Google releases Gemini 3.5 Flash: inference speed increased by 4 times, cost only half of competing products

Core conclusion

Google officially released Gemini 3.5 Flash on May 19, which is a new model positioned as "cutting edge intelligence + extreme speed" and designed specifically for Agent workflows and large-scale automation scenarios. Its key data points deserve the attention of every AI automation practitioner:

• The output speed is 4 times that of other cutting-edge models, and the inference efficiency has greatly improved.
• The cost is only half of competing products, which has obvious advantages in large-scale deployment scenarios
• CharXiv Reasoning reaches 84.2%, and the reasoning ability enters the first echelon
• Agent capabilities are comprehensively enhanced, and combined with the Antigravity framework, it reached 76.2% in Terminal-Bench 2.1

For content automation practitioners, this means that more complex AI Agent workflows can be run at lower costs.

Background and trigger events

On May 19, 2026, Google DeepMind released Gemini 3.5 Flash on the official blog. This is another major update by Google at the model level after the release of Spark Agent at Google I/O in March. Different from the "API-first" Spark Agent, Gemini 3.5 Flash puts more emphasis on the capability boundaries of the model itself - especially the overall improvement in coding, multi-modal understanding and Agent tasks.

Google DeepMind CTO Koray Kavukcuoglu said in the release that Gemini 3.5 Flash is designed to "achieve cutting-edge intelligence at extremely low cost" and allow developers to deploy AI Agents on a large scale in production environments.

Key Impact (by Dimension)

Adaptation suggestions

The emergence of Gemini 3.5 Flash gives AI automation practitioners a more cost-effective choice:

• Agent orchestration layer upgrade: The Antigravity framework allows 3.5 Flash to maintain a high success rate in complex multi-step tasks. If your n8n or OpenClaw workflow uses multiple AI call nodes, consider migrating some inference tasks to 3.5 Flash
• Cost-first model routing: Use 3.5 Flash for non-critical inference scenarios (content rewriting, summary generation, data extraction), reserve Claude or GPT for tasks that require deep inference - achieve cost optimization
• Agent reliability improvement: Open source guardrail tools such as Forge (which can increase the 8B model from 53% to 99% Agent task success rate) combined with the high inference speed of 3.5 Flash make locally deployed Agents closer to production-level reliability
• Compare DeepSeek V4 strategy: If you are using DeepSeek V4 for inference cost reduction, you can use Gemini 3.5 Flash as another alternative for A/B testing

Task List

• Log in to Google AI Studio to obtain the Gemini 3.5 Flash API key
• Configure model routing in the existing AI automation workflow and add 3.5 Flash to the optional model pool
• Test output quality and speed comparison in non-critical inference tasks
• Evaluate API cost changes and update cost budget models

Example: curl calls Gemini 3.5 Flash API

# Gemini 3.5 Flash API
curl -X POST "https://generativelanguage.googleapis.com/v1beta/models/gemini-3.5-flash:generateContent" \
  -H "Content-Type: application/json" \
  -d '{
 "contents": [{"parts":[{"text": " n8n JSON， score issues "}]}]
  }'

• Google
• Google AI Studio
• Gemini API

Gemini 3.5 Flash、DeepSeek V4、Claude、GPT-4o、n8n、OpenClaw、OpenAI、Google DeepMind

Internal link guidance

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