AI 模型情報

Gemini 2.5 Flash

google/gemini-2-5-flash

出品方: Google · 系列: gemini-flash · 發布 2025-06-17 · 知識截止: 2025-01

$0.300
輸入 / 1M token
$2.50
輸出 / 1M token
1.05M
上下文長度
66K
最大輸出

Prices in USD per 1M tokens. Unknown means the provider does not publish per-token pricing.

能力清單

工具呼叫推理結構化輸出附件開放權重溫度可調
支援模態: 輸入 text, image, audio, video, pdf · 輸出 text

Model fit scores

0–100 · higher is better

These scores reward declared capabilities, context size, price and provider availability — they are not benchmark results. Use them as a directional signal alongside your own evaluation.

Coding100
  • Tool calling40/40
  • Structured output20/20
  • Reasoning10/10
  • Context window (100K → 1M)20/20
  • Provider availability10/10
Agents100
  • Tool calling35/35
  • Structured output25/25
  • Reasoning15/15
  • Output token limit15/15
  • Provider availability10/10
JSON / structured output94
  • Structured output / JSON mode50/50
  • Tool calling20/20
  • Temperature control10/10
  • Price-friendly for high-volume14/20
Cost efficiency56
  • Headline price (log-scaled)51/95
  • Has prompt-cache pricing5/5
Long context91
  • Context window (100K → 2M)81/90
  • Has published price for full window10/10
Vision100
  • Accepts image input50/50
  • Context window (10K → 1M)30/30
  • Has published price10/10
  • Provider availability10/10
Production-readiness94
  • Number of independent providers40/40
  • Has published per-token price20/20
  • Context window ≥ 8K15/15
  • No data inconsistencies across providers4/10
  • Official model (not derivative)15/15

Cost Efficiency Index

Open full calculator →

Estimated cost using the recommended provider's headline rate. Each scenario fixes average input/output tokens — the assumptions are shown in the third column.

ScenarioCostAssumption
RAG answer
per 1,000 RAG answers
$2.75
< $0.01 per request
5K input tokens (query + 4 retrieved chunks of ~1K each) and a 500-token answer. Typical SaaS knowledge-base bot.
Support ticket triage
per 10,000 tickets
$5.50
< $0.01 per request
1K input tokens (ticket body + system prompt) and a 100-token JSON classification reply. High-volume customer support.
Data extraction
per 1,000 documents
$1.85
< $0.01 per request
2K input tokens (a single document page) and a 500-token JSON extraction. ETL / invoice / form pipelines.
Code review
per 1,000 PRs
$4.90
< $0.01 per request
8K input tokens (diff + surrounding files) and a 1K-token review comment. PR-bot workloads.
Agent step
per 1,000 steps
$5.10
< $0.01 per request
12K input tokens (long-running tool history) and a 600-token tool-call decision. Cost per agent step.

