Google: Gemini 3 Pro Preview vs nvidia/bigvgan_v2_22khz_80band_256x

Google: Gemini 3 Pro Preview comes out ahead on the data we track: 6 advantages and none for nvidia/bigvgan_v2_22khz_80band_256x.

Key numbers

SpecGoogle: Gemini 3 Pro Previewnvidia/bigvgan_v2_22khz_80band_256x
ProviderGoogleHugging Face
Input price (per 1M tokens)$2.00n/a
Output price (per 1M tokens)$12.00n/a
Blended price (3:1 input/output)$4.50n/a
Cheaper than … of all models we track12%n/a
Context window1.0M tokens (~1,573 pages)n/a
Larger context than … of all models81%n/a
Max output per response66K tokens (~49,200 words)n/a
Input typestext, image, file, audio, videoaudio
Output typestextaudio
Free variantNoNo
Listed since2025-11-18n/a
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What it costs for real workloads

Monthly cost at list price for five common workloads. Token counts per unit are stated so you can scale them to your own traffic. A workload that does not fit a model's context window is marked rather than priced.

Workload (per month)Google: Gemini 3 Pro Previewnvidia/bigvgan_v2_22khz_80band_256xDifference
Customer-support chatbot
50,000 conversations — each a 6-turn conversation (1,500 in / 400 out tokens)
$390n/a—
RAG search over documents
20,000 questions — each a question answered from ~8 retrieved passages (6,000 in / 500 out tokens)
$360n/a—
Coding / tool-using agent
2,000 tasks — each a multi-step task with tool calls and file context (60,000 in / 6,000 out tokens)
$384n/a—
Batch summarisation
10,000 documents — each a 6,000-word report summarised to a page (8,000 in / 600 out tokens)
$232n/a—
Long-document analysis
500 documents — each a 150-page contract or codebase read in one pass (100,000 in / 2,000 out tokens)
$112n/a—

Capabilities side by side

CapabilityGoogle: Gemini 3 Pro Previewnvidia/bigvgan_v2_22khz_80band_256xWhat it lets you do
Tool / function calling✓ Yes—call your APIs and run agent loops
Structured output (JSON schema)✓ Yes—return JSON that validates against your schema
Reasoning / thinking mode✓ Yes—spend extra tokens thinking before answering hard problems
Image input✓ Yes—read screenshots, charts and scanned pages
Audio input✓ Yes✓ Yestake speech or audio directly
File / PDF input✓ Yes—accept documents without your own parsing step
Image output——generate images, not just text
Built-in web search——answer from live web results
Seed (reproducible sampling)✓ Yes—repeat a generation for tests and evals
Log-probabilities——read token confidence for classification and scoring

From each model's published parameters and input/output types. “—” means not advertised, not proven absent.

Price history

Which should you choose?

Choose Google: Gemini 3 Pro Preview if…

  • you need tool / function calling — to call your APIs and run agent loops; nvidia/bigvgan_v2_22khz_80band_256x does not advertise it
  • you need structured output (JSON schema) — to return JSON that validates against your schema; nvidia/bigvgan_v2_22khz_80band_256x does not advertise it
  • you need reasoning / thinking mode — to spend extra tokens thinking before answering hard problems; nvidia/bigvgan_v2_22khz_80band_256x does not advertise it
  • you need image input — to read screenshots, charts and scanned pages; nvidia/bigvgan_v2_22khz_80band_256x does not advertise it
  • you need file / PDF input — to accept documents without your own parsing step; nvidia/bigvgan_v2_22khz_80band_256x does not advertise it
  • you need seed (reproducible sampling) — to repeat a generation for tests and evals; nvidia/bigvgan_v2_22khz_80band_256x does not advertise it

Choose nvidia/bigvgan_v2_22khz_80band_256x if…

No advantage on the data we track — pick it for provider preference or output quality on your own prompts.

Frequently asked questions

Is Google: Gemini 3 Pro Preview better than nvidia/bigvgan_v2_22khz_80band_256x?

Google: Gemini 3 Pro Preview comes out ahead on the data we track: 6 advantages and none for nvidia/bigvgan_v2_22khz_80band_256x.

Do Google: Gemini 3 Pro Preview and nvidia/bigvgan_v2_22khz_80band_256x support function calling and JSON output?

Tool calling — Google: Gemini 3 Pro Preview: yes, nvidia/bigvgan_v2_22khz_80band_256x: not advertised. JSON-schema structured output — Google: Gemini 3 Pro Preview: yes, nvidia/bigvgan_v2_22khz_80band_256x: not advertised.

Can Google: Gemini 3 Pro Preview or nvidia/bigvgan_v2_22khz_80band_256x read images?

Only Google: Gemini 3 Pro Preview accepts image input; nvidia/bigvgan_v2_22khz_80band_256x is text-only for input.

Is Google: Gemini 3 Pro Preview or nvidia/bigvgan_v2_22khz_80band_256x free to use?

No free variant is listed for either; both are pay-per-token.

About the two models

Google

Google: Gemini 3 Pro Preview

Gemini 3 Pro is Google’s flagship frontier model for high-precision multimodal reasoning, combining strong performance across text, image, video, audio, and code with a 1M-token context window. Reasoning Details must be preserved when using multi-turn tool calling, see our docs here: https://openrouter.ai/docs/use-cases/reasoning-tokens#preserving-reasoning-blocks. It delivers state-of-the-art benchmark results in general reasoning, STEM problem solving, factual QA, and multimodal understanding, including leading scores on LMArena, GPQA Diamond, MathArena Apex, MMMU-Pro, and Video-MMMU. Interactions emphasize depth and interpretability: the model is designed to infer intent with minimal prompting and produce direct, insight-focused responses. Built for advanced development and agentic workflows, Gemini 3 Pro provides robust tool-calling, long-horizon planning stability, and strong zero-shot generation for complex UI, visualization, and coding tasks. It excels at agentic coding (SWE-Bench Verified, Terminal-Bench 2.0), multimodal analysis, and structured long-form tasks such as research synthesis, planning, and interactive learning experiences. Suitable applications include autonomous agents, coding assistants, multimodal analytics, scientific reasoning, and high-context information processing.

Full Google: Gemini 3 Pro Preview specs →

Compare Google: Gemini 3 Pro Preview with other models

Compare nvidia/bigvgan_v2_22khz_80band_256x with other models

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