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gemini-2.5-pro

vertex_ai-language-models · Chat model

gemini-2.5-pro is listed here as a chat model from vertex_ai-language-models. This page shows simple API pricing, token limits, and capability flags so you can compare it with similar options.

Provider and model identifiers are kept in their original form for accuracy.

vertex_ai-language-models-gemini-2-5-pro

Input
$1.2500 / 1M tokens
Output
$10.0000 / 1M tokens
Cached input
$0.1250 / 1M tokens
Context window
65.5K

Catalog generated: Jul 13, 2026

Compare this model Open a side-by-side table using this route and a close match from the current catalog. Estimate cost Use token counts, request volume, and cache assumptions to check a realistic monthly bill.

Quick read

Best for

Use this page when you need a fast view of cost, context size, and supported features before testing the model in your own workload.

Things to verify

Always check the provider page for discounts, cache pricing, region rules, and any model limits that may not appear in public metadata.

Pricing

Item Price
Input
$1.2500 / 1M tokens
Output
$10.0000 / 1M tokens
Cached input
$0.1250 / 1M tokens
Embedding
$1.2500 / 1M tokens

Limits

Context window
65.5K
Max input tokens
1.0M
Max output tokens
65.5K
Max tokens
65.5K
Explore benchmark family Review source-backed benchmark rows for the attached base model family. Check data sources See how pricing data is generated and what still needs provider verification. API vs subscription Learn when API pricing matters compared with ChatGPT, Claude Code, Cursor, or Copilot subscriptions. Cache and batch pricing Understand cached input, cache write, batch, priority, and flex pricing rows shown on this page.

Capabilities

Capability Supported
Vision Supported
Function calling Supported
Parallel function calling -
Tool choice Supported
Prompt caching Supported
Reasoning Supported
Response schema Supported
System messages Supported
Audio input Supported
Audio output -
Web search Supported
PDF input Supported
Video input Supported

Benchmarks

Most benchmark rows are attached to the base model family rather than this provider route. Open benchmark explorer

Benchmark Score Metric Scope Checked Source
Humanity's Last Exam 21.6% (no tools) accuracy Base model: Gemini 2.5 Pro (Gemini 2.5 Pro (GA)) 2026-05-31 Link
GPQA Diamond 86.4% pass@1 pass@1 Base model: Gemini 2.5 Pro (Gemini 2.5 Pro (GA)) 2026-05-31 Link
AIME 2025 88.0% pass@1 pass@1 Base model: Gemini 2.5 Pro (Gemini 2.5 Pro (GA)) 2026-05-31 Link
LiveCodeBench 69.0% (single attempt) accuracy Base model: Gemini 2.5 Pro (Gemini 2.5 Pro (GA)) 2026-05-31 Link
Aider Polyglot 82.2% diff-fenced pass rate Base model: Gemini 2.5 Pro (Gemini 2.5 Pro (GA)) 2026-05-31 Link
SWE-bench Verified 59.6% (single attempt) accuracy Base model: Gemini 2.5 Pro (Gemini 2.5 Pro (GA)) 2026-05-31 Link
Aider Polyglot 82.2% pass rate Base model: Gemini 2.5 Pro (gemini-2.5-pro) 2026-05-31 Link
SWE-bench Verified (multiple attempts) 67.2% accuracy Base model: Gemini 2.5 Pro (gemini-2.5-pro) 2026-05-31 Link
GPQA 86.4% accuracy Base model: Gemini 2.5 Pro (gemini-2.5-pro) 2026-05-31 Link
AIME 2025 88.0% accuracy Base model: Gemini 2.5 Pro (gemini-2.5-pro) 2026-05-31 Link
Aider Polyglot 79.1% percent correct Base model: Gemini 2.5 Pro Preview (gemini/gemini-2.5-pro-preview-06-05) 2026-05-31 Link
Aider Polyglot 76.9% percent correct Base model: Gemini 2.5 Pro Preview (gemini/gemini-2.5-pro-preview-05-06) 2026-05-31 Link

Similar models

Candidates below have the same known input/output modality shape and usable token pricing. Use the filters to change the ranking lens before opening a comparison.

