LLM Provider Comparison Matrix
LLM Provider Comparison Matrix
Section titled βLLM Provider Comparison MatrixβA practical reference for choosing the right provider and model.
Quick Comparison (December 2024)
Section titled βQuick Comparison (December 2024)β| Provider | Best For | Latency | Price | Context Window |
|---|---|---|---|---|
| OpenAI GPT-4o | General purpose, balanced | Medium | $$ | 128K |
| OpenAI GPT-4o-mini | Cost-sensitive apps | Fast | $ | 128K |
| Claude 3.5 Sonnet | Long documents, coding | Medium | $$ | 200K |
| Claude 3 Haiku | Speed-critical apps | Very Fast | $ | 200K |
| Gemini 1.5 Pro | Multimodal, long context | Medium | $$ | 1M |
| Gemini 1.5 Flash | High-volume apps | Fast | $ | 1M |
Detailed Pricing
Section titled βDetailed Pricingβ| Model | Input ($/1M) | Output ($/1M) | Context | Rate Limits |
|---|---|---|---|---|
| GPT-4 Turbo | $10.00 | $30.00 | 128K | Tier-based |
| GPT-4o | $2.50 | $10.00 | 128K | Tier-based |
| GPT-4o-mini | $0.15 | $0.60 | 128K | Tier-based |
| GPT-3.5 Turbo | $0.50 | $1.50 | 16K | Tier-based |
| o1-preview | $15.00 | $60.00 | 128K | Limited |
| o1-mini | $3.00 | $12.00 | 128K | Limited |
Rate Limit Tiers:
- Tier 1: 500 RPM, 30K TPM
- Tier 2: 5K RPM, 450K TPM
- Tier 3: 5K RPM, 1M TPM
- Tier 4: 10K RPM, 2M TPM
- Tier 5: 10K RPM, 10M TPM
Anthropic
Section titled βAnthropicβ| Model | Input ($/1M) | Output ($/1M) | Context | Rate Limits |
|---|---|---|---|---|
| Claude 3.5 Sonnet | $3.00 | $15.00 | 200K | Tier-based |
| Claude 3 Opus | $15.00 | $75.00 | 200K | Tier-based |
| Claude 3 Haiku | $0.25 | $1.25 | 200K | Tier-based |
Features:
- Prompt caching (90% discount on cached tokens)
- Extended thinking for complex reasoning
- Tool use / function calling
| Model | Input ($/1M) | Output ($/1M) | Context | Rate Limits |
|---|---|---|---|---|
| Gemini 1.5 Pro | $3.50 | $10.50 | 1M | 360 RPM |
| Gemini 1.5 Flash | $0.075 | $0.30 | 1M | 1000 RPM |
| Gemini 1.0 Pro | $0.50 | $1.50 | 32K | 360 RPM |
Features:
- Native multimodal (images, video, audio)
- 1M token context window
- Grounding with Google Search
Capability Matrix
Section titled βCapability MatrixβReasoning & Accuracy
Section titled βReasoning & Accuracyβ| Capability | GPT-4o | Claude 3.5 | Gemini 1.5 Pro |
|---|---|---|---|
| Complex reasoning | ββββ | βββββ | ββββ |
| Math/Logic | ββββ | ββββ | ββββ |
| Code generation | ββββ | βββββ | ββββ |
| Instruction following | βββββ | βββββ | ββββ |
| Factual accuracy | ββββ | ββββ | ββββ |
Features
Section titled βFeaturesβ| Feature | OpenAI | Anthropic | |
|---|---|---|---|
| Streaming | β | β | β |
| Function calling | β | β | β |
| JSON mode | β | β | β |
| Vision | β | β | β |
| Audio | β | β | β |
| Video | β | β | β |
| Fine-tuning | β | β | β |
| Batch API | β | β | β |
| Prompt caching | β | β | β |
Use Case Recommendations
Section titled βUse Case RecommendationsβCost-Optimized Stack
Section titled βCost-Optimized StackβFor applications where cost is the primary concern:
Simple queries: GPT-4o-mini or Gemini Flash - $0.15-0.30 per 1M tokens - Good enough for FAQ, classification, extraction
Complex queries: GPT-4o or Claude Haiku - $2.50-3.00 per 1M tokens - When quality matters more than cost
Reasoning tasks: o1-mini or Claude Sonnet - $3.00-15.00 per 1M tokens - For problems requiring multi-step reasoningLatency-Optimized Stack
Section titled βLatency-Optimized StackβFor applications where speed is critical:
<200ms TTFT: Claude Haiku, Gemini Flash - Fastest models available - Suitable for real-time applications
200-500ms TTFT: GPT-4o-mini, GPT-4o - Good balance of speed and capability - Use for interactive experiences
>500ms acceptable: Claude Opus, o1-preview - Highest capability models - Use for batch/async workloadsLong Context Stack
Section titled βLong Context StackβFor applications with large documents:
<32K tokens: Any model works - Standard context window
32K-200K tokens: Claude 3.x, GPT-4 Turbo - Extended context capability
200K-1M tokens: Gemini 1.5 - Only option for very long context - Consider document summarization insteadProvider-Specific Considerations
Section titled βProvider-Specific ConsiderationsβPros:
- Most widely adopted, best ecosystem
- Consistent quality across models
- Best documentation and tooling
Cons:
- Rate limits can be restrictive
- No extended context beyond 128K
- Pricing creep on popular models
Anthropic
Section titled βAnthropicβPros:
- Best safety/alignment
- 200K context window standard
- Excellent for coding tasks
Cons:
- Smaller model selection
- No fine-tuning available
- Fewer integrations
Pros:
- 1M token context window
- Native multimodal capabilities
- Competitive pricing
Cons:
- Less consistent quality
- Fewer third-party integrations
- Documentation gaps
Decision Framework
Section titled βDecision Frameworkβββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ What's your priority? ββββββββββββββββββββββββ¬ββββββββββββββββββ¬ββββββββββββββββββββββ€β COST β LATENCY β QUALITY ββββββββββββββββββββββββΌββββββββββββββββββΌββββββββββββββββββββββ€β GPT-4o-mini β Claude Haiku β Claude Opus ββ Gemini Flash β Gemini Flash β GPT-4 / o1 ββ Claude Haiku β GPT-4o-mini β Claude 3.5 Sonnet ββββββββββββββββββββββββ΄ββββββββββββββββββ΄ββββββββββββββββββββββ
Need long context (>128K)? β Gemini 1.5 or ClaudeNeed multimodal (video)? β Gemini 1.5Need fine-tuning? β OpenAI or GoogleNeed best safety? β AnthropicCost Estimation Examples
Section titled βCost Estimation ExamplesβCustomer Support Bot
Section titled βCustomer Support Botβ- 10K conversations/day
- 5 turns average
- 500 tokens/turn (with history)
| Model | Monthly Cost |
|---|---|
| GPT-4o-mini | ~$450 |
| GPT-4o | ~$3,750 |
| Claude Haiku | ~$375 |
| Claude Sonnet | ~$4,500 |
Document Analysis
Section titled βDocument Analysisβ- 1K documents/day
- 50K tokens/document average
- 500 token output
| Model | Monthly Cost |
|---|---|
| Gemini Flash | ~$125 |
| Claude Haiku | ~$400 |
| GPT-4o | ~$4,000 |
| Claude Sonnet | ~$4,800 |
Keeping Current
Section titled βKeeping CurrentβPricing and capabilities change frequently. Resources:
Related guides: