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gemini-3-flash-preview API pricing & access

gemini-3-flash-preview API pricing: $1 per 1M tokens. gemini-3-flash-preview. Supports text, image, video, audio, file input and text output. Li…

gemini-3-flash-preview API access

gemini-3-flash-preview. Supports text, image, video, audio, file input and text output. Listed specifications follow public vendor documentation. Available features and limits depend on the selected serving channel.

Compare supported API endpoints and capabilities, then access gemini-3-flash-preview through the unified API gateway.

Category: text
Context length: 1048576 tokens
Maximum output: 65536 tokens
Supported APIs: Gemini API, OpenAI Chat Completions API, Anthropic Messages API
API endpoints: POST /v1beta/models/gemini-3-flash-preview:generateContent, POST /v1/chat/completions, POST /v1/messages
Input modalities: text, image, video, audio, file
Output modalities: text
Capabilities: function calling, structured output, reasoning, caching, vision

gemini-3-flash-preview API pricing

Base input price: $1 per 1M tokens
Base output price: $3 per 1M tokens

Base prices are shown in USD before group-specific adjustments. Open the live pricing page for current access-group prices.

About gemini-3-flash-preview

gemini-3-flash-preview is Google's Gemini 3 Flash preview ID for text, image, video, audio and PDF input with text output. It remains listed for maintaining existing preview integrations and evaluating migration.

Preview status warrants lifecycle and behavior monitoring. Native audio or video generation and Live sessions are separate products; validate multimodal understanding, tools, thinking and structured output on representative tasks.

Official reference, checked 2026-10-14.

Use cases and prompting

Retain the full preview identifier and record the returned version.
Request locations for input evidence and check handling of unreadable or inaudible material.
Before moving to a stable model, retest tool arguments, refusals and stream completion.
Compare the same test cases with gemini-3.6-flash; check request and response formats in the API documentation.

How to call gemini-3-flash-preview

gemini-3-flash-preview is served through tbuy's unified gateway. Existing OpenAI or Anthropic SDK code keeps working: point base_url at https://modelsok.com and use your tbuy API key.

curl (OpenAI-compatible)

curl https://modelsok.com/v1/chat/completions \
  -H "Authorization: Bearer $API_KEY" \
  -H "Content-Type: application/json" \
  -d '{"model": "gemini-3-flash-preview", "messages": [{"role": "user", "content": "Hello"}]}'

Python (openai SDK)

from openai import OpenAI

client = OpenAI(base_url="https://modelsok.com/v1", api_key="YOUR_API_KEY")
response = client.chat.completions.create(
    model="gemini-3-flash-preview",
    messages=[{"role": "user", "content": "Hello"}],
)
print(response.choices[0].message.content)

Python (anthropic SDK)

from anthropic import Anthropic

client = Anthropic(base_url="https://modelsok.com", api_key="YOUR_API_KEY")
message = client.messages.create(
    model="gemini-3-flash-preview",
    max_tokens=1024,
    messages=[{"role": "user", "content": "Hello"}],
)
print(message.content[0].text)

Frequently asked questions about gemini-3-flash-preview

What is gemini-3-flash-preview?

How do I call gemini-3-flash-preview?

Create an API key with access to gemini-3-flash-preview, then use the exact model ID and a supported endpoint from the API access section. Request fields depend on the selected endpoint.

How is gemini-3-flash-preview priced?

Pricing depends on the selected provider group and the model billing unit. Refer to the current input, output, request, or media prices in the pricing section.

What is the context window of gemini-3-flash-preview?

The model catalog lists a context window of 1048576 tokens. Check the selected endpoint for request limits.

What is the maximum output of gemini-3-flash-preview?

The model catalog lists a maximum output of 65536 tokens. Your request settings may set a lower limit.

How should I evaluate gemini-3-flash-preview for my project?

Start with the use cases and prompting guidance on this page, then evaluate the model with representative inputs from your project.

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