Gemini 1.5 Pro vs Claude 3.5 Haiku

Compare Gemini 1.5 Pro and Claude 3.5 Haiku. Find out which one is better for your use case.

Model Comparison

FeatureGemini 1.5 ProClaude 3.5 Haiku
ProviderGoogleAnthropic
Model Typetexttext
Context Window1,000,000 tokens200,000 tokens
Input Cost$3.50 / 1M tokens$0.80 / 1M tokens
Output Cost$7.00 / 1M tokens$4.00 / 1M tokens

Strengths & Best Use Cases

Gemini 1.5 Pro

1. Breakthrough long-context window up to 1,000,000 tokens

  • Can process 1 hour of video, 11 hours of audio, 700k+ words, or 100k+ lines of code in a single prompt.
  • Supports advanced retrieval, reasoning, summarization, and cross-document tasks.
  • Achieves 99% retrieval accuracy on 1M-token Needle-In-A-Haystack tests.

2. Strong multimodal reasoning across video, audio, images, and text

  • Can analyze long videos (e.g., full silent films), track events, infer causality, and identify small details.
  • Handles large complex documents like manuals, transcripts, and books.

3. High-performance reasoning and problem solving

  • Comparable to Gemini 1.0 Ultra across many benchmarks.
  • Excels at code reasoning, multi-step explanations, and large-scale codebase analysis.

4. Advanced code understanding and generation

  • Performs problem-solving on codebases exceeding 100,000 lines.
  • Capable of cross-file reasoning, debugging guidance, API comprehension, and generating structured code improvements.

5. Efficient Mixture-of-Experts (MoE) architecture

  • Activates only relevant expert pathways per input.
  • Enables faster training, lower latency, and more efficient serving.
  • Dramatically improves scalability and inference speed.

6. Exceptional in-context learning capabilities

  • Learns new tasks directly from long prompts without fine-tuning.
  • Demonstrated by learning to translate a low-resource language (Kalamang) from a grammar manual.

7. High-fidelity multimodal understanding

  • Reads, analyzes, and reasons about long PDFs, code repositories, images, and videos together.
  • Enables new classes of applications: legal analysis, scientific review, codebase audits, long-form content generation, etc.

8. Safety and reliability first

  • Undergoes extensive ethics, safety testing, and red-teaming.
  • Improved representational safety and reduced hallucinations compared to previous generations.

9. Available for developers and enterprises

  • Accessible via AI Studio and Vertex AI.
  • Supports future pricing tiers for expanded context windows.
  • Designed for real enterprise-scale workloads.

10. Widely capable mid-size model

  • Positioned between Gemini Pro and Gemini Ultra generations.
  • Well-balanced: reasoning, multimodality, long-context, and speed.

Claude 3.5 Haiku

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

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