Google Gemini

Name: Google Gemini
Price: 2 USD
Availability: InStock
Author: Google

Gemini via AI Studio for prototyping or Vertex AI for production

ai.google.dev ai.google.dev/gemini-api/docs

Overall in llm apis

2of 18 · score 76

Data coverage

89%

24 of 27 fields sourced

Best for

•Workloads that genuinely need 500K+ tokens of context per request
•Voice and video products wanting one model rather than a pipeline
•Australian or regulated deployments that must pin inference to a region

Strong on

+Effort control Yes 1/18
+AU region Yes 1/18
+Trains on your data Partial 2/18
+MCP support Partial 3/18
+Computer use Partial 3/18

Weak on

−Max output 65,536 tokens 7/10
Better: xAI: Unlimited
−$/M output $12/M tok 9/13
Better: Fireworks AI: $0.05/M tok
−Open weights Partial 12/18
Better: Meta Llama: Yes

vs Qwen

•Ahead on Computer use: Partial vs No
•Ahead on Schema output: Yes vs Partial
•Behind on Max output: 65,536 tokens vs 131,072 tokens
•Behind on $/M output: $12/M tok vs $7.5/M tok

How Google Gemini scores among 18 llm apis24 of 27 fields known

Capability7

Flagship model

Gemini 3.1 Pro Preview (gemini-3.1-pro-preview)

ai.google.dev · 2026-07-30

Context window1st

1,048,576 tokens

1/14

ai.google.dev · 2026-07-30

Max output

65,536 tokens

7/10

Leader: xAI · Unlimited

ai.google.dev · 2026-07-30

Image input1st

Yes

1/18

ai.google.dev · 2026-07-30

Audio in/out1st

Partial

1/18

ai.google.dev · 2026-07-30

Open weights

Partial

12/18

Leader: Meta Llama · Yes

ai.google.dev · 2026-01-15

OpenAI-compat API1st

Yes

1/18

ai.google.dev · 2026-01-15

Performance2

TTFT p50

—

Output tok/s

—

Pricing4

$/M input

$2/M tok

7/13

Leader: Groq · $0.05/M tok

aistudio.google.com · 2026-11-06

$/M output

$12/M tok

9/13

Leader: Fireworks AI · $0.05/M tok

aistudio.google.com · 2026-11-06

$/M cache read

$0.2/M tok

5/12

Leader: DeepSeek · $0.0028/M tok

ai.google.dev · 2026-07-30

Batch discount1st

50%

1/14

ai.google.dev · 2026-07-30

Agentic6

Tool use1st

Yes

1/18

ai.google.dev · 2026-07-30

Schema output1st

Yes

1/18

ai.google.dev · 2026-01-15

Effort control1st

Yes

1/18

ai.google.dev · 2026-01-15

Computer use3rd

Partial

3/18

Leader: Anthropic · Yes

ai.google.dev · 2026-01-15

MCP support3rd

Partial

3/18

Leader: Anthropic · Yes

ai.google.dev · 2026-07-30

Cache TTL

Explicit caches, default 1 h TTL; implicit caching too

· 2026-01-15

Governance & continuity6

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.

· 2026-01-15

Notice period

—

Pinnable versions1st

Yes

1/18

ai.google.dev · 2026-01-15

Zero retention

Partial

7/18

Leader: Amazon Bedrock · Yes

· 2026-01-15