comparison is designed for teams choosing between two production model records, not for declaring a universal winner. Nano Banana Pro by Google currently records 65.5K context, 32.8K maximum output, $2.00 input per 1M tokens, $120.00 output per 1M tokens. Qwen/Qwen-Image by Qwen records 8.2K context, 4.1K maximum output, $0.50 input per 1M tokens, $2.00 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

Nano Banana Pro

Nano Banana Pro for higher-fidelity image generation and design-heavy edits

Context
65.5K
Max output
32.8K
Input / 1M
$2.00
Output / 1M
$120.00
Output speed

Accepts

  • Text input
  • Image input

Produces

  • Text output
  • Image output
VS

Qwen

Qwen/Qwen-Image

Qwen/Qwen-Image is a source-linked Hugging Face repository assigned to Text-to-image. Its recorded task interface accepts text and produces image.

Context
8.2K
Max output
4.1K
Input / 1M
$0.50
Output / 1M
$2.00
Output speed

Accepts

  • Text input

Produces

  • Image output

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 Nano Banana Pro leads in recorded data

  • Context capacity: 65.5K
  • Maximum output: 32.8K

Where Qwen/Qwen-Image leads in recorded data

  • Input price: $0.50
  • Output price: $2.00

Context capacity

Higher listed limit

Nano Banana Pro:65.5K

Qwen/Qwen-Image:8.2K

Nano Banana Pro

Maximum output

Higher listed limit

Nano Banana Pro:32.8K

Qwen/Qwen-Image:4.1K

Nano Banana Pro

Input price

Lower recorded price

Nano Banana Pro:$2.00

Qwen/Qwen-Image:$0.50

Qwen/Qwen-Image

Output price

Lower recorded price

Nano Banana Pro:$120.00

Qwen/Qwen-Image:$2.00

Qwen/Qwen-Image

Output speed

Higher recorded throughput

Nano Banana Pro:

Qwen/Qwen-Image:

No complete comparison

Time to first token

Lower recorded latency

Nano Banana Pro:

Qwen/Qwen-Image:

No complete comparison

Intelligence Index

Higher directory index

Nano Banana Pro:

Qwen/Qwen-Image:

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

SpecificationNano Banana ProQwen/Qwen-Image
ProviderGoogleQwen
Model familygemini-pro
Accepted inputstext, imagetext
Produced outputstext, imageimage
Context window65.5KRecorded lead8.2K
Max output32.8KRecorded lead4.1K
Intelligence Index
Input price / 1M$2.00$0.50Recorded lead
Output price / 1M$120.00$2.00Recorded lead
Output speed
Time to first token
Reasoning modeDocumentedNot documented
Tool callingNot documentedNot documented
Image inputDocumentedNot documented
Audio inputNot documentedNot documented
Structured outputNot documentedNot documented
LicenseProprietaryNot documented
ReleasedMay 28, 2026Mar 1, 2026

Workload guidance

Which model should you choose?

Nano Banana Pro currently leads on larger context, larger maximum output. Qwen/Qwen-Image currently leads on 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