Gemini 2.5 Flash Lite

Lean Gemini 2.5 lane for cheap multimodal traffic and quick agents
- Context
- 1.0M
- Released
- 1y ago
- Input / 1M tokens
- $0.10
- Output / 1M tokens
- $0.40
- Cached input / 1M tokens
- $0.01
- Cache write / 1M tokens
- $0.08
Sources:models.devOpenRouter
Benchmarks
DeepSWE is the primary coding benchmark where an exact model evaluation exists. Other sourced evaluations appear below; missing scores are not zero.
Not evaluated in DeepSWE 1.1 as of 2026-09-22. Results are only shown for exact model versions in the official dataset. Official leaderboard.
No benchmark results have been matched to this model yet.
Specifications
- Developer
- Google DeepMind
- Model family
- Gemini
- Type
- Language model
- Predecessor
- —
- Successor
- —
- Released
- June 17, 2025
- Model ID
google/gemini-2.5-flash-lite- Openness
- Closed
- License
- —
- Input modalities
- text, image, file, audio, video
- Output modalities
- text
- Modality
- text+image+file+audio+video->text
- Tokenizer
- Gemini
- Max output tokens
- 66K
- Knowledge cutoff
- 2025-01
- Hugging Face
- —
- Source freshness
- Metadata synced Oct 8, 2026, 10:17 PM UTC
Additional source evidence
- Source model
- google/gemini-2.5-flash-lite
- Source family
- gemini-flash-lite
- Last updated
- 2025-06-17
- Knowledge cutoff
- 2025-01
- Model context
- 1.0M
- Model output limit
- 66K
- Open weights
- No
- File attachments
- Yes
- Reasoning
- Yes
- Tool calling
- Yes
- Structured output
- Yes
- Temperature control
- Yes
Published benchmarks
Complete source record (JSON)
{
"id": "google/gemini-2.5-flash-lite",
"name": "Gemini 2.5 Flash-Lite",
"description": "Lean Gemini 2.5 lane for cheap multimodal traffic and quick agents",
"family": "gemini-flash-lite",
"last_updated": "2025-06-17",
"knowledge": "2025-01",
"attachment": true,
"reasoning": true,
"tool_call": true,
"structured_output": true,
"temperature": true,
"modalities": {
"input": [
"text",
"image",
"audio",
"video",
"pdf"
],
"output": [
"text"
]
},
"limit": {
"context": 1048576,
"output": 65536
},
"benchmarks": [
{
"name": "Artificial Analysis Coding Index",
"score": 9.5,
"source": "https://openrouter.ai/google/gemini-2.5-flash-lite/benchmarks",
"metric": "index",
"date": "2026-03-11"
},
{
"name": "SciCode",
"score": 19.3,
"source": "https://openrouter.ai/google/gemini-2.5-flash-lite/benchmarks",
"metric": "percent correct",
"date": "2026-03-11"
},
{
"name": "Terminal-Bench Hard",
"score": 4.5,
"source": "https://openrouter.ai/google/gemini-2.5-flash-lite/benchmarks",
"metric": "success rate",
"date": "2026-03-11"
}
],
"release_date": "2025-06-17",
"open_weights": false
}Infrastructure
Provider availability
| Provider | Endpoint | Context | Input /M tokens | Output /M tokens | Cached input /M tokens | Cache write /M tokens | Uptime 1d | Data handling |
|---|---|---|---|---|---|---|---|---|
| google-ai-studio/flex | 1.0M | $0.05 | $0.20 | $0.005 | $0.04 | 100.00% | ZDR: NoTraining: Unknown Prompt logging: Unknown Retention: Unknown Checked 2026-10-15 | |
| google-ai-studio/flexBatch pricing | 1.0M | $0.05 | $0.20 | $0.005 | $0.04 | 100.00% | ZDR: NoTraining: Unknown Prompt logging: Unknown Retention: Unknown Checked 2026-10-15 | |
| google-vertex/eu | 1.0M | $0.10 | $0.40 | $0.01 | $0.08 | 95.21% | ZDR: YesTraining: Unknown Prompt logging: Unknown Retention: Unknown Checked 2026-10-15 | |
| google-vertex | 1.0M | $0.10 | $0.40 | $0.01 | $0.08 | 100.00% | ZDR: YesTraining: Unknown Prompt logging: Unknown Retention: Unknown Checked 2026-10-15 | |
| google-vertex/euBatch pricing | 1.0M | $0.10 | $0.40 | $0.01 | $0.08 | 95.76% | ZDR: NoTraining: Unknown Prompt logging: Unknown Retention: Unknown Checked 2026-10-15 | |
| google-vertexBatch pricing | 1.0M | $0.10 | $0.40 | $0.01 | $0.08 | 100.00% | ZDR: NoTraining: Unknown Prompt logging: Unknown Retention: Unknown Checked 2026-10-15 | |
| google-ai-studio | 1.0M | $0.10 | $0.40 | $0.01 | $0.08 | 99.93% | ZDR: NoTraining: Unknown Prompt logging: Unknown Retention: Unknown Checked 2026-10-15 | |
| google-ai-studioBatch pricing | 1.0M | $0.10 | $0.40 | $0.01 | $0.08 | 99.93% | ZDR: NoTraining: Unknown Prompt logging: Unknown Retention: Unknown Checked 2026-10-15 | |
| google-ai-studio/priority | 1.0M | $0.18 | $0.72 | $0.02 | $0.15 | 100.00% | ZDR: NoTraining: Unknown Prompt logging: Unknown Retention: Unknown Checked 2026-10-15 | |
| google-ai-studio/priorityBatch pricing | 1.0M | $0.18 | $0.72 | $0.02 | $0.15 | 100.00% | ZDR: NoTraining: Unknown Prompt logging: Unknown Retention: Unknown Checked 2026-10-15 |
Provider data:OpenRouter
Text provenance
Gemini app/webGoogle SynthID text watermarking
Google DeepMind says text generated in the Gemini app and web experience is watermarked with SynthID by adjusting token probabilities.
Official explanation