Gemini 4 Argon
Google DeepMind frontier model for complex, long-horizon software engineering, enterprise knowledge work, and cybersecurity defense.
- Context
- 1.0M
- Released
- 2w ago
- Input / 1M tokens
- $2.00
- Output / 1M tokens
- $10.00
- Cached input / 1M tokens
- $0.10
- Cache write / 1M tokens
- $0.19
Sources:OpenRouter
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.
Other published benchmarks
| Evaluation | Reported score and source |
|---|---|
| GPQA diamond | |
| SimpleQA Verified |
Benchmark compilation: Epoch AI, Capabilities & benchmarking (CC BY attribution). Scores are converted to percentages and model names matched to the Vertical Tabs catalog. Individual evaluations are credited to their original sources. External results may carry separate licences and evaluation configurations; do not interpret scores from different harnesses as directly comparable.
Specifications
- Developer
- Google DeepMind
- Model family
- Gemini
- Predecessor
- —
- Successor
- —
- Released
- September 30, 2026
- Model ID
google/gemini-4-argon- Openness
- Closed
- License
- —
- Input modalities
- audio, file, image, text, video
- Output modalities
- text
- Modality
- text+image+file+audio+video->text
- Tokenizer
- Gemini
- Max output tokens
- 66K
- Hugging Face
- —
- Source freshness
- Metadata synced Oct 6, 2026, 11:01 PM UTC
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 | $1.00 | $5.00 | $0.05 | $0.09 | 100.00% | ZDR: NoTraining: Unknown Prompt logging: Unknown Retention: Unknown Checked 2026-10-15 | |
| google-ai-studio/flexBatch pricing | 1.0M | $1.00 | $5.00 | $0.05 | $0.09 | 100.00% | ZDR: NoTraining: Unknown Prompt logging: Unknown Retention: Unknown Checked 2026-10-15 | |
| google-vertex/global | 1.0M | $2.00 | $10.00 | $0.10 | $0.19 | 99.38% | ZDR: YesTraining: Unknown Prompt logging: Unknown Retention: Unknown Checked 2026-10-15 | |
| google-vertex/globalBatch pricing | 1.0M | $2.00 | $10.00 | $0.10 | $0.19 | 99.24% | ZDR: NoTraining: Unknown Prompt logging: Unknown Retention: Unknown Checked 2026-10-15 | |
| google-ai-studio | 1.0M | $2.00 | $10.00 | $0.10 | $0.19 | 99.58% | ZDR: NoTraining: Unknown Prompt logging: Unknown Retention: Unknown Checked 2026-10-15 | |
| google-ai-studioBatch pricing | 1.0M | $2.00 | $10.00 | $0.10 | $0.19 | 99.51% | ZDR: NoTraining: Unknown Prompt logging: Unknown Retention: Unknown Checked 2026-10-15 | |
| google-vertex/us | 1.0M | $2.20 | $11.00 | $0.11 | $0.19 | 100.00% | ZDR: YesTraining: Unknown Prompt logging: Unknown Retention: Unknown Checked 2026-10-15 | |
| google-vertex/usBatch pricing | 1.0M | $2.20 | $11.00 | $0.11 | $0.19 | 100.00% | ZDR: NoTraining: Unknown Prompt logging: Unknown Retention: Unknown Checked 2026-10-15 | |
| google-vertex/global/priority | 1.0M | $3.60 | $18.00 | $0.18 | $0.34 | 100.00% | ZDR: YesTraining: Unknown Prompt logging: Unknown Retention: Unknown Checked 2026-10-15 | |
| google-vertex/global/priorityBatch pricing | 1.0M | $3.60 | $18.00 | $0.18 | $0.34 | 100.00% | ZDR: NoTraining: Unknown Prompt logging: Unknown Retention: Unknown Checked 2026-10-15 | |
| google-ai-studio/priority | 1.0M | $3.60 | $18.00 | $0.18 | $0.34 | 100.00% | ZDR: NoTraining: Unknown Prompt logging: Unknown Retention: Unknown Checked 2026-10-15 | |
| google-ai-studio/priorityBatch pricing | 1.0M | $3.60 | $18.00 | $0.18 | $0.34 | 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