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LLM ComparisonGemini 3 ProClaude 3.5 Haiku

Gemini 3 Pro vs Claude 3.5 Haiku

Compare Gemini 3 Pro and Claude 3.5 Haiku. Build AI products powered by either model on Appaca.

Model Comparison

FeatureGemini 3 ProClaude 3.5 Haiku
ProviderGoogleAnthropic
Model Typetexttext
Context Window1,000,000 tokens200,000 tokens
Input Cost
$4.00/ 1M tokens
$0.80/ 1M tokens
Output Cost
$18.00/ 1M tokens
$4.00/ 1M tokens

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Strengths & Best Use Cases

Gemini 3 Pro

Google

1. State-of-the-art reasoning

  • Top performance across academic reasoning, scientific knowledge, math, and complex problem-solving.
  • Excels at long-horizon, multi-step workflows and deep logical interpretation.

2. World-leading multimodal capabilities

  • Natively understands text, images, videos, audio, and code.
  • Ranked highest on benchmarks like MMMU-Pro, Video-MMMU, ScreenSpot-Pro.

3. Exceptional coding + agentic workflows

  • Strong in competitive coding and real-world agentic tasks (SWE-Bench Verified, Terminal-Bench, LiveCodeBench).
  • Improved tool calling, planning, and execution for autonomous or semi-autonomous agents.

4. Powerful for long-context tasks

  • Effective at 128K-1M context windows with high retrieval accuracy.
  • Ideal for document-heavy workflows, research, analysis, multi-file coding, and multi-document reasoning.

5. Strong information synthesis and interpretation

  • Outperforms peers in chart reasoning, OCR, structured extraction, and screen understanding.
  • Excellent at combining multimodal inputs into coherent, concise answers.

6. High reliability for enterprise tasks

  • Benchmarks show superior factuality, grounding, and parametric knowledge.
  • Strong multilingual accuracy and global commonsense performance.

7. Optimized for production agents

  • Designed for complex multi-step planning, simultaneous task execution, and improved consistency.
  • Works across coding, research, creative workflows, UI generation, and data-heavy applications.

Claude 3.5 Haiku

Anthropic

1. Intelligence & Benchmark Performance

  • Matches Claude 3 Opus (previous largest model) on many intelligence tasks.
  • Surpasses Claude 3 Opus on multiple evaluations despite being a smaller, faster model.
  • Major improvements across every skill category vs previous Haiku.

2. Coding Strength

  • Scores 40.6% on SWE-bench Verified, outperforming:

    • Claude 3.5 Sonnet (original version)
    • GPT-4o
    • Many agent-driven systems
  • Excellent for engineering assistants, agent coding tasks, and bug fixing.

3. Speed & Latency

  • Same speed class as Claude 3 Haiku (ultra-fast).
  • Ideal for real-time interactions, high request volumes, and UI responsiveness.

4. Tool Use & Instruction Following

  • Better at following instructions than previous Haiku.
  • Stronger at tool use accuracy, making it reliable for agents and workflows.

5. Best Use Cases

  • High-volume, low-latency tasks
  • User-facing products
  • Sub-agent tasks in larger workflows
  • Processing large structured datasets (pricing, inventory, purchase history)
  • Rapid content or code generation where speed matters