Gemini API — Access Google Gemini 3 Pro & Flash via ApiTopMix

The Google Gemini API gives you one of the strongest multimodal model families around — great at text and vision, built for very long context, and priced to compete. On ApiTopMix you get Gemini API access through a single OpenAI-compatible key: call gemini-3-pro-preview (the latest Pro flagship), gemini-3.1-pro-preview and gemini-2.5-pro, plus the fast, cheap Flash tier — gemini-3-flash-preview, gemini-2.5-flash and gemini-3.1-flash-lite-preview — all at base URL https://apitopmix.com/v1.

Everything below works from one sk- key. Because ApiTopMix is OpenAI-compatible, your existing code keeps working — you change the base_url and the model string, nothing else. Billing is pay-per-use and sits below Google's official list price, so a cheap Gemini API path is the default rather than a promo, and the Flash tier is especially cheap for high-volume traffic. There is no Google Cloud project to create and no separate Google AI Studio account to set up: ApiTopMix provides the gateway.

What Google Gemini is good at

Gemini is Google's flagship model family, and it earns its place on three strengths that map cleanly to real workloads. If your app touches images, huge inputs, or high request volume, the Gemini API is a natural fit:

• Multimodal (text + vision) — Gemini handles images alongside text well, so the Gemini multimodal API is a strong pick for document understanding, screenshots, charts, product photos and mixed image-and-text prompts.
• Very long context — Gemini is designed for large context windows, which makes the Gemini long context API ideal for whole documents, long transcripts, big codebases and multi-file analysis in a single request.
• Competitive pricing, cheap at volume — Gemini is priced to compete, and the Flash tier is very cheap, so high-volume traffic — chat, classification, extraction, simple agents — runs at a fraction of the cost of a top-tier model.
• Strong general reasoning — the Pro tier holds its own on complex reasoning, coding help and structured output, so you are not trading capability for the multimodal and long-context strengths.

The practical pattern is to send hard, high-value steps to a Pro model and everything else to Flash — more on that split next. Because both tiers share one key and one base URL, routing is just a change to the model string.

Gemini Pro vs Flash — two tiers

Google splits Gemini into two tiers, and ApiTopMix exposes both behind the same sk- key and the same base URL. You choose per request simply by which model id you send.

In short: Pro is the capability tier for the hard, high-value calls, and Flash is the volume tier that keeps costs low when you are sending a lot of traffic. Many teams default to Flash and escalate only the hardest steps to a Pro model like gemini-3-pro-preview. Because it is all one key, you can route per task or even A/B test by swapping the model string.

The Google Gemini model lineup

ApiTopMix keeps the full Gemini lineup available so you can run on the latest Pro flagship, pin a specific version, or drop down to Flash for cheap high-volume work. Here is the complete Google Gemini lineup and the exact model ids:

No prices are printed here on purpose: rates change, and the ApiTopMix pricing page is always the source of truth. What is stable is the shape of the lineup — gemini-3-pro-preview is the current Pro flagship, gemini-2.5-pro stays available for pinning, and the Flash tier (down to gemini-3.1-flash-lite-preview) is where Gemini API pricing gets very cheap for volume.

How to call the Gemini API

ApiTopMix exposes an OpenAI-compatible endpoint, so calling the Gemini API is the request you already know — just with the ApiTopMix base URL and a Gemini model id. This is the short Gemini API quick-start.

One endpoint, one key

Get the key first:

1. Create an account at apitopmix.com/register.
2. Open the console, go to Tokens, and click Create new token.
3. Copy the key — it starts with sk-. That single key drives every Gemini model, plus the rest of the catalog.

curl (OpenAI-compatible)

The fastest way to confirm your Gemini API key works — one request to the Pro flagship:

curl https://apitopmix.com/v1/chat/completions \
  -H "Authorization: Bearer sk-your-apitopmix-key" \
  -H "Content-Type: application/json" \
  -d '{
    "model": "gemini-3-pro-preview",
    "messages": [{"role": "user", "content": "Say hi from Google Gemini 3 Pro"}]
  }'

Swap "gemini-3-pro-preview" for "gemini-3.1-pro-preview" or "gemini-2.5-pro" to pin another Pro version, or for "gemini-3-flash-preview" / "gemini-2.5-flash" / "gemini-3.1-flash-lite-preview" to run the cheap Flash tier — everything else stays identical.