Comparing from
Model Cost Input shape Features Context Why it is close
gemini-2.5-pro
vertex_ai-language-models
In $1.2500 / 1M tokens
Out $10.0000 / 1M tokens
pdf
Output: text
VisionFunction callingTool choicePrompt caching
65.5K
Current model
Reference row

Overall blends cost, exact modality shape, capabilities, and context.

Model Cost Input shape Features Context Why it is close
gemini-2.5-pro
Google
In $1.2500 / 1M tokens
Out $10.0000 / 1M tokens
pdf
Output: text
VisionFunction callingTool choicePrompt caching
65.5K
Exact I/O shape
Overall 76%
gemini-pro-latest
Google
In $1.2500 / 1M tokens
Out $10.0000 / 1M tokens
pdf
Output: text
VisionFunction callingTool choicePrompt caching
65.5K
Exact I/O shape
Overall 76%
gemini-pro-latest
Google
In $1.2500 / 1M tokens
Out $10.0000 / 1M tokens
pdf
Output: text
VisionFunction callingTool choicePrompt caching
65.5K
Exact I/O shape
Overall 76%
gemini-3-pro-preview
vertex_ai-language-models
In $2.0000 / 1M tokens
Out $12.0000 / 1M tokens
pdf
Output: text
VisionFunction callingTool choicePrompt caching
65.5K
Same provider
Overall 71%
gemini-3-pro-preview
Vertex AI
In $2.0000 / 1M tokens
Out $12.0000 / 1M tokens
pdf
Output: text
VisionFunction callingTool choicePrompt caching
65.5K
Exact I/O shape
Overall 71%
gemini-3-pro-preview
Google
In $2.0000 / 1M tokens
Out $12.0000 / 1M tokens
pdf
Output: text
VisionFunction callingTool choicePrompt caching
65.5K
Exact I/O shape
Overall 71%
gemini-3-pro-preview
OpenRouter
In $2.0000 / 1M tokens
Out $12.0000 / 1M tokens
pdf
Output: text
VisionFunction callingTool choicePrompt caching
65.5K
Exact I/O shape
Overall 71%
gemini-3-flash-preview
Vertex AI
In $0.5000 / 1M tokens
Out $3.0000 / 1M tokens
pdf
Output: text
VisionFunction callingTool choicePrompt caching
65.5K
Exact I/O shape
Overall 63%
gpt-5
OpenAI
In $1.2500 / 1M tokens
Out $10.0000 / 1M tokens
pdf
Output: text
VisionFunction callingTool choicePrompt caching
128.0K
Exact I/O shape
Overall 62%
gpt-5
Azure
In $1.2500 / 1M tokens
Out $10.0000 / 1M tokens
pdf
Output: text
VisionFunction callingTool choicePrompt caching
128.0K
Exact I/O shape
Overall 60%
gpt-5-2025-08-07
Azure
In $1.2500 / 1M tokens
Out $10.0000 / 1M tokens
pdf
Output: text
VisionFunction callingTool choicePrompt caching
128.0K
Exact I/O shape
Overall 60%
gpt-5-chat
Azure
In $1.2500 / 1M tokens
Out $10.0000 / 1M tokens
pdf
Output: text
VisionFunction callingTool choicePrompt caching
16.4K
Exact I/O shape
Overall 56%
gpt-5-chat-latest
Azure
In $1.2500 / 1M tokens
Out $10.0000 / 1M tokens
pdf
Output: text
VisionFunction callingTool choicePrompt caching
16.4K
Exact I/O shape
Overall 56%

Sources

Source links
Pricing dataLiteLLM model cost map
Synced at2026-05-28
Catalog generated2026-07-13T14:21:55.110Z