Anthropic offers three Claude model tiers: Opus (maximum capability), Sonnet (balanced performance and cost), and Haiku (fastest and most affordable). Choosing the wrong model for a use case costs either money (using Opus where Haiku would do) or quality (using Haiku where Sonnet is required). This Claude model comparison gives enterprise teams the data they need to make that decision precisely.
For the broader API architecture discussion, see the Claude API Enterprise Guide. For a full model cost analysis, see Claude API Pricing Explained.
At-a-Glance: The Three Claude Models
Full Feature Comparison Table
| Feature / Specification | Opus 4.6 | Sonnet 4.6 | Haiku 4.5 |
|---|---|---|---|
| Context & Capacity | |||
| Context Window | 200K tokens | 200K tokens | 200K tokens |
| Max Output Tokens | 8,192 | 8,192 | 8,192 |
| Vision / Image Input | ✓ | ✓ | ✓ |
| PDF / Document Processing | ✓ | ✓ | ✓ |
| Capabilities | |||
| Extended Thinking | ✓ | ✓ | ✗ |
| Tool Use / Function Calling | ✓ | ✓ | ✓ |
| Multi-Tool Parallel Calls | ✓ | ✓ | △ |
| Computer Use (Beta) | ✓ | ✓ | △ |
| Code Generation Quality | Highest | Excellent | Good |
| Complex Reasoning | Highest | Strong | Basic |
| Long-form Writing Quality | Highest | Excellent | Good |
| Multi-step Agent Tasks | Excellent | Excellent | Limited |
| Performance | |||
| Relative Latency (TTFT) | Slow | Medium | Fast |
| Tokens per Second | ~80 | ~150 | ~250+ |
| Streaming Support | ✓ | ✓ | ✓ |
| Pricing (per million tokens) | |||
| Input — Standard | $15 | $3 | $0.80 |
| Output — Standard | $75 | $15 | $4 |
| Input — Prompt Cache Read | $1.50 | $0.30 | $0.08 |
| Input — Prompt Cache Write | $18.75 | $3.75 | $1.00 |
| Batch API (50% discount) | ✓ | ✓ | ✓ |
| Enterprise Features | |||
| SOC 2 Type II | ✓ | ✓ | ✓ |
| No Training on API Data | ✓ | ✓ | ✓ |
| Available on AWS Bedrock | ✓ | ✓ | ✓ |
| Available on Google Vertex | ✓ | ✓ | ✓ |
| Available on Azure | △ | ✓ | ✓ |
✓ = Full support △ = Partial/Beta ✗ = Not available. Verify current availability with Anthropic documentation.
Model Selection by Use Case
The right model depends on three factors: how complex is the task, what throughput do you need, and how sensitive are you to cost. Here's the decision table for common enterprise use cases.
| Use Case | Recommended Model | Why |
|---|---|---|
| Legal contract analysis | Sonnet | Strong reasoning at 5x lower cost than Opus |
| Financial modelling & audit | Opus | Extended thinking for multi-step calculations |
| Customer service chatbot | Haiku | Fast responses, high volume, simple tasks |
| Code review & generation | Sonnet | Excellent code quality, production-scale cost |
| Complex architecture decisions | Opus | Deep reasoning, nuanced trade-off analysis |
| Document summarisation | Haiku | Cost-efficient for high-volume processing |
| Multi-agent orchestration | Sonnet | Orchestrator; Haiku for specialist sub-agents |
| Medical/clinical documentation | Opus | Accuracy over cost in regulated contexts |
| Classification / labelling | Haiku | Simple task, maximum throughput |
| RAG-based Q&A systems | Sonnet | Context synthesis at scale |
| Research & analysis reports | Sonnet | Quality output at reasonable cost |
| Real-time interactive apps | Haiku | Sub-second response for user-facing features |
| Extended thinking tasks | Opus | Highest reasoning depth in thinking mode |
| Batch data processing | Haiku | Cost + Batch API = 10-15x cheaper than Opus |
Cost Modelling: What You Actually Pay at Scale
Model selection decisions at enterprise scale compound quickly. At 10 million input tokens per day, choosing Haiku over Opus saves approximately $142,000 per day. Choosing Sonnet over Opus saves $120,000 per day. If your task quality requirements allow, the cost differential is significant enough to validate rigorous model selection evaluation.
Run your own evaluation: send the same 100 representative inputs to all three models, score the outputs against a quality rubric, then calculate the cost-quality trade-off. For most enterprise tasks, Sonnet's quality/cost ratio is optimal. Opus is justified when quality degradation on complex tasks has downstream business consequences (incorrect legal advice, flawed financial analysis).
Our Claude API integration service includes model selection evaluation as part of architecture engagements. We run your actual workloads against all three models before recommending a production configuration.
Not Sure Which Claude Model Is Right for Your Use Case?
We run model evaluation workloads against your actual tasks. Book a strategy call and we'll build the case before you commit to a production configuration.
Book a Free Strategy Call →Multi-Model Architectures
The most cost-effective enterprise Claude deployments don't use a single model — they use different models for different functions within the same workflow. A common pattern: Sonnet as the orchestrator agent that plans and synthesises, Haiku as the specialist sub-agents that perform classification, extraction, and formatting tasks, with Opus reserved for the specific steps that require its full reasoning capability.
This architecture can reduce API costs by 40–60% compared to running everything through Sonnet, with minimal quality degradation for the tasks delegated to Haiku. See our multi-agent systems guide for the implementation patterns.