Python (openai SDK)

Because the endpoint is OpenAI-compatible, use the official openai Python SDK unchanged — point base_url at ApiTopMix and set the model to a Gemini id. This is the whole trick behind the Gemini OpenAI-compatible API:

from openai import OpenAI

client = OpenAI(
    base_url="https://apitopmix.com/v1",
    api_key="sk-your-apitopmix-key",
)

resp = client.chat.completions.create(
    model="gemini-3-pro-preview",   # or gemini-2.5-pro / gemini-3-flash-preview
    messages=[{"role": "user", "content": "Summarize this long document in five bullets."}],
)

print(resp.choices[0].message.content)

Any framework that speaks the OpenAI protocol — LangChain, LlamaIndex, your own wrapper — works the same way: base URL https://apitopmix.com/v1, your sk- key, and a Gemini model id. To send images, use the standard OpenAI multimodal message format (an image_url content part) and Gemini's vision handles the rest.

Migrating from Google AI Studio or Vertex AI

If you currently reach Gemini through Google AI Studio or Vertex AI, moving to ApiTopMix is a two-line change — and it removes the Google Cloud setup entirely. You keep your code, your SDK and your request shape; you change where requests go and which key you send:

• base_url → https://apitopmix.com/v1 (the OpenAI-compatible endpoint).
• api_key → your ApiTopMix sk- key (no Google Cloud service account, no Vertex credentials).
• model → gemini-3-pro-preview (or any other Pro or Flash id).

That is it — no rewrite of your request/response handling, streaming or tool-calling logic, because the OpenAI-compatible surface matches what you already use. It also means you can buy Gemini API access and use the Gemini API without Google Cloud: an ApiTopMix account and key is all you need — no project, no billing account, no Vertex configuration. ApiTopMix provides the gateway; you keep your existing code. If you were juggling several provider SDKs, note that the same key also reaches GPT and Claude, so you can consolidate onto one interface.

Gemini vs GPT vs Claude — which model?

The Gemini vs GPT (and Claude) question comes down to what each family does best, and on ApiTopMix you do not have to pick just one — all three live behind the same key and the same OpenAI-compatible base URL:

• Gemini — strong multimodal understanding, very long context, and competitive pricing, with Flash being especially cheap for high volume. A great default when your workload is image-heavy, long-context, or cost-sensitive at scale.
• GPT — a strong all-round choice with a huge ecosystem. See the GPT-5 API and GPT-5.6 API pages for the OpenAI lineup on ApiTopMix.
• Claude — a favorite for coding and long-form reasoning. See the cheap Claude API and Claude Sonnet API pages, and the Claude Code guide for agentic coding.

Because you route each task to whichever model fits and compare them by changing only the model string, you can benchmark Gemini vs GPT on your own prompts in minutes rather than opening three accounts. The pricing page lists rates for all three families side by side.

Why use ApiTopMix for the Gemini API

ApiTopMix is a unified AI API gateway. For Google Gemini, that turns into a few concrete wins:

Frequently asked questions

Further reading

• GPT-5 API — OpenAI's flagship on ApiTopMix; compare Gemini vs GPT and route per task.
• GPT-5.6 API — the newer GPT release, same key and base URL.
• Cheap Claude API — the most affordable route into the Claude family with the same key.
• Claude Sonnet API — the balanced Claude tier for high-volume production.
• Use Claude Code — wire ApiTopMix into Claude Code for agentic coding.
• ApiTopMix Pricing — current per-model rates for the whole Gemini lineup and every other model.
• ApiTopMix API Docs — endpoints, headers and full examples.

Conclusion

The Google Gemini API is the family you reach for when your workload is multimodal, long-context, or cost-sensitive at scale. On ApiTopMix you get the whole lineup behind one sk- key at an OpenAI-compatible base URL, https://apitopmix.com/v1: the latest gemini-3-pro-preview and the rest of the Pro tier for capability, and the very cheap Flash tier — gemini-3-flash-preview, gemini-2.5-flash, gemini-3.1-flash-lite-preview — for high volume, with no Google Cloud project required.

Set it up once — a curl test or a base-URL swap — and pick the right model per task by changing a single string. Get a key, run the curl test above, and check the pricing page for current per-model rates before you scale up.