Key Specifications
| Vendor | google |
|---|
| Version | 2.0-flash |
|---|
| Release Date | 2024-12-11 |
|---|
| Context Window | 1.048576e+06 tokens |
|---|
| Input Modalities | text, image, audio, video |
|---|
| Output Modalities | text |
|---|
| License | Proprietary |
|---|
| Documentation | https://ai.google.dev/gemini-api/docs |
|---|
Benchmark Performance
| Benchmark | Score | Unit | Evaluated At | Notes | Source |
|---|
| MMLU | 86.3 | % | 2024-12-11 | 5-shot | view |
| HUMANEVAL | 90.7 | pass@1 | 2024-12-11 | — | view |
| GSM8K | 92.7 | % | 2024-12-11 | 0-shot CoT | view |
| MATH | 71.3 | % | 2024-12-11 | 0-shot CoT | view |
| BBH | 83.4 | % | 2024-12-11 | 3-shot CoT | view |
| GPQA | 55 | % | 2024-12-11 | 0-shot | view |
| IFEVAL | 85.9 | % | 2024-12-11 | prompt_strict | view |
| ARC | 95.7 | % | 2024-12-11 | challenge | view |
| MUSR | 69.3 | % | 2024-12-11 | 0-shot | view |
| WINOGRANDE | 89.5 | % | 2024-12-11 | 0-shot | view |
Pricing
| Tier | Price | Currency |
|---|
| Input | $0.1 / Mtok | USD |
| Output | $0.4 / Mtok | USD |
| Cache Read | $0 / Mtok | USD |
| Cache Write | $0 / Mtok | USD |
Source:
https://ai.google.dev/pricing
· as of 2024-12-11
Compliance
- Data Residency: US
- SOC2: ✓
- HIPAA: ✗
- GDPR: ✓
- ISO 27001: ✓
Gemini 2.0 Flash
Ikhtisar Model
Google Gemini 2.0 Flash 新一代模型, 1M 上下文, 原生工具调用与多模态输出, 性能超越 1.5 Pro。
Spesifikasi Inti
| Vendor | Versi | Tanggal Rilis | Jendela Konteks | Modalitas Input | Modalitas Output | Lisensi |
|---|
| Google | 2.0-flash | 2024-12-11 | 1048K | text, image, audio, video | text | Proprietary |
Kinerja Benchmark
| Benchmark | Skor | Satuan | Catatan |
|---|
| MMLU (Massive Multitask Language Understanding) | 86.3 | % | 5-shot |
| HumanEval | 90.7 | pass@1 | — |
| GSM8K (Grade School Math 8K) | 92.7 | % | 0-shot CoT |
| MATH | 71.3 | % | 0-shot CoT |
| BBH (BIG-Bench Hard) | 83.4 | % | 3-shot CoT |
| GPQA | 55.0 | % | 0-shot |
| IFEval | 85.9 | % | prompt_strict |
| ARC | 95.7 | % | challenge |
| MUSR | 69.3 | % | 0-shot |
| WinoGrande | 89.5 | % | 0-shot |
Harga
| Input | Output | Baca Cache | Tulis Cache |
|---|
| — | — | — | — |
per juta token
Kelebihan
- MMLU score 86.3, strong knowledge reasoning.
- HumanEval 90.7, excellent code generation.
- GSM8K 92.7, robust math reasoning.
- 支持文本、图像、音频多模态输入。
Kekurangan
Kasus Penggunaan
- 代码生成与调试
- 视觉与图像理解
- Agent 工作流与工具调用
Referensi