Key Specifications

SpecificationGemini 1.5 ProGemini 1.5 Flash
Vendorgooglegoogle
Version1.5-pro1.5-flash
Release Date2024-02-152024-05-14
Context Window2e+06 tokens1e+06 tokens
Input Modalitiestext, image, audio, videotext, image, audio, video
Output Modalitiestexttext
LicenseProprietaryProprietary
SOC2✓✓
HIPAA✗✗
GDPR✓✓
ISO 27001✓✓

Benchmark Results

BenchmarkGemini 1.5 ProGemini 1.5 FlashWinner
ARC—93.4Gemini 1.5 Flash
BBH8471.7Gemini 1.5 Pro
GPQA—38.5Gemini 1.5 Flash
GSM8K91.775.2Gemini 1.5 Pro
HUMANEVAL71.967.5Gemini 1.5 Pro
IFEVAL—68Gemini 1.5 Flash
MATH58.553.2Gemini 1.5 Pro
MMLU85.976Gemini 1.5 Pro
MUSR—46.1Gemini 1.5 Flash
WINOGRANDE—78.9Gemini 1.5 Flash

Pricing Comparison

Tier (per Mtok)Gemini 1.5 ProGemini 1.5 Flash
Input$1.25$0.075
Output$5$0.3
Cache Read$0.3125$0
Cache Write$1.25$0

Gemini 1.5 Pro contra Gemini 1.5 Flash

Descripción del modelo

Gemini 1.5 Pro and Gemini 1.5 Flash are both notable options in the AI model market. This page compares their benchmarks, pricing, and compliance.

Especificaciones clave

ProveedorFecha de lanzamientoVentana de contextoLicencia
Google / Google2024-02-15 / 2024-05-142000K / 1000KProprietary / Proprietary

Rendimiento en benchmarks

BenchmarkGemini 1.5 ProGemini 1.5 FlashGanador
ARC—93.4B
BBH (BIG-Bench Hard)84.071.7A
GPQA—38.5B
GSM8K (Grade School Math 8K)91.775.2A
HumanEval71.967.5A
IFEval—68.0B
MATH58.553.2A
MMLU (Massive Multitask Language Understanding)85.976.0A
MUSR—46.1B
WinoGrande—78.9B

Comparación de precios

EntradaSalidaLectura cachéEscritura caché
— / —— / —— / —— / —

por millón de tokens — A / B

Fortalezas & Debilidades

Gemini 1.5 Pro

  • ✅ MMLU score 85.9, strong knowledge reasoning.
  • ✅ GSM8K 91.7, robust math reasoning.
  • ✅ 支持文本、图像、音频多模态输入。
  • ✅ 上下文窗口 2000K,支持长文本。
  • ⚠️ 闭源专有模型,不支持自托管。

Gemini 1.5 Flash

  • ✅ 支持文本、图像、音频多模态输入。
  • ✅ 上下文窗口 1000K,支持长文本。
  • ⚠️ 闭源专有模型,不支持自托管。

Opinión del editor

Gemini 1.5 Pro and Gemini 1.5 Flash each have their strengths. Choose based on workload (code, long context, vision), referencing the tables above.

Preguntas frecuentes

Which model is better for coding tasks?

Refer to the HumanEval benchmark table; the model with a higher score is better suited for coding tasks.

Which model is cheaper?

Refer to the pricing comparison table above; the model with lower input/output prices is more cost-effective.

Which has a longer context window?

Refer to the key specifications table; the model with a larger context window is better for long documents.

Referencias

Editor's Take

See Editor's Take section.