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Краткий вывод

  • Official capabilities include a 1M context window, up to 64K output, plus function calling, structured output, search tools, and code execution.
  • Compared with classic lightweight Flash tiers, it is better suited to complex Q&A, coding, long-document handling, and agent workflows.
  • The recommended integration path remains OpenAI-compatible chat so existing SDKs, SSE streaming, and retry middleware can be reused.

Частые ошибки

  • 400 invalid_request_error: триггер=Missing required fields, malformed messages, or invalid parameter types in the payload.; исправление=Validate model, messages, max_tokens, and any tools/schema JSON before retrying.; повтор=Retry only after fixing the payload; avoid blind retries.
  • 401 authentication_error: триггер=Missing Authorization header, malformed bearer token, or invalid API key.; исправление=Verify Authorization: Bearer <YOUR_API_KEY> format and key validity.; повтор=Retry after authentication is fixed.
  • 429 rate_limit_error: триггер=Request rate, concurrency, or quota usage has hit upstream rate limiting.; исправление=Apply exponential backoff and inspect concurrency, context size, and current quota consumption.; повтор=Use 1s/2s/4s backoff with jitter; reduce concurrency or downgrade workload shape if it persists.
  • 500 internal_error: триггер=Transient upstream instability, tool execution failure, or internal processing issues.; исправление=Capture request id and a compact context summary, then retry; escalate if failures persist.; повтор=Retry 2-3 times with short delays.

gemini-3.5-flash

gemini-3.5-flash is Google's next-generation Flash text model released on May 19, 2026, positioned around higher intelligence with Flash-class latency. It fits high-throughput chat, coding copilots, long-context Q&A, structured output, and tool-enabled workflows through ToAPIs-compatible chat integration.

Тип модели:
Цена: Input 60 кредитов/1M, Output 360 кредитов/1M
Type a message to test the model.

Прозрачные цены

Цены gemini-3.5-flash

Text usage is billed by actual token consumption. Final billing follows the current account quote.

Пополнить кредиты
Input 60 кредитов/1M, Output 360 кредитов/1M

Почему ToAPIs

Why call gemini-3.5-flash through ToAPIs?

Keep model access, API keys, billing, and usage management in one workflow.

High intelligence with Flash latency

It is not just a low-cost fallback tier; it aims to handle deeper understanding, planning, and generation while staying responsive.

1M long context

Well suited to long-document summarization, codebase analysis, knowledge synthesis, large prompts, and extended conversations.

Structured and tool-based output

Function calling, structured JSON, search tools, and code execution make it a stronger fit for agentic workflows.

Connect in three steps

Create a key, send a compatible chat request, and monitor usage.

  1. 1

    Step 1

    Create an API key and set Authorization: Bearer <YOUR_API_KEY>.

  2. 2

    Step 2

    POST to /v1/chat/completions with at least model and messages.

  3. 3

    Step 3

    Tune max_tokens, temperature, and top_p based on task complexity and determinism needs.

When to use gemini-3.5-flash

Use case 1

When you need more reasoning and coding strength than a classic lightweight model without giving up too much responsiveness.

Use case 2

When handling long-context tasks such as document Q&A, codebase analysis, long-session memory, or retrieval-grounded answers.

Use case 3

When you need structured JSON, function calling, or search/tool integration for agents.

Частые вопросы

gemini-3.5-flash FAQ

What is gemini-3.5-flash best for?

It is best for text and coding assistant tasks that need strong intelligence without giving up throughput and response speed.

How is it different from a classic Flash model?

The main difference is a higher intelligence ceiling, making it more suitable for complex Q&A, long context, and tool-enabled workflows.

What is the fastest way to integrate it?

Use the OpenAI-compatible Chat Completions path first so you can reuse existing messages, streaming, and retry middleware.

When should max_tokens be constrained carefully?

Constrain max_tokens carefully for long-context, coding, and structured-output tasks to avoid bloated responses, cost drift, or timeouts.

gemini-3.5-flash API

Start building with gemini-3.5-flash

Test a request here, then continue in the dashboard or API documentation.

Start for freeView API Docs

Try gemini-3.5-flash with one ToAPIs key.

Use the same account and API surface across supported text models.

Sign up to get free credits