OpenAI vs Anthropic vs Google: The Ultimate 2024 Comparison

Choosing the right LLM provider is one of the most important decisions you'll make for your AI application. Get it wrong, and you'll either overpay or sacrifice quality. Get it right, and you'll ship faster while keeping costs under control.

In this comprehensive comparison, we'll break down the three major LLM providers—**OpenAI**, **Anthropic**, and **Google**—across every dimension that matters: cost, performance, quality, latency, and ideal use cases.

Executive Summary

**TL;DR**: Here's the quick take:

| Provider | Best For | Price Tier | Quality Tier | Key Strength |

|----------|----------|------------|--------------|--------------|

| **OpenAI** | General purpose, code generation | $$$ | ⭐⭐⭐⭐⭐ | Ecosystem & reliability |

| **Anthropic** | Long-form content, safety-critical | $$$$ | ⭐⭐⭐⭐⭐ | Context length & coherence |

| **Google** | Cost-conscious, simple tasks | $ | ⭐⭐⭐⭐ | Price & multimodal |

Pricing Breakdown

Let's start with the numbers. Pricing varies dramatically between providers and models.

OpenAI Pricing (as of Jan 2024)

| Model | Input ($/1M tokens) | Output ($/1M tokens) | Context Window |

|-------|---------------------|----------------------|----------------|

| **GPT-4 Turbo** | $10.00 | $30.00 | 128K tokens |

| **GPT-4** | $30.00 | $60.00 | 8K tokens |

| **GPT-3.5 Turbo** | $0.50 | $1.50 | 16K tokens |

**Key insights**:

Anthropic Pricing (Claude 3 family)

| Model | Input ($/1M tokens) | Output ($/1M tokens) | Context Window |

|-------|---------------------|----------------------|----------------|

| **Claude 3 Opus** | $15.00 | $75.00 | 200K tokens |

| **Claude 3 Sonnet** | $3.00 | $15.00 | 200K tokens |

| **Claude 3 Haiku** | $0.25 | $1.25 | 200K tokens |

**Key insights**:

Google Pricing (Gemini family)

| Model | Input ($/1M tokens) | Output ($/1M tokens) | Context Window |

|-------|---------------------|----------------------|----------------|

| **Gemini Pro** | $0.50 | $1.50 | 32K tokens |

**Key insights**:

Cost Comparison: Real-World Example

Let's calculate the cost for a typical use case: **customer support chatbot** processing 100,000 conversations per month.

**Assumptions**:

# Monthly costs for 100K conversations

# OpenAI GPT-4 Turbo
gpt4_cost = (100_000 * 500 * 10 / 1_000_000) + (100_000 * 300 * 30 / 1_000_000)
print(f"GPT-4 Turbo: ${gpt4_cost:.2f}")  # $1,400.00

# OpenAI GPT-3.5 Turbo
gpt35_cost = (100_000 * 500 * 0.5 / 1_000_000) + (100_000 * 300 * 1.5 / 1_000_000)
print(f"GPT-3.5 Turbo: ${gpt35_cost:.2f}")  # $70.00

# Anthropic Claude 3 Opus
opus_cost = (100_000 * 500 * 15 / 1_000_000) + (100_000 * 300 * 75 / 1_000_000)
print(f"Claude 3 Opus: ${opus_cost:.2f}")  # $3,000.00

# Anthropic Claude 3 Sonnet
sonnet_cost = (100_000 * 500 * 3 / 1_000_000) + (100_000 * 300 * 15 / 1_000_000)
print(f"Claude 3 Sonnet: ${sonnet_cost:.2f}")  # $600.00

# Google Gemini Pro
gemini_cost = (100_000 * 500 * 0.5 / 1_000_000) + (100_000 * 300 * 1.5 / 1_000_000)
print(f"Gemini Pro: ${gemini_cost:.2f}")  # $70.00

**Results**:

Performance Benchmarks

MMLU (Massive Multitask Language Understanding)

Measures general knowledge and reasoning across 57 subjects.

| Model | MMLU Score | Percentile |

|-------|------------|------------|

| Claude 3 Opus | **86.8%** | 96th |

| GPT-4 Turbo | 86.4% | 95th |

| Claude 3 Sonnet | 79.0% | 89th |

| Gemini Pro 1.5 | 81.9% | 92nd |

| GPT-3.5 Turbo | 70.0% | 70th |

**Winner: Claude 3 Opus** (barely edges out GPT-4)

HumanEval (Code Generation)

Measures ability to generate correct Python code from docstrings.

| Model | HumanEval Score | Pass Rate |

|-------|-----------------|-----------|

| **GPT-4 Turbo** | **90.2%** | Best |

| Claude 3 Opus | 84.9% | Excellent |

| GPT-3.5 Turbo | 76.8% | Good |

| Gemini Pro | 67.7% | Fair |

**Winner: GPT-4 Turbo** (superior for code generation)

Use Case Recommendations

Based on all the data, here's our recommendation framework:

Use Case Matrix

| Use Case | 1st Choice | 2nd Choice | 3rd Choice | Rationale |

|----------|------------|------------|------------|-----------|

| **Code Generation** | GPT-4 Turbo | Claude 3 Opus | GPT-3.5 | GPT-4 has best HumanEval scores |

| **Long-Form Writing** | Claude 3 Opus | GPT-4 Turbo | Claude 3 Sonnet | 200K context + coherence |

| **Summarization** | Claude 3 Sonnet | Claude 3 Opus | GPT-4 | Best quality/cost ratio |

| **Simple Q&A** | Gemini Pro | GPT-3.5 | Claude Haiku | Cheapest, fast enough |

| **Classification** | GPT-3.5 | Claude Haiku | Gemini Pro | Simple task, cheap models work |

Decision Tree

START: What's your use case?
│
├─ Code generation?
│  └─ YES → GPT-4 Turbo
│
├─ Long documents (>50K tokens)?
│  └─ YES → Claude 3 Opus (200K context)
│
├─ Budget-constrained?
│  └─ YES → Gemini Pro or GPT-3.5
│
└─ General purpose?
   └─ GPT-4 Turbo (best balance)

Key Takeaways

Recommendations

**For most teams, we recommend**:

**For budget-conscious teams**: