---
title: Google Gemini
slug: google-gemini
url: "https://toolweight.com/options/google-gemini"
homepage: "https://ai.google.dev"
categories: llm-apis
last_verified: 2026-01-15
license: CC-BY-4.0
---

# Google Gemini

> Gemini via AI Studio for prototyping or Vertex AI for production

Google ships Gemini through two doors: AI Studio with a generous free tier for prototyping, and Vertex AI with the region pinning, quotas and contracts that production needs. The pitch is long context at low cost, genuinely native audio in and out, and the deepest regional footprint of any provider here, including Australian regions that competitors cannot match.

## Identity

|  |  |
| --- | --- |
| Name | Google Gemini |
| Company | Google |
| One-liner | Gemini via AI Studio for prototyping or Vertex AI for production |
| Site | https://ai.google.dev |
| Docs | https://ai.google.dev/gemini-api/docs |
| Founded | 1998 |
| Open source | No |
| Brand | https://toolweight.com/vendors/Google |
| Compared in | 1 |

## Where it is compared

### [LLM APIs](https://toolweight.com/compare/llm-apis)
Ranked **#1 of 18** on default weights.
| Field | Value | Confidence | Verified | Source | Note |
| --- | --- | --- | --- | --- | --- |
| Flagship model | Gemini 3 Pro | Inferred | 2026-01-15 | https://blog.google/products/gemini/gemini-3/ | Launched November 2025; a newer flagship may have shipped since. |
| Context window | 1,000,000 tokens | Vendor-claimed | 2026-01-15 | https://ai.google.dev/gemini-api/docs/models | Input window. Google publishes a separate, much smaller output cap alongside it. |
| Max output | - | Unknown | - | - | Google publishes a per-model output cap well below the million-token input window, but the current figure for this flagship was not confirmed and is not worth guessing at, check the models page before sizing a long generation. |
| Image input | ● | Vendor-claimed | 2026-01-15 | https://ai.google.dev/gemini-api/docs/image-understanding | - |
| Audio in/out | ● | Vendor-claimed | 2026-01-15 | https://ai.google.dev/gemini-api/docs/live | Native audio tokens in and out via the Live API, plus video input. |
| Open weights | ◐ | Vendor-claimed | 2026-01-15 | https://ai.google.dev/gemma | The Gemma family is downloadable; Gemini itself is not. |
| OpenAI-compat API | ● | Vendor-claimed | 2026-01-15 | https://ai.google.dev/gemini-api/docs/openai | A chat-completions compatibility endpoint is documented for both AI Studio and Vertex. |
| TTFT p50 | - | Unknown | - | - | - |
| Output tok/s | - | Unknown | - | - | - |
| $/M input | $2 /M tok | Vendor-claimed | 2026-01-15 | https://ai.google.dev/gemini-api/docs/pricing | Rate for prompts up to 200K tokens, off Google's pricing page; longer prompts are surcharged. |
| $/M output | $12 /M tok | Vendor-claimed | 2026-01-15 | https://ai.google.dev/gemini-api/docs/pricing | Rate for prompts up to 200K tokens; the long-context tier costs more. |
| $/M cache read | $0.2 /M tok | Inferred | 2026-01-15 | - | Approximate, caching discounts input heavily but Google also charges cache storage per token-hour, which can dominate for small caches held a long time. |
| Batch discount | 50 % | Vendor-claimed | 2026-01-15 | https://ai.google.dev/gemini-api/docs/batch-mode | - |
| Tool use | ● | Vendor-claimed | 2026-01-15 | https://ai.google.dev/gemini-api/docs/function-calling | - |
| Schema output | ● | Vendor-claimed | 2026-01-15 | https://ai.google.dev/gemini-api/docs/structured-output | responseSchema constrains decoding to a supplied schema. |
| Effort control | ● | Vendor-claimed | 2026-01-15 | https://ai.google.dev/gemini-api/docs/thinking | Thinking level / thinking budget controls reasoning depth per request. |
| Computer use | ◐ | Inferred | 2026-01-15 | https://ai.google.dev/gemini-api/docs/computer-use | A dedicated computer-use model rather than a tool on the flagship, which is this column's definition of partial, so it is now graded that way rather than as a yes. |
| MCP support | ◐ | Inferred | 2026-01-15 | - | MCP is wired up in the SDKs rather than being a server-side connector on the API. |
| Cache TTL | Explicit caches, default 1 h TTL; implicit caching too | Inferred | 2026-01-15 | - | - |
| Continuity policy | Stable versions carry dated suffixes you can pin, and Google publishes a retirement date per version. In practice this is the fastest-moving line-up here: preview models are withdrawn with weeks of notice, and the 1.5 generation was retired roughly a year after GA. Vertex adds contractual predictability that AI Studio does not. | Community-reported | 2026-01-15 | - | - |
| Notice period | - | Unknown | - | - | Google publishes per-version retirement dates but no single guaranteed notice window; preview models get materially less than stable ones. |
| Pinnable versions | ● | Vendor-claimed | 2026-01-15 | https://ai.google.dev/gemini-api/docs/models | - |
| Zero retention | ◐ | Inferred | 2026-01-15 | - | Tier-dependent, which is what this column calls partial: on Vertex, prompts are not stored and enterprise controls apply, but the free AI Studio tier is a different bargain, assume it is used to improve products. We have not confirmed exclusion from abuse-monitoring logs, which is the bar the column's definition actually sets. |
| Trains on your data | ◐ | Inferred | 2026-01-15 | - | No for paid Vertex and paid AI Studio usage; the free tier explicitly is used to improve Google products. |
| AU region | ● | Inferred | 2026-01-15 | - | Vertex AI serves Gemini from australia-southeast1, with region pinning enforced at the project level. |
| API since | 2023 | Inferred | - | - | - |
| Positioning | Long context and native multimodality across Google's cloud | Inferred | - | - | - |

