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Gemini 2.5 Flash Preview 09 2025
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Gemini 2.5 Flash Preview 09 2025

gemini-2.5-flash-preview-09-2025
Google
This latest 2.5 Flash model comes with improvements in two key areas we heard consistent feedback on: Better agentic tool use: We've improved how the model uses tools, leading to better performance in more complex, agentic and multi-step applications. This model shows noticeable improvements on key agentic benchmarks, including a 5% gain on SWE-Bench Verified, compared to our last release (48.9% → 54%). More efficient: With thinking on, the model is now significantly more cost-efficient—achieving higher quality outputs while using fewer tokens, reducing latency and cost (see charts above).

Pricing

PricingCache ReadInput AudioInput Audio Cached Web SearchCache Storage
$0.3$2.499
$0.075/M tokens$0.999/M tokens$0.249/M tokens$0.035/request$1/h/M tokens

Input Modalities

  • Text
  • Vision
  • Audio
  • Video

Output Modalities

  • Text

Context length

  • 1.05M tokens

Max output

  • 65.5K tokens

Capabilities

  • Thinking
  • Streaming
  • Tool calling
  • Web search
  • URL context
  • Code interpreter
  • Computer use
  • File search
  • Memory tool
  • Structured outputs
  • Citations
  • Prompt caching
  • Background mode
  • Server-side sessions

Providers

VertexAI gemini-2.5-flash-preview-09-2025
Pricing$0.3$2.499
Cache Read$0.075/M tokens
Input Audio$0.999/M tokens
Input Audio Cached $0.249/M tokens
Web Search$0.035/request
Cache Storage$1/h/M tokens
Context1M
Max output65K
Latency0.5S
Throughput144.3TPS
Uptime
0.00% uptime 2 days ago
0.00% uptime yesterday
0.00% uptime today
Google AI Studio gemini-2.5-flash-preview-09-2025
Pricing$0.3$2.499
Cache Read$0.075/M tokens
Input Audio$0.999/M tokens
Input Audio Cached $0.249/M tokens
Web Search$0.035/request
Cache Storage$1/h/M tokens
Context1M
Max output65K
Latency0.4S
Throughput121.1TPS
Uptime
0.00% uptime 2 days ago
0.00% uptime yesterday
0.00% uptime today

Performance for gemini-2.5-flash-preview-09-2025

Uptime is the percentage of requests that succeeded over the past 72 hours. AIHubMix continuously monitors every provider and automatically retries with the next-best provider when one returns an error or responds too slowly; Latency is total round-trip time (lower is better); Throughput is how fast the model writes (tokens per second, higher is better).

Uptime
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Latency
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Throughput
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Try this model

Python
import os
from openai import OpenAI

client = OpenAI(
    api_key=os.environ["AIHUBMIX_API_KEY"],
    base_url="https://shkq.org/v1",
)

response = client.chat.completions.create(
    model="gemini-2.5-flash-preview-09-2025",
    messages=[
      {
        "role": "user",
        "content": "Hello, how are you?"
      }
    ],
    max_tokens=1024,
    stream=False,
)

print(response.choices[0].message.content)

Frequently asked questions

What is Gemini 2.5 Flash Preview 09 2025?

This latest 2.5 Flash model comes with improvements in two key areas we heard consistent feedback on: Better agentic tool use: We've improved how the model uses tools, leading to better performance in more complex, agentic and multi-step applications. This model shows noticeable improvements on key agentic benchmarks, including a 5% gain on SWE-Bench Verified, compared to our last release (48.9% → 54%). More efficient: With thinking on, the model is now significantly more cost-efficient—achieving higher quality outputs while using fewer tokens, reducing latency and cost (see charts above).

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