What's new in Gemini 3.7 Flash

This page All models

Gemini 3.7 Flash (gemini-3.7-flash) is generally available (GA) and ready for production use. It is our most intelligent workhorse model yet for coding and agents.

This guide explains what's new in Gemini 3.7 Flash, API changes, code examples, and migration guidance.

New model

Gemini 3.7 Flash supports a 1M token context window, 64k max output tokens, tunable thinking levels (low, medium, high), and the same suite of built-in tools as 3.6 Flash.

For complete specs, see the Gemini 3.7 Flash model page. For detailed pricing, see the pricing page.

Quickstart

from google import genai

client = genai.Client()

interaction = client.interactions.create(
    model="gemini-3.7-flash",
    input="Write a three.js script that renders a realistic 3D black hole."
)

print(interaction.output_text)

import { GoogleGenAI } from "@google/genai";

const client = new GoogleGenAI({});

const interaction = await client.interactions.create({
  model: "gemini-3.7-flash",
  input: "Write a three.js script that renders a realistic 3D black hole.",
});

console.log(interaction.output_text);

curl "https://generativelanguage.googleapis.com/v1beta/interactions" \
  -H "x-goog-api-key: $GEMINI_API_KEY" \
  -H 'Content-Type: application/json' \
  -X POST \
  -d '{
    "model": "gemini-3.7-flash",
    "input": "Write a three.js script that renders a realistic 3D black hole."
  }'

What's new in Gemini 3.7 Flash

• Coding and agentic tasks: Significantly higher quality on real-world software engineering and agentic benchmarks, improving issue resolution and reducing failed agent loops.
• Web development and stronger design parity: Generates higher-fidelity desktop and web application code directly from design mocks, with strong gains in design adherence and in auditing existing codebases against mocks to verify 1:1 design parity.
• Promotional pricing: Gemini 3.7 Flash will be available at an introductory price of $0.75/1M input tokens and $3.75/1M output tokens. We’re also applying this new rate to 3.6 Flash. Introductory pricing expires on December 31, 2026; after, $1.50/1M input tokens and $7.50/1M output tokens will apply.

Choosing the right model

Reference the below table to review recommended migration targets for your workloads. To upgrade from Gemini 3.5 Flash, Gemini 3 Flash (Preview), or Gemini 3.1 Pro, ensure you remove deprecated sampling parameters (temperature, top_p, top_k) and prefilled model turns. Gemini 3.6 Flash already no longer supported these parameters.

Understanding reasoning levels

Gemini 3.7 Flash gives developers flexible control over latency and intelligence by adjusting the model's thinking level:

• Low thinking effort: Reduces time-to-answer for latency-critical tasks like incident response pipelines, real-time chat, writing drafts, and fast data analysis.
• Medium (default): Best quality for most tasks. Recommended for complex code and agentic use cases, with higher first-pass accuracy.

• High thinking effort: Maximizes the model's ability to think and use tools. Best for complex reasoning, hard math, and the most difficult coding and agent tasks. Allows extended thoughts and function calls, with higher token consumption and cost.

from google import genai

client = genai.Client()

interaction = client.interactions.create(
    model="gemini-3.7-flash",
    input="Analyze this payment processing pipeline for race conditions during retry attempts and rewrite the transaction locks safely.",
    generation_config={
        "thinking_level": "medium"  # Balanced reasoning effort for complex tasks
    }
)

print(interaction.output_text)

import { GoogleGenAI } from "@google/genai";

const client = new GoogleGenAI({});

const interaction = await client.interactions.create({
  model: "gemini-3.7-flash",
  input: "Analyze this payment processing pipeline for race conditions during retry attempts and rewrite the transaction locks safely.",
  generation_config: {
    thinking_level: "medium"
  }
});

console.log(interaction.output_text);

curl "https://generativelanguage.googleapis.com/v1beta/interactions" \
  -H "x-goog-api-key: $GEMINI_API_KEY" \
  -H 'Content-Type: application/json' \
  -X POST \
  -d '{
    "model": "gemini-3.7-flash",
    "input": "Analyze this payment processing pipeline for race conditions during retry attempts and rewrite the transaction locks safely.",
    "generation_config": {
      "thinking_level": "medium"
    }
  }'

Updated Antigravity agent

Due to its improved performance and reasoning, Gemini 3.7 Flash is now the new default model powering the Antigravity agent in Gemini Managed Agents and Google Antigravity SDK.

from google import genai

client = genai.Client()

interaction = client.interactions.create(
    agent="antigravity-preview-05-2026",
    input=(
        "Audit https://web.dev for performance, Core Web Vitals, and SEO. "
        "Query Google's PageSpeed Insights API for both Mobile and Desktop strategies. "
        "Check search indexing with Google Search for site:web.dev. "
        "Format the output as a side-by-side scorecard table with prioritized fixes."
    ),
    environment="remote",
)

print(interaction.output_text)

import { GoogleGenAI } from "@google/genai";

const client = new GoogleGenAI({});

const interaction = await client.interactions.create({
  agent: "antigravity-preview-05-2026",
  input: "Audit https://web.dev for performance, Core Web Vitals, and SEO. Query Google's PageSpeed Insights API for both Mobile and Desktop strategies. Check search indexing with Google Search for site:web.dev. Format the output as a side-by-side scorecard table with prioritized fixes.",
  environment: "remote",
}, { timeout: 300000 });

console.log(interaction.output_text);

curl -X POST "https://generativelanguage.googleapis.com/v1beta/interactions" \
-H "Content-Type: application/json" \
-H "x-goog-api-key: $GEMINI_API_KEY" \
-d '{
    "agent": "antigravity-preview-05-2026",
    "input": "Audit https://web.dev for performance, Core Web Vitals, and SEO. Query Google'\''s PageSpeed Insights API for both Mobile and Desktop strategies. Check search indexing with Google Search for site:web.dev. Format the output as a side-by-side scorecard table with prioritized fixes.",
    "environment": "remote"
}'

The underlying Gemini model can be configured using agent_config.

Migration checklist

  `/gemini-interactions-api migrate my app to Gemini 3.7 Flash`

Migrate to gemini-3.7-flash

• Update Model ID: Change your target model string to gemini-3.7-flash.
• Remove deprecated sampling parameters:
  • Strip temperature, top_p, and top_k from generation configs.
  • Replace thinking_budget with the string enum thinking_level.
  • Remove candidate_count (unsupported in Gemini 3.x).
• Enforce turn validation rules:
  • Standardize multi-turn conversations on server-side previous_interaction_id.
  • Remove prefilled model turns.
• Audit function calling:
  • Place multimodal assets inside the response payload.
  • Format inline instructions using \n\n.
  • If you see Malformed_Function_Call errors tied to pre-tool text, see Workarounds for pre-tool text requirements.
  • Only if using generateContent API: Ensure all FunctionResponse objects include call_id and name.
• Baseline Gemini 3.x requirements: For SDK updates and thought signature preservation, see the Gemini 3.5 Migration Checklist.

Pricing

Introductory pricing applies across Google AI Studio and Gemini Enterprise Agent Platform through December 31, 2026 for both Gemini 3.7 Flash and Gemini 3.6 Flash. From January 1, 2027, standard pricing will take effect. For details, please see pricing page.

Next steps

• Review API specs on the Models Overview.
• Explore multi-agent orchestration in the Interactions API Guide.
• Test and refine prompts in Google AI Studio.