Anthropic's Claude family now consists of three distinct models, each optimized for different tasks and budgets: Opus 4.7 for complex reasoning, Sonnet 4.6 as the production default, and Haiku 4.5 for high-volume, cost-sensitive work. The naming convention, established in March 2024 with the Claude 3 release, reflects a deliberate engineering trade-off between capability, speed, and cost per token.

What Are the Key Differences Between Claude's Three Models?

Each Claude tier serves a distinct purpose in the model family. Opus 4.7, released in April 2026, is the flagship model designed for the hardest reasoning tasks and longest-horizon agentic work, where decisions compound across multiple steps. Sonnet 4.6, released in February 2026, occupies the balanced middle ground, offering enough capability for most production workloads while remaining fast and cost-effective to deploy at scale. Haiku 4.5, released in October 2025, prioritizes speed and affordability, making it ideal for high-volume tasks where latency matters more than raw reasoning power.

The pricing structure reflects these trade-offs. Opus 4.7 costs significantly more per token than Sonnet 4.6, which in turn costs roughly three times more than Haiku 4.5 on both input and output. However, all three models maintain a consistent 5-to-1 output-to-input price ratio, making budget calculations straightforward.

Context window capacity also varies across the tiers. Opus 4.7 and Sonnet 4.6 both support a 1-million-token context window, allowing them to process roughly 750,000 words at once. Haiku 4.5, by contrast, offers a 200,000-token context window, which is still substantial but limits its ability to handle extremely long documents or maintain extended agentic chains.

How Should You Choose Between Opus, Sonnet, and Haiku?

• Use Opus 4.7 when: You're tackling deep, multi-file refactors where early decisions cascade through dozens of steps, need frontier-grade reasoning for proof-style problems or novel algorithm design, or have hit a quality ceiling on Sonnet that prompt engineering cannot fix. Opus 4.7 also introduced sharper vision capabilities and a self-verification step that improves reliability on long tool-use chains.
• Use Sonnet 4.6 when: You're doing general-purpose coding, writing features, refactoring single files, debugging, or building analysis and retrieval-augmented generation (RAG) pipelines. Sonnet is the recommended default for almost every production workload and remains genuinely strong for the vast majority of real-world coding tasks.
• Use Haiku 4.5 when: You need to process high-volume tasks at low latency, such as classification, routing, or running sub-agents. Despite its smaller size and lower cost, Haiku is a genuinely capable model, not a toy, and is roughly 5 times cheaper than Opus and 3 times cheaper than Sonnet on both input and output.

The performance gap between Opus and Sonnet has widened with the latest releases. Opus 4.7 reopened a meaningful gap on SWE-bench Verified, a benchmark measuring real-world coding ability on actual GitHub bug reports and pull requests. Sonnet 4.6 scores approximately 80% on this benchmark, meaning it produces working fixes for roughly 80% of real open-source issues tested. Opus 4.7 scores higher, making the escalation decision clearer when Sonnet falls short.

"Sonnet 4.6 is the default. Almost every production workload should start here. Opus 4.7 is for the hard problems where you've measured Sonnet falling short. Haiku 4.5 is for the simple problems at volume, and it's a real model, not a toy," explained Jano Barnard, R&D Engineer at Cloudvisor.

Jano Barnard, R&D Engineer at Cloudvisor

What Hidden Costs Should You Know About?

Beyond per-token pricing, there are several cost levers that developers often overlook. Prompt caching, a feature available across all three tiers, allows you to cache frequently repeated input tokens and pay a reduced rate for cached tokens on subsequent requests. This can dramatically lower costs for workloads that reuse the same context repeatedly, such as analyzing the same codebase multiple times or running agents over consistent system prompts.

Model string pinning is another critical practice. Rather than relying on floating aliases like "claude-opus-latest," developers should pin specific model versions such as "claude-opus-4-7" to ensure consistent behavior and pricing across their applications. This prevents unexpected performance or cost changes when Anthropic releases new versions.

If you're consuming Claude through Amazon Bedrock or Google Vertex AI instead of the Anthropic API directly, the per-token rates remain the same, but the billing lands on your AWS or GCP invoice. This can be advantageous if you already have committed spend or data-residency requirements on those platforms. Alternatively, if you're using Claude through claude.ai or Claude Code on a subscription plan, you pay a flat monthly fee rather than per-token rates.

Is There a Model Beyond Opus?

In April 2026, Anthropic unveiled Claude Mythos Preview, a frontier model sitting above the Opus tier that demonstrates striking capability at cybersecurity tasks. However, Mythos is only available as a gated research preview under Project Glasswing, with access limited to a small set of vetted organizations conducting defensive security work. Because of its restricted availability, it is not a practical choice for most day-to-day workloads.

For the vast majority of developers and organizations, the choice remains among Opus, Sonnet, and Haiku. The key is matching the model's capabilities and cost to your specific task. Starting with Sonnet as the default and escalating to Opus only when measured performance gaps justify the higher cost remains the most practical approach for building AI-powered applications at scale.