DiffusionGemma 26B A4B IT
Gemma 4 based discrete text diffusion model for fast chat, reasoning, and tool use
- Context
- 262K
- Released
- 4mo ago
- Parameters
- 26B
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
- —
- Type
- Language model
- Predecessor
- —
- Successor
- —
- Released
- June 9, 2026
- Model ID
google/diffusiongemma-26b-a4b-it- Openness
- Open weights
- License
- Apache 2.0
- Parameters
- 26B
- Input modalities
- text, image
- Output modalities
- text
- Modality
- text+image->text
- Max output tokens
- 33K
- Knowledge cutoff
- 2025-01
- Hugging Face
- —
- Source freshness
- Metadata synced Oct 8, 2026, 10:17 PM UTC
Additional source evidence
- Source model
- google/diffusiongemma-26b-a4b-it
- Source family
- gemma
- Last updated
- 2026-07-15
- Knowledge cutoff
- 2025-01
- Model context
- 262K
- Model output limit
- 33K
- Open weights
- Yes
- File attachments
- Yes
- Reasoning
- Yes
- Tool calling
- Yes
- Temperature control
- Yes
Downloadable weights
Complete source record (JSON)
{
"id": "google/diffusiongemma-26b-a4b-it",
"name": "DiffusionGemma 26B A4B IT",
"description": "Gemma 4 based discrete text diffusion model for fast chat, reasoning, and tool use",
"family": "gemma",
"last_updated": "2026-07-15",
"knowledge": "2025-01",
"attachment": true,
"reasoning": true,
"tool_call": true,
"temperature": true,
"modalities": {
"input": [
"text",
"image"
],
"output": [
"text"
]
},
"limit": {
"context": 262144,
"output": 32768
},
"release_date": "2026-06-09",
"open_weights": true,
"license": "Apache 2.0",
"weights": [
{
"label": "Hugging Face",
"url": "https://huggingface.co/google/diffusiongemma-26B-A4B-it"
}
]
}Infrastructure
Provider availability
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 explanationDeployment graph
Can I run this?
Vertical Tabs only shows compatibility when it has structured evidence tying this exact model to hardware, runtime, quantization, memory use, and observed performance.