Gemini 2.5 Flash
Gemini 2.5 Flash is Google's Flash-tier workhorse in the Gemini 2.5 family, positioned as its price-performance choice for low-latency, high-volume tasks that still need reasoning.
input · usd / 1m tok
$0.30
output · usd / 1m tok
$2.50
context window
1mtokens
modalities · in → out
takes text, image, audio and video in, gives text out
pricing
base api ratesusd per 1m tokens
- input
- $0.30
- output
- $2.50
- cache read
- $0.03
- audio input
- $1.00
providers
Google hosts Gemini 2.5 Flash. Impossibl routes your request intelligently and handles failover automatically when a provider is down.
- Google
specifications
takes text, image, audio and video in, gives text outgoogle/gemini-2.5-flash
- creatorGoogle
- model typeText generation
- context window1,000,000 tokens
- maximum outputnot published
- input
takes text, image, audio and video in, gives text out
- outputtext
- tool callingnot verified
- releasedjun 17, 2025
- endpoint
/v1/chat/completions
unknown means the public catalog does not establish that fact. a model's documented capabilities can differ from what a particular api supports. see the model documentation for integration details.
try it · your prompt, this model, live
# responses API
import os
from openai import OpenAI
client = OpenAI(
api_key=os.environ["IMPOSSIBL_API_KEY"],
base_url="https://api.impossibl.com/v1",
)
resp = client.responses.create(
model="google/gemini-2.5-flash",
input="",
)
print(resp.output_text)
edit the prompt, then run
benchmarks
intelligence index
9.9#80 of 90 models on the gateway
- omniscience-42.6#75 of 86
- gpqa68.3%#75 of 88
- humanity’s last exam4.7%#79 of 89
- GPQA68.3%
- MMMU-Pro65.5%
- AIME 202560.3%
- AA-LCR49.9%
- LiveCodeBench49.5%
- IFBench39.0%
- Tau214.9%
- Terminal-Bench Hard12.1%
- Multilingual LCR8.3%
- Humanity’s Last Exam4.7%
- CritPt1.4%
- Intelligence Index9.85
- Omniscience Index-42.57
- intelligence index (API)9.9
each configuration is listed separately; these evaluations describe the tested model configuration, and performance and costs can differ on impossibl. unmeasured scores are omitted and api values keep their source units. last checked 2026-09-11.
compare Gemini 2.5 Flash with other models
frontier labs and open weights, best-ranked firstusd / 1m tok · in / out
- anthropic/claude-fable-5-1$10.00 / $50.00compare →
- openai/gpt-6-astra$10.00 / $50.00compare →
- meta/muse-spark-1.3$1.25 / $4.25compare →
- zai/glm-5.3$1.40 / $4.40compare →
frequently asked questions
What is Gemini 2.5 Flash?
Gemini 2.5 Flash is Google's Flash-tier workhorse in the Gemini 2.5 family, positioned as its price-performance choice for low-latency, high-volume tasks that still need reasoning. It carries the family's built-in thinking capability, so it can reason before responding across coding, mathematics, and scientific work at Flash speed.
How much does Gemini 2.5 Flash cost?
Gemini 2.5 Flash costs $0.30 per million input tokens and $2.50 per million output tokens through the Impossibl API. Cache reads cost $0.03 per million tokens. Audio input costs $1.00 per million audio input tokens. All rates are in USD.
What is the context length of Gemini 2.5 Flash?
Gemini 2.5 Flash has a 1,000,000-token context window through the Impossibl API.
What inputs and outputs does Gemini 2.5 Flash support?
Gemini 2.5 Flash accepts text, image, audio, and video as input. Gemini 2.5 Flash returns text.
How do I use Gemini 2.5 Flash through an API?
Gemini 2.5 Flash is available through the Impossibl API. Use google/gemini-2.5-flash as the model identifier with /v1/chat/completions. The quickstart explains how to create an API key and send your first request.
When was Gemini 2.5 Flash released?
Google released Gemini 2.5 Flash on June 17, 2025.
this page describes Gemini 2.5 Flash as listed by the impossibl public api. prices and availability come from that catalog, refreshed here every five minutes. this is an impossibl offering, not a comparison of independent hosting-provider quotes. model descriptions and release dates, where available, use the creator sources linked under the answers above.
view the source catalog ↗model as markdown ↗report a correction →