Claude Model Comparison and Selection Guide
Claude is available in multiple model tiers with different capability, cost, and latency profiles. As of July 2026, Anthropic’s model overview compares Claude Fable 5, Claude Opus 4.8, Claude Sonnet 5, and Claude Haiku 4.5 as the main current models.[1]
What Is the Claude Model Family?
The Claude model family is Anthropic’s lineup of large language models (LLMs). Tiers such as Fable, Opus, Sonnet, and Haiku represent different points on the intelligence-speed-cost tradeoff. Mythos is offered separately through limited availability in Project Glasswing, so treat it separately from generally available model selection.[1]
graph TD
A[Claude Model Family] --> B[Claude Opus]
A --> C[Claude Sonnet]
A --> D[Claude Haiku]
A --> E[Claude Fable]
B --> B1[Highest Intelligence]
B --> B2[Higher Cost, Lower Speed]
B --> B3[Research & Complex Tasks]
C --> C1[Balanced]
C --> C2[Mid Cost, Mid Speed]
C --> C3[Recommended for Production]
D --> D1[Fast & Lightweight]
D --> D2[Low Cost, Fastest]
D --> D3[High-Frequency & Real-Time]
E --> E1[Highest Capability]
E --> E2[Long-Running Agents]
E --> E3[1M Context]For Claude 4.6 and later, a dateless model ID such as claude-sonnet-5 is still a pinned snapshot, not an evergreen pointer. In production, manage model IDs and upgrade decisions explicitly.[1]
Model Comparison Table
| Item | Claude Fable | Claude Opus | Claude Sonnet | Claude Haiku |
|---|---|---|---|---|
| Latest model ID | claude-fable-5 | claude-opus-4-8 | claude-sonnet-5 | claude-haiku-4-5 |
| Positioning | Highest capability for long-running agents | Complex agentic coding and enterprise work | Best speed-intelligence balance | Fastest lightweight model |
| Context window | 1M tokens | 1M tokens | 1M tokens | 200K tokens |
| Max output | 128K tokens | 128K tokens | 128K tokens | 64K tokens |
| Relative cost | Highest | High | Medium | Low |
| Best at | Long-running agents and advanced reasoning | Complex coding and enterprise work | Code generation, writing, analysis | Classification, summarization, fast responses |
| Recommended use cases | Highest-capability long-running work | Complex agents and design decisions | General production | High-frequency calls, real-time |
Note: Model IDs, pricing, context windows, and output limits change over time. Confirm current values in Anthropic’s official Models overview and Pricing pages.[1][2]
Detailed Model Characteristics
Claude Fable — Highest-Capability Long-Running Agent Model
Claude Fable 5 is positioned by Anthropic as its most capable widely released model. It has a 1M token context window, 128K token max output, and always-on adaptive thinking, making it suitable for long-running agents and advanced knowledge work.[1]
Appropriate use cases:
- Long-running, multi-step agent tasks
- Deep analysis across large document or code contexts
- Work where output quality matters more than cost
Claude Opus — Complex Coding and Enterprise Work
Claude Opus is a high-capability model for complex agentic coding and enterprise work. As of July 2026, Claude Opus 4.8 is the current comparison point.[1]
Key characteristics:
- Handles complex multi-step reasoning tasks
- Handles long context up to 1M tokens
- Produces higher-quality judgments when used as an autonomous agent
- Suited for tasks where high-quality output is required, such as research paper summarization, peer review, and code refactoring
Appropriate use cases:
- Long-running AI agents that call multiple tools and make decisions autonomously
- Deep analysis of specialized documents such as scientific papers, legal texts, or technical specifications
- High-complexity coding tasks including architecture design and complex algorithm implementation
- Tasks that extract insights from large volumes of data where human review is impractical
Claude Sonnet — Balanced, Recommended for Production
Claude Sonnet offers the best balance of intelligence, speed, and cost. For most production use cases, Sonnet is the first choice.
Key characteristics:
- Delivers high-quality output while maintaining significantly lower cost and higher speed compared to Opus
- Handles a wide range of tasks including code generation, document writing, data analysis, and conversational responses
- Response speed suited for large-scale API integrations
- Used daily by many users as the default model on Claude.com
Appropriate use cases:
- General API integrations (chatbots, code assistants, document generation)
- Continuous task processing in production environments
- Building AI tools for teams and organizations
- Code generation and review at medium-to-high complexity
Claude Haiku — Fast, Lightweight, Cost-First
Claude Haiku is the fastest and lowest-cost model in the Claude family. It is the right choice when latency is the primary concern or when large volumes of requests need to be processed at minimal cost.
