Gemini 1.5 Pro vs Claude 3 Opus
Benchmarks, API Token Pricing, Context Window & Speed Comparison
Related topics (12)
Gemini 1.5 Pro by Google and Claude 3 Opus by Anthropic represent two of the frontier AI models analyzed in our comprehensive 2026 AI benchmark and LLM comparison. In this head-to-head evaluation, we examine API token pricing, context window specifications, inference speed (tokens per second), and empirical reasoning performance. From a pure economic perspective, Gemini 1.5 Pro holds a notable pricing advantage for token ingestion. On output generation, Gemini 1.5 Pro is more economical per million generated tokens. In data-heavy architectures requiring extensive repository or document analysis, Gemini 1.5 Pro provides an expanded memory horizon with 2,000K tokens. In latency-sensitive production environments, Gemini 1.5 Pro leads in tokens-per-second throughput, making it ideal for real-time conversational agents and high-concurrency workflows. Below is the complete empirical head-to-head breakdown across cost, speed, context, and capability matrices.
원하는 AI 모델 선택 및 실시간 비교
Select any AI models from our verified benchmark database to generate live side-by-side matrices.
Gemini 1.5 Pro
플래그십 프론티어 모델Google의 Gemini 1.5 Pro 모델은 2M 토큰 컨텍스트 윈도우와 입력 $1.25/1M 토큰, 출력 $5/1M 토큰의 합리적인 API 요금을 제공하며 코딩, 추론 및 엔터프라이즈 자동화에 최적화되어 있습니다.
$1.25 / 1M
$5.00 / 1M
2M tokens
32.5%
Claude 3 Opus
플래그십 프론티어 모델Anthropic의 Claude 3 Opus 모델은 200K 토큰 컨텍스트 윈도우와 입력 $15/1M 토큰, 출력 $75/1M 토큰의 합리적인 API 요금을 제공하며 코딩, 추론 및 엔터프라이즈 자동화에 최적화되어 있습니다.
$15.00 / 1M
$75.00 / 1M
200K tokens
32.2%
한눈에 보는 핵심 차이점
- Gemini 1.5 Pro is 13.5x cheaper for API usage (input + output tokens combined).
- Gemini 1.5 Pro has a larger context window (2M vs 200K tokens).
- Gemini 1.5 Pro is faster at 65 tok/s vs 30 tok/s.
- Gemini 1.5 Pro leads on SWE-bench coding (32.5% vs 32.2%).
| Feature | Gemini 1.5 Pro | Claude 3 Opus |
|---|---|---|
Intelligence Index Composite reasoning & knowledge score (0-100) | 46 | 44 |
Provider | Anthropic | |
Input Price Cost per million input tokens | $1.25 / 1M | $15.00 / 1M |
Output Price Cost per million output tokens | $5.00 / 1M | $75.00 / 1M |
Blended Price Weighted 7:2:1 cache:input:output per 1M | $0.97 / 1M | $11.55 / 1M |
Context Window Maximum input + output tokens | 2M tokens~3,000 A4 pages of text | 200K tokens~300 A4 pages of text |
Max Output Tokens Per single request | 8K | 4K |
Throughput Speed Tokens generated per second | 65 tok/s | 30 tok/s |
SWE-bench Verified Real-world software engineering | 32.5% | 32.2% |
GPQA Diamond Graduate-level reasoning | 58.5% | 50.4% |
Cached Input Price Prompt caching discount per 1M tokens | $0.31 / 1M | $1.50 / 1M |
부문별 우위 모델
At-a-glance decision framework검증된 벤치마크 점수 비교
Official evaluation metrics verified by independent third-party research labs.
Industry benchmark evaluating real-world GitHub issue resolution and multi-file debugging.
Challenging questions created by domain experts to test complex PhD-level reasoning.
Hardened reasoning and academic knowledge benchmark with reduced lucky-guess probability.
Crowdsourced human preference evaluation based on blind, head-to-head model battles.
Accuracy when reasoning over very large inputs that fill the model context window.
Tokens emitted per second during active generation streaming.
지연 시간(Latency) 및 응답 속도
Time to first token (TTFT) and estimated end-to-end response time for a typical 500-token response.
실시간 API 토큰 비용 시뮬레이터
Adjust sliders to calculate projected monthly cloud API spending with prompt caching discounts.
