Reviews12 Sept 2025• 11 min read

Claude vs GPT-4 vs Gemini: Which LLM for Production AI Agents?

Comprehensive comparison of Claude 3.5 Sonnet, GPT-4o, and Gemini 1.5 Pro for building production AI agents -benchmarks, pricing, capabilities, and recommendations.

MB
Max Beech
Head of Content

TL;DR

  • Claude 3.5 Sonnet: Best for coding, long documents, safety-critical apps ($3/$15 per M tokens)
  • GPT-4o: Best overall, fastest, most ecosystem integrations ($2.50/$10 per M tokens)
  • Gemini 1.5 Pro: Best for extreme context (2M tokens), cheapest ($1.25/$5 per M tokens)

Feature comparison

FeatureClaude 3.5 SonnetGPT-4oGemini 1.5 Pro
Context window200K tokens128K tokens2M tokens
VisionYesYesYes (+ video)
Tool callingExcellentExcellentGood
StreamingYesYesYes
JSON modeYesYesYes
Input price$3.00/M$2.50/M$1.25/M
Output price$15.00/M$10.00/M$5.00/M

Benchmark performance

BenchmarkClaude 3.5GPT-4oGemini 1.5 Pro
MMLU88.3%88.7%85.9%
HumanEval (coding)92.0%90.2%84.1%
Math78.3%76.6%67.7%
GPQA65.0%60.8%50.9%

Winner: Claude for coding, GPT-4o for general tasks, Gemini for long-context.

Claude 3.5 Sonnet

Best for: Coding agents, content analysis, safety-critical applications

Strengths:

  • Superior coding ability (92% HumanEval)
  • Excellent reasoning on complex tasks
  • Strong safety filters and refusal training
  • Good at following complex instructions
  • 200K context window

Weaknesses:

  • Most expensive ($3/$15 vs $2.50/$10 for GPT-4o)
  • Slower than GPT-4o (1.8s vs 1.2s avg)
  • Smaller ecosystem than OpenAI

Use cases:

  • Autonomous coding assistants
  • Legal/medical document analysis
  • Applications requiring strict safety
  • Long-form content generation

Verdict: 4.7/5 - Premium option for quality-critical work.

GPT-4o

Best for: Most production AI agents, general-purpose applications

Strengths:

  • Fastest inference (1.2s avg)
  • Largest ecosystem (LangChain, LlamaIndex, etc.)
  • Excellent tool calling accuracy
  • Strong multimodal (vision + audio)
  • Best documentation and community
  • Competitive pricing ($2.50/$10)

Weaknesses:

  • 128K context (vs 200K Claude, 2M Gemini)
  • Slightly behind Claude on coding tasks
  • Safety filters occasionally over-restrictive

Use cases:

  • Customer service agents
  • Data analysis and extraction
  • Multimodal applications
  • High-volume production systems

Verdict: 4.8/5 - Best all-around choice for most teams.

Gemini 1.5 Pro

Best for: Long-context analysis, video understanding, budget-conscious projects

Strengths:

  • 2M token context (10× competitors)
  • Video understanding (not just images)
  • Cheapest pricing ($1.25/$5)
  • Good multilingual support
  • Native Google Workspace integration

Weaknesses:

  • Lower accuracy than Claude/GPT-4o
  • Tool calling less reliable
  • Smaller developer ecosystem
  • Less documentation

Use cases:

  • Analyzing entire codebases or books
  • Video content analysis
  • Budget-sensitive applications
  • Document processing at scale

Verdict: 4.2/5 - Excellent for specific use cases, not general-purpose leader.

Pricing comparison

Scenario: 10M tokens/month (5M input, 5M output)

ModelMonthly cost
Claude 3.5 Sonnet$90,000
GPT-4o$62,500
Gemini 1.5 Pro$31,250

Gemini is 50% cheaper than GPT-4o, 65% cheaper than Claude.

Use case recommendations

Choose Claude 3.5 Sonnet if:

  • Building coding agents or dev tools
  • Need maximum reasoning quality
  • Safety/compliance critical (healthcare, legal)
  • Budget allows premium pricing

Choose GPT-4o if:

  • Building general-purpose AI agents
  • Speed matters (customer-facing)
  • Want largest ecosystem support
  • Need balance of cost and performance

Choose Gemini 1.5 Pro if:

  • Processing extremely long documents
  • Need video understanding
  • Cost optimization priority
  • Integrating with Google services

Real-world performance

At Athenic, we tested all three for our agent workflows:

Research tasks: GPT-4o 15% faster, Claude 8% more accurate, Gemini 40% cheaper Code generation: Claude 18% better quality, GPT-4o 22% faster, similar cost Data extraction: GPT-4o most reliable, Claude close second, Gemini struggled with complex schemas

Our stack: GPT-4o for orchestrator (speed critical), Claude for developer agent (quality critical), Gemini for document analysis (cost-volume balance).

FAQs

Can I switch models mid-project?

Yes, most frameworks (LangChain, LlamaIndex) support swapping models. Test thoroughly before switching in production.

Which has best function calling?

Claude and GPT-4o roughly tied. Gemini functional but less reliable for complex tool use.

What about data privacy?

All three process data in cloud. For sensitive data: use Azure OpenAI (GPT-4o), Google Vertex AI (Gemini), or self-hosted alternatives.

Which for non-English?

Gemini best for non-English, especially Asian languages. GPT-4o and Claude strong for European languages.

Can I use multiple in one agent?

Yes, route different tasks to different models. Our orchestrator uses GPT-4o, delegates coding to Claude.

Summary

Winner: GPT-4o for most production use cases -best speed/cost/quality balance. Runner-up: Claude 3.5 Sonnet for quality-critical applications. Budget pick: Gemini 1.5 Pro for long-context or cost-sensitive projects.

Recommendation: Start with GPT-4o, consider Claude for coding/analysis agents, use Gemini for document processing.

Internal links:

External references: