Gemma 3 12B
Gemma 3 12B by Google: 5 offers. From €0.045 per 1M input tokens. No offer with EU processing is listed.
Calculate costs for this modelCompare offersView price history
Profile
| Profile | |
|---|---|
| Developer | |
| Type | Language models |
| Origin | US |
| Input types | text+bild |
| Context (tokens) | 131,072 |
| Max. output (tokens) | 16,384 |
| Reasoning | ohne |
| Parameters (bn) | 12.19 |
| Open weights | ✓ yes |
| Licence | Gemma Terms of Use |
| VRAM at 4-bit (GB) | 11 (RTX PRO 4000) |
| Released | – |
searchit Entity Extraction (24 Sept 2026): 14.2 %
Offers with processing in the EU (0)
No offers in this group.
Offers outside the EU (5)
| Provider | Country | Variant | Input | Output | Source | As of |
|---|---|---|---|---|---|---|
| AWS Bedrock | US | flex | €0.045 | €0.13 | pricing.us-east-1.amazonaws.com | 14 Oct 2026 |
| DeepInfra | US | standard | €0.045 | €0.13 | deepinfra.com | 14 Oct 2026 |
| AWS Bedrock | US | standard | €0.08 | €0.26 | pricing.us-east-1.amazonaws.com | 14 Oct 2026 |
| AWS Bedrock | US | priority | €0.14 | €0.46 | pricing.us-east-1.amazonaws.com | 14 Oct 2026 |
| Cloudflare Workers AI | US | standard | €0.31 | €0.50 | developers.cloudflare.com | 10 Oct 2026 |
€ per 1M tokens. Source: providers' pricing pages, read and checked by searchit. As of 14 Oct 2026.
AI Act
Whether the developer has signed the Code of Practice for general-purpose AI models: unknown. What this means is explained under “EU and AI Act”. EU processing and AI Act
Benchmarks
| Benchmarks | |
|---|---|
| GPQA Diamond (Artificial Analysis) | 34.9 |
| Humanity's Last Exam (Artificial Analysis) | 4.2 |
| Berkeley Function-Calling Leaderboard V4 | 30.4 |
| OTIS Mock AIME 2024-2025 (Epoch AI) | 16.7 |
| Vectara HHEM-2.3 | 4.4 |
| Vectara HHEM-2.3 – antwortrate | 97.4 |
| Vectara HHEM-2.3 – halluzination | 4.4 |
| LLMStructBench: Benchmarking Large Language Model Structured Data Extraction (arXiv:2602.14743) | 0.72 |
| LLMStructBench: Benchmarking Large Language Model Structured Data Extraction (arXiv:2602.14743) – doc micro | 0.49 |
| LLMStructBench: Benchmarking Large Language Model Structured Data Extraction (arXiv:2602.14743) – f1 micro | 0.95 |
| LLMStructBench: Benchmarking Large Language Model Structured Data Extraction (arXiv:2602.14743) – score | 0.72 |
| searchit Extraktions-Messlauf REPO-9 (PROMPT-CRAWLER-TEXT-START, 8 Dokumente × 3 Läufe) – treffer beziehungen | 2.9 |
| searchit Extraktions-Messlauf REPO-9 (PROMPT-CRAWLER-TEXT-START, 8 Dokumente × 3 Läufe) – treffer entitaeten | 25.5 |
| MMLU-Pro (TIGER-Lab Leaderboard) | 60.6 |