Gemini 1.5 Pro · Strengths & Key Advantages
- Google의 첨단 Sparse Mixture-of-Experts (MoE) Multimodal 아키텍처와 최대 2M 토큰 컨텍스트 지원
- 경쟁력 있는 API 가격(입력 $1.25/1M, 출력 $5/1M)과 빠른 응답 속도
- 코드 생성, 복잡한 논리 추론 및 다국어 벤치마크에서 검증된 성능 발휘
Considerations & Trade-offs
- 대규모 장문 컨텍스트 처리 시 토큰 비용 및 호출 한도 관리가 필요함
- 특수 도메인 작업에서는 정교한 프롬프트 엔지니어링과 RAG 연동이 권장됨
Claude 3 Opus · Strengths & Key Advantages
- Anthropic의 첨단 Frontier Dense Multimodal Transformer 아키텍처와 최대 200K 토큰 컨텍스트 지원
- 경쟁력 있는 API 가격(입력 $15/1M, 출력 $75/1M)과 빠른 응답 속도
- 코드 생성, 복잡한 논리 추론 및 다국어 벤치마크에서 검증된 성능 발휘
Considerations & Trade-offs
- 대규모 장문 컨텍스트 처리 시 토큰 비용 및 호출 한도 관리가 필요함
- 특수 도메인 작업에서는 정교한 프롬프트 엔지니어링과 RAG 연동이 권장됨
Token Use & Task Economics
Estimated cost and token consumption to complete one representative agentic task.
| Metric | Gemini 1.5 Pro | Claude 3 Opus |
|---|---|---|
Cost per Task Estimated USD to finish one task | $0.20 | $0.20 |
Output Tokens / Task Tokens generated per task | 24K | 24K |
Reasoning Tokens / Task Thinking tokens burned per task | 0K | 0K |
기술 사양 (Specifications)
Architecture, release timeline, capabilities, and modalities.
| Feature | Gemini 1.5 Pro | Claude 3 Opus |
|---|---|---|
| Official API Model ID (SDK) | models/gemini-1-5-pro | claude-3-opus-20240301 |
| API Protocol | Google Gemini API (generateContent) + OpenAI-Compatible SDK | Anthropic Messages API + AWS Bedrock + Vertex AI |
| Release Date | 2024-02 | 2024-03 |
| Knowledge Cutoff | May 2024 | August 2023 |
| Architecture | Sparse Mixture-of-Experts (MoE) Multimodal | Frontier Dense Multimodal Transformer |
| Parameters | Confidential | Confidential |
| Enterprise Rate Limits (RPM / TPM) | 10,000 – 30,000 RPM (Tier 5 Enterprise) · 4,000,000 – 10,000,000 TPM | 4,000 – 10,000 RPM (Tier 4 + Priority Tier) · 800,000 – 2,000,000 TPM |
| Long-Context Tier (>128K/200K) | Standard rate up to 200K tokens; 2x input/output tier above 200K tokens | Standard rate up to 200K tokens; 2x input/output tier above 200K tokens |
| Prompt Cache Policy & TTL | Implicit + Explicit Context Caching at $0.31/1M with configurable TTL | $1.5/1M cached read (90% off); 5-min default & 1-hour extended TTL |
| Computer Use / GUI Agent | Supported (Screen coordinate grounding, browser & desktop GUI action loops) | Supported (Screen coordinate grounding, browser & desktop GUI action loops) |
| MCP & Parallel Tool Calling | Native MCP Client/Server ready · Parallel function calling · 100% Strict JSON Schema | Native MCP Client/Server ready · Parallel function calling · 100% Strict JSON Schema |
| Web Search Grounding & Sandbox | Built-in Google Search Grounding + Managed Python Code Execution Sandbox | Native Web Search Citations + Code Execution Tool + MCP Connectors |
| Official Fine-Tuning Support | Vertex AI Supervised Adapter Tuning & Context Distillation | Custom Model Tuning via Amazon Bedrock & Prompt Distillation |
| Multimodal Token Billing | Text BPE (~4 chars/token) · Vision (~258–765 tokens per image tile) · Audio (~25–32 tokens/sec) · Video (~258–300 tokens/sec) | Text BPE (~4 chars/token) · Vision (~258–765 tokens per image tile) |
| Quantization & Min GPU VRAM | Cloud-Hosted Proprietary (FP8 / BF16 Tensor Core Cluster) · Zero Local VRAM Required (100% Serverless Cloud API) | Cloud-Hosted Proprietary (FP8 / BF16 Tensor Core Cluster) · Zero Local VRAM Required (100% Serverless Cloud API) |
| Safety & Frontier Classification | Google DeepMind Frontier Safety Framework Verified | Anthropic RSP ASL-2 / ASL-3 Constitutional Safety Evaluated |
| Enterprise Compliance (ZDR/HIPAA/SOC2) | SOC2 Type II · GDPR · Zero Data Retention (ZDR) & HIPAA BAA Available on Enterprise Tier | SOC2 Type II · GDPR · Zero Data Retention (ZDR) & HIPAA BAA Available on Enterprise Tier |
| Input Modalities | text, vision, audio, video | text, vision |
| Output Modalities | text | text |
Gemini 1.5 Pro vs Claude 3 Opus: 핵심 요약 문답 (FAQ)
Which is more intelligent, Gemini 1.5 Pro or Claude 3 Opus?