定價詳情

推薦定價來自 google · gemini-2.5-flash

$0.300
輸入
$2.50
輸出
$0.030
快取讀取
$1.00
輸入音訊

最便宜的渠道: qihang-ai · $0.090 輸入 + $0.710 輸出

於 21 家供應商可用

服務商服務商模型 ID輸入 / 1M輸出 / 1M上下文發布日期
Google
google
gemini-2.5-flash$0.300$2.501.05M2025-03-20
Vertex
google-vertex
gemini-2.5-flash$0.300$2.501.05M2025-06-17
OpenRouter
openrouter
google/gemini-2.5-flash$0.300$2.501.05M2025-07-17
Vercel AI Gateway
vercel
google/gemini-2.5-flash$0.300$2.501.05M2025-03-20
302.AI
302ai
gemini-2.5-flash$0.300$2.501M2025-06-17
NanoGPT
nano-gpt
gemini-2.5-flash$0.300$2.501.05M2025-06-05
Abacus
abacus
gemini-2.5-flash$0.300$2.501.05M2025-03-20
Perplexity Agent
perplexity-agent
google/gemini-2.5-flash$0.300$2.501.05M2025-03-20
Jiekou.AI
jiekou
gemini-2.5-flash$0.270$2.251.05M2026-01
ZenMux
zenmux
google/gemini-2.5-flash$0.300$2.501.05M2025-06-17
Qiniu
qiniu-ai
gemini-2.5-flashUnknownUnknown1.05M2025-08-05
Kilo Gateway
kilo
google/gemini-2.5-flash$0.300$2.501.05M2025-07-17
SAP AI Core
sap-ai-core
gemini-2.5-flash$0.300$2.501.05M2025-03-25
Poe
poe
google/gemini-2.5-flash$0.210$1.801.07M2025-04-26
Helicone
helicone
gemini-2.5-flash$0.300$2.501.05M2025-06-17
FrogBot
frogbot
gemini-2.5-flash$0.300$2.501.05M2025-07-17
AIHubMix
aihubmix
gemini-2.5-flash$0.300$2.501.05M2025-03-20
Requesty
requesty
google/gemini-2.5-flash$0.300$2.501.05M2025-06-17
LLM Gateway
llmgateway
gemini-2.5-flash$0.300$2.501.05M2025-03-20
FastRouter
fastrouter
google/gemini-2.5-flash$0.300$2.501.05M2025-06-17
QiHang
qihang-ai
gemini-2.5-flash$0.090$0.7101.05M2025-12-17

各渠道資料存在不一致

  • context_window varies: 1000000, 1048000, 1048576, 1048756, 1065535
  • release_date varies (span 287d): 2025-03-20, 2025-03-25, 2025-04-26, 2025-06-05, 2025-06-17, 2025-07-17, 2025-08-05, 2025-12-17, 2026-01
  • modalities varies across offerings

各服務商對此模型的回報值不一致。上方「核心數據」採用代表性服務商的值;逐項請以下表為準。

Frequently asked questions

How much does Gemini 2.5 Flash cost?

Gemini 2.5 Flash costs $0.300 per 1M input tokens and $2.50 per 1M output tokens, sourced from google. Cache reads, audio tokens and >200K-context tiers (where applicable) are listed in the Pricing detail block above.

What is the context window of Gemini 2.5 Flash?

Gemini 2.5 Flash has a context window of 1.05M tokens, with a max output of 66K tokens per reply. This is the total combined size of prompt + completion.

Does Gemini 2.5 Flash support tool calling?

Yes. Gemini 2.5 Flash supports tool calling (function calling). This makes it suitable for production agent and automation workloads where the model has to invoke external functions reliably.

Does Gemini 2.5 Flash support structured output / JSON mode?

Yes. Gemini 2.5 Flash supports structured output / JSON-schema-constrained decoding. This makes it suitable for production agent and automation workloads where the model has to invoke external functions reliably.

Can Gemini 2.5 Flash accept image input?

Yes. Gemini 2.5 Flash accepts both text and image input. Vision pricing per image is usually billed on top of the regular token rate — check Google's docs for the exact rule.

Is Gemini 2.5 Flash open-weight?

No. Gemini 2.5 Flash is a proprietary model — only Google (and any approved hosting partners) can serve it. The pricing above reflects the cheapest API access.

What are the best alternatives to Gemini 2.5 Flash?

If Gemini 2.5 Flash doesn't fit, consider Gemini 2.5 Pro, Gemini 3 Flash Preview, Gemma 3 27B. Each one targets the same use case — see the Related links below for direct head-to-head pages.

Where does this data come from?

All numbers come from the public models.dev API and are normalised into a single canonical model record. We re-pull daily and write any changes (price, context, capability) to the /changelog page.

最近更新:

Data is sourced from models.dev and normalized for comparison. Prices and capabilities may change. Always verify critical production decisions with the provider's official documentation.