Google DeepMind
Gemini 2.5 Pro TTS
Audio output
Speech generation model for controllable voice, narration, and audio delivery
- Released
- 1y ago
- Pricing
- Not published
Sources:models.dev
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
- Audio model
- Predecessor
- —
- Successor
- —
- Released
- September 30, 2025
- Model ID
google/gemini-2.5-pro-tts- Openness
- Closed
- License
- —
- Input modalities
- text
- Output modalities
- audio
- Modality
- text->audio
- Hugging Face
- —
- Source freshness
- Metadata synced Oct 8, 2026, 10:17 PM UTC
Additional source evidence
- Source model
- google/gemini-2.5-pro-tts
- Source family
- gemini-pro
- Last updated
- 2025-12-10
- Knowledge cutoff
- 2025-01
- Model context
- 33K
- Model output limit
- 16K
- Open weights
- No
- File attachments
- No
- Reasoning
- No
- Tool calling
- No
- Temperature control
- No
Complete source record (JSON)
{
"id": "google/gemini-2.5-pro-tts",
"name": "Gemini 2.5 Pro TTS",
"description": "Speech generation model for controllable voice, narration, and audio delivery",
"family": "gemini-pro",
"last_updated": "2025-12-10",
"knowledge": "2025-01",
"attachment": false,
"reasoning": false,
"tool_call": false,
"temperature": false,
"modalities": {
"input": [
"text"
],
"output": [
"audio"
]
},
"limit": {
"context": 32768,
"output": 16384
},
"release_date": "2025-09-30",
"open_weights": false
}Infrastructure
Provider availability
Provider-specific media pricing is not available in the imported source data yet.
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