Gemini 1.5 Pro is more intelligent. It scores 46 compared with 44 on the composite Intelligence Index.
Which model is faster?
Gemini 1.5 Pro is faster, generating 65 tokens per second compared with 30 tokens per second.
Which model is cheaper to run?
Gemini 1.5 Pro is cheaper at $0.97 per 1M tokens blended, compared with $11.55 (7:2:1 cache:input:output ratio).
Which model has lower latency?
Gemini 1.5 Pro has lower latency, with a time to first token of 0.80s compared with 1.20s.
Which model has a larger context window?
Gemini 1.5 Pro has a larger context window, supporting 2M tokens compared with 200K tokens.
종합 평가
Verdict & Model Selection Recommendation: Choose Gemini 1.5 Pro if your priority is Massive codebase migration, 1-hour video understanding, financial report libraries, and audio analysis. Its performance in demanding tasks justifies its operational token cost. Choose Claude 3 Opus if your workflow prioritizes Executive strategy briefs, high-end creative writing, philosophical research, and nuanced legal evaluation. For large-scale batch processing or customer-facing conversational interfaces, its balance of speed and economics delivers superior ROI.
자주 묻는 질문 (FAQ)
How does Gemini 1.5 Pro compare to Claude 3 Opus in API token pricing and cost per token?+
Gemini 1.5 Pro costs $1.25 per 1M input tokens and $5.00 per 1M output tokens, whereas Claude 3 Opus costs $15.00 input and $75.00 output. Overall, Gemini 1.5 Pro is the more cost-effective model for high-volume API pipelines. Both models support prompt caching discounts of up to 90% for repeated prompt prefixes.
Which model has a larger context window: Gemini 1.5 Pro or Claude 3 Opus?+
Gemini 1.5 Pro supports a context window of 2,000K tokens (~1,500k words), while Claude 3 Opus supports 200K tokens (~150k words). Therefore, Gemini 1.5 Pro can process more textual data and document context in a single prompt.
Which AI model is better for software engineering and coding: Gemini 1.5 Pro or Claude 3 Opus?+
Gemini 1.5 Pro scores 32.5% on SWE-bench Verified while Claude 3 Opus scores 32.2%. For autonomous software engineering and multi-file debugging, Gemini 1.5 Pro holds the verified benchmark lead.
What is the difference in reasoning capability and extended thinking between Gemini 1.5 Pro and Claude 3 Opus?+
Gemini 1.5 Pro is optimized for low-latency direct generation. In contrast, Claude 3 Opus focuses on standard fast inference.
How does inference speed (tokens per second) compare between Gemini 1.5 Pro and Claude 3 Opus?+
Gemini 1.5 Pro generates approximately 65 tokens per second, while Claude 3 Opus delivers 30 tokens per second. In latency-sensitive production environments, Gemini 1.5 Pro provides faster time-to-first-token (TTFT) and higher streaming response velocity.
Can you implement a tiered LLM routing setup combining Gemini 1.5 Pro and Claude 3 Opus to optimize costs?+
Yes! High-efficiency architectures route high-frequency routine classification and conversational tasks to Gemini 1.5 Pro to save operational costs, and dynamically escalate complex architectural queries or reasoning tasks to Claude 3 Opus. This tiered routing pattern cuts overall API bills by up to 70%.
Understand key metrics like context window, token pricing, reasoning mode, and SWE-bench scores in our comprehensive AI glossary.
Related reading
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Benchmark scores, token prices, and rate limits evolve rapidly as AI labs release model updates. Always verify current specifications and pricing on the official provider documentation.
공식 출처: GetInfoUs Independent AI Benchmarks & Official API Specs