**Verdict.** The cheapest credible route to a million-token window and the only provider here with genuinely native audio in and out. Vertex is also the most convincing answer to an Australian data-residency requirement. The cost is churn, this line-up turns over faster than any other, so pin versions and expect a migration each year.

## Alternatives

- [Qwen](https://toolweight.com/options/alibaba-qwen), Alibaba's model family, huge open-weight range, closed flagship
- [Amazon Bedrock](https://toolweight.com/options/amazon-bedrock), Multi-vendor model access inside your existing AWS account
- [Anthropic](https://toolweight.com/options/anthropic), Claude models, built around long agentic runs and tool use
- [Cerebras](https://toolweight.com/options/cerebras), Wafer-scale inference, the fastest tokens per second available
- [Cohere](https://toolweight.com/options/cohere), Enterprise-focused models built for RAG and private deployment
- [DeepSeek](https://toolweight.com/options/deepseek), Frontier-adjacent models at a small fraction of Western prices
- [Fireworks AI](https://toolweight.com/options/fireworks-ai), Fast open-weight inference with strong structured-output support
- [Groq](https://toolweight.com/options/groq), Custom LPU silicon serving open-weight models at extreme speed
- [Meta Llama](https://toolweight.com/options/meta-llama), Open-weight Llama models, hosted almost everywhere but Meta
- [Mistral AI](https://toolweight.com/options/mistral-ai), European lab with an open-weight lineage and EU-resident hosting
- [Moonshot AI](https://toolweight.com/options/moonshot-ai), Kimi models, open-weight agentic performance at low cost
- [OpenAI](https://toolweight.com/options/openai), GPT models plus audio, images and embeddings on one bill

## Licence and attribution

Data from toolweight (https://toolweight.com), licensed CC-BY-4.0.

- Licence: [CC-BY-4.0](https://creativecommons.org/licenses/by/4.0/)
- Canonical HTML: https://toolweight.com/options/google-gemini
- Machine-readable: https://toolweight.com/options/google-gemini.md · https://toolweight.com/api/v1 · https://toolweight.com/mcp
- toolweight takes no affiliate revenue and sells no placements. Corrections: https://toolweight.com/suggest