Google DeepMind Commercial APIStatus: preview

Gemini 2.0 Pro (Experimental)

Google's flagship intelligence model engineered for complex coding, mathematical proofs, and 2M token context.

Released: Feb 5, 2025
Last Verified: Aug 10, 2026
Context Window

2,000k

Tokens

Max Output

8.192k

Output limit

Architecture

Multimodal Transformer

Model family

Parameters

Not Disclosed

Total / Active

Input Token Cost

$0.00

Per 1M tokens

Output Token Cost

$0.00

Per 1M tokens

Model Overview

Gemini 2.0 Pro is Google's most capable model for complex coding and deep reasoning tasks. It combines a 2-million token context window with native multimodal capabilities and advanced world knowledge.

Developer Implementation Notes

Currently in experimental preview on Google AI Studio. Exceptional performance on complex multi-file coding and math.

Key Strengths

  • Gigantic 2,000,000 token context window
  • Top-tier coding and mathematical benchmark performance
  • Comprehensive multimodal input support (video/audio/images/text)

Limitations & Boundaries

  • Experimental release status with potential endpoint changes
  • Higher latency than Gemini 2.0 Flash

Capabilities & Modalities

Modalities:text, image, audio, video
Reasoning Chains:Supported
Tool / Function Calling:Supported
Structured Outputs:Supported
Fine-Tuning:No
Local Deployment:Cloud Only

Best Production Use Cases

  • Entire repository codebase refactoring and analysis
  • Hour-long video understanding and multimodal querying
  • Complex scientific literature synthesis

Verified Benchmark Results

Standardized evaluations with methodology notes and authoritative citation links.

View all industry benchmarks →
Coding Official
LiveCodeBench

58.4%

Pass@1, 0-shot code generation

Reasoning & Math Official
GPQA Diamond

74.2%

Zero-shot Chain-of-Thought

Reasoning & Math Official
AIME (2024/2025)

76.5%

Pass@1 mathematical reasoning

Multimodal Official
MMMU

76.2%

Multimodal visual benchmark

Pricing & Inference Cost Calculator

Token Cost Estimator – Gemini 2.0 Pro (Experimental)

Calculate projected inference spend with prompt caching

Quick Workload Presets

Input Tokens / Req2,000
100100k200k
Output Tokens / Req500
5016k32k
Number of Requests1,000
125k50k
Cache Hit Rate0%
0% (No cache)50%90% (Max)
Total Input Spend

$0.0000

2.00M input tokens

Total Output Spend

$0.0000

0.50M output tokens

Estimated Total Cost

$0.00

Avg: $0.00000 / req

Rates: $0.00 in / $0.00 out per million tokens (Google AI Studio (Preview))Last verified: Aug 10, 2026

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Data Accuracy & Verification Notice

AI model specifications, pricing records, and benchmark metrics published on this platform are compiled directly from authoritative sources (official provider documentation, research papers, and verified evaluation harnesses). Benchmark results reflect specific test harnesses and prompting methodologies; scores are not directly comparable across differing evaluation setups.