Model Comparison
Compare AI models side-by-side to find the best fit for your use case.
Elyxir's comparison tool helps you evaluate models side-by-side, comparing capabilities, pricing, and performance.
Comparing Models
Quick Comparison
- Navigate to the Model Hub
- Hover over a model card
- Click Compare
- Select up to 4 models to compare
- View the comparison table
Comparison Table
The comparison shows:
| Attribute | Description |
|---|---|
| Provider | Model creator |
| Context Window | Maximum input tokens |
| Input Price | Cost per 1K input tokens |
| Output Price | Cost per 1K output tokens |
| Speed | Response latency |
| Capabilities | Chat, code, vision, etc. |
Key Comparisons
GPT-4o vs Claude 3.5 Sonnet
| Attribute | GPT-4o | Claude 3.5 Sonnet |
|---|---|---|
| Provider | OpenAI | Anthropic |
| Context | 128K | 200K |
| Input Price | $5/1M | $3/1M |
| Output Price | $15/1M | $15/1M |
| Vision | Yes | Yes |
| Best For | General, vision | Coding, analysis |
Choose GPT-4o for: Multimodal tasks, fast responses, broad capabilities Choose Claude 3.5 for: Code generation, long documents, detailed analysis
GPT-4o-mini vs Claude 3 Haiku
| Attribute | GPT-4o-mini | Claude 3 Haiku |
|---|---|---|
| Provider | OpenAI | Anthropic |
| Context | 128K | 200K |
| Input Price | $0.15/1M | $0.25/1M |
| Output Price | $0.60/1M | $1.25/1M |
| Speed | Very fast | Very fast |
| Best For | Simple tasks | Quick queries |
Choose GPT-4o-mini for: Cost-sensitive applications, high volume Choose Claude 3 Haiku for: Longer context needs, balanced capability
Llama 3.2 vs GPT-4o-mini
| Attribute | Llama 3.2 90B | GPT-4o-mini |
|---|---|---|
| Provider | Meta | OpenAI |
| Context | 128K | 128K |
| Open Source | Yes | No |
| Price | Varies | $0.15/1M |
| Best For | Self-hosting | Simplicity |
Choose Llama for: Self-hosting, no API costs, customization Choose GPT-4o-mini for: Ease of use, reliability, support
Comparison Criteria
Quality
Evaluate based on:
- Response accuracy
- Instruction following
- Reasoning depth
- Output formatting
Cost
Calculate total cost:
Total Cost = (Input Tokens × Input Price) + (Output Tokens × Output Price)
Speed
Consider for your use case:
- Streaming latency: Time to first token
- Total time: Full response completion
- Throughput: Tokens per second
Context Window
Larger context allows:
- Longer documents
- More conversation history
- Complex multi-part prompts
Benchmark Scores
Common benchmarks:
| Benchmark | Measures |
|---|---|
| MMLU | General knowledge |
| HumanEval | Code generation |
| GSM8K | Math reasoning |
| HellaSwag | Common sense |
Benchmark scores don't always reflect real-world performance. Test models with your specific use cases.
Making a Decision
Decision Framework
- Define requirements: What capabilities do you need?
- Set budget: What's your cost ceiling?
- Test candidates: Try top 2-3 models
- Measure: Evaluate on real tasks
- Choose: Select based on results
Common Scenarios
High-volume chat application → GPT-4o-mini or Claude 3 Haiku
Code generation tool → Claude 3.5 Sonnet
Research assistant with web search → Perplexity Sonar
Document analysis (long documents) → Claude 3.5 Sonnet or Gemini Pro
Real-time customer support → GPT-4o-mini (fast, affordable)
Related
- Model Hub Overview - Hub introduction
- Discovery - Finding models
- Providers - Provider details