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
Input Modalities
- Text
- Vision
- Audio
- Video
Output Modalities
- Text
Capabilities
- Tools
- Tool calling
- Structured outputs
Providers
VertexAI gemini-2.5-flash-preview-09-2025
Pricing$0.300$2.499
Cache Read$0.03/M tokens
Input Audio$0.9999/M tokens
Input Audio Cached $0.0999/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$0.300$2.499
Cache Read$0.03/M tokens
Input Audio$0.9999/M tokens
Input Audio Cached $0.0999/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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Python