Key characteristics:
- Lowest latency (compatible with interfaces requiring real-time responses)
- Lowest cost (enables cost optimization for high-frequency calls and large batch processing)
- Stable quality for routine classification, summarization, and data extraction tasks
- Improved streaming response experience
Appropriate use cases:
- Real-time chat UIs (autocomplete during typing, interfaces requiring immediate responses)
- Bulk document classification and labeling (batch processing)
- Short-form summarization and conversion to structured data
- First stage of preprocessing and filtering pipelines
Use-Case-Based Selection Guide
| Use Case | Recommended Model | Reason |
|---|---|---|
| Chatbot (general purpose) | Sonnet | Best balance of response quality and cost |
| Highest-capability long-running agents | Fable | Takes advantage of 1M context and highest capability |
| Code generation (complex architecture) | Opus / Fable | High reasoning capability required |
| Code completion / minor edits | Sonnet / Haiku | Speed and cost are priorities |
| Document summarization (short to medium) | Haiku | Sufficient quality at low cost |
| Deep analysis of long or specialized documents | Opus | Accuracy and context retention are priorities |
| Autonomous agents (multi-step) | Opus / Fable | Complex decision-making required |
| Large batch processing | Haiku | Cost minimization is the top priority |
| Real-time API (immediate response) | Haiku | Latency is the top priority |
| General production (default) | Sonnet | Best overall balance of cost, quality, and speed |
Cost Optimization Tips
Model Routing (Choosing Models by Task)
Model routing is a design pattern that automatically selects different models based on the complexity of each task. Rather than sending all requests to a single model, routing selects the most appropriate model for each task, optimizing quality and cost simultaneously.
An effective implementation is to use lightweight Haiku first to classify each request, then forward only requests judged as complex to Opus.
graph LR
REQ[User Request] --> ROUTER[Router]
ROUTER --> |Simple task| HAIKU[Haiku]
ROUTER --> |Moderate task| SONNET[Sonnet]
ROUTER --> |Complex task| OPUS[Opus]
ROUTER --> |Highest capability needed| FABLE[Fable]
HAIKU --> RES[Response]
SONNET --> RES
OPUS --> RES
FABLE --> RESUsing Prompt Caching
Prompt caching reduces the token processing cost by up to 90% when the same prompt prefix is sent repeatedly. It is particularly effective for use cases that include long system prompts or repeatedly referenced documents. See Claude API and Prompt Caching for details.
Haiku Preprocessing → Opus Final Judgment Pattern
A cost-efficient implementation pattern combines Haiku and Opus in a two-stage architecture.
- Preprocessing with Haiku: Summarize and filter large volumes of documents with Haiku, extracting only the most relevant information.
- Final judgment with Opus: Pass the information extracted by Haiku to Opus to generate a high-quality final answer.
This pattern leverages Opus’s high reasoning capability while reducing the number of input tokens and lowering overall cost.
Summary
- Claude Fable is the right choice for long-running agent work and advanced reasoning that needs the highest available capability.
- Claude Opus is well suited to complex coding, enterprise work, and demanding agent tasks.
- Claude Sonnet is the first choice for most production use cases, offering the best overall balance.
- Claude Haiku is the right choice for high-frequency or large-batch processing where latency and cost are the top priorities.
- Claude Fable 5, Claude Opus 4.8, and Claude Sonnet 5 have 1M token context windows; Claude Haiku 4.5 has a 200K token context window.
- Combining model routing and prompt caching can further optimize costs.
FAQ
Q: How should I choose between Claude Fable and Claude Opus?
Consider Fable for the highest-capability long-running agent work or very large context tasks. Consider Opus for complex coding and enterprise work where high-quality reasoning is needed. For simple Q&A or short summarization, higher-capability models are usually poor cost choices.
Q: What do the version numbers in a model ID (for example, sonnet-4-6) represent?
Version numbers indicate the model’s generation and improvement iteration. Higher numbers represent a newer generation with improved performance within the same tier. In production environments, specifying a fixed version ID prevents unexpected behavior changes.
Q: Is there a quality difference between Opus and Haiku for the same task?
The difference varies by task. For simple classification or routine summarization, the gap is small and Haiku delivers sufficient quality. For complex reasoning, multi-step logic, or specialized analysis, Opus shows a clear advantage.
Q: What does a context window mean?
The context window is the maximum amount of text a model can process in a single request. Claude Fable 5, Claude Opus 4.8, and Claude Sonnet 5 support 1M tokens; Claude Haiku 4.5 supports 200K tokens.[1]
This page’s model IDs, context windows, output limits, and pricing-related statements are grounded in Anthropic’s Models overview and Pricing pages.[1][2]
References
- Anthropic, Models overview
- Anthropic, Pricing
For the latest releases and updates, check the official website and official documentation.