Claude Sonnet 5.5 and Claude Opus 5.5 share a 1 million token context window, 128,000-token output limit and Anthropic’s current agent stack. Their practical difference is positioning: Sonnet is the faster, lower-priced default for repeated coding and tool workflows, while Opus is the premium option for the hardest autonomous and professional tasks.
Neither is universally better. The right model is the one that completes your workload reliably at the lowest total cost.
Quick verdict
Choose Sonnet 5.5 for most production coding agents, high-volume API workflows and interactive work where latency and price matter. Choose Opus 5.5 when your own evaluations show that its stronger reasoning reduces failures, retries or expert review enough to justify twice the input and output price.
Do not use a public benchmark as the only routing rule. Build workload-specific quality gates through the AI Testing & Evaluation hub.
Sonnet 5.5 vs Opus 5.5 specs
| Feature | Sonnet 5.5 | Opus 5.5 |
|---|---|---|
| Model ID | claude-sonnet-5-5 | claude-opus-5-5 |
| Standard input | $2/M | $4/M |
| Cache read | $0.20/M | $0.20/M |
| 5-minute cache write | $2.50/M | $5/M |
| Standard output | $10/M | $20/M |
| Context window | 1,000,000 | 1,000,000 |
| Maximum output | 128,000 | 128,000 |
| Thinking | Adaptive | Adaptive, always on |
| Default effort | High | Medium |
| Speed positioning | Fast | Moderate |
| Best starting point | Repeated production workloads | Highest-difficulty workloads |
The equal cache-read rate is notable. An Opus workload with a strong cache-hit rate can narrow the input-cost gap, but cache writes and uncached input still cost twice as much.
Pricing and completed-task cost
At standard rates, Sonnet costs half as much for uncached input, cache writes and output. A request using 1 million input tokens and 100,000 output tokens would cost about $3 on Sonnet and $6 on Opus before cache effects and tools.
That arithmetic does not settle the decision. If Opus solves a difficult task in one attempt while Sonnet requires retries and extensive review, Opus can be cheaper per accepted result. If both reach the same result, Sonnet normally has the cost advantage.
Track:
- accepted output per run
- retries and failed tool calls
- input and output tokens
- cache-write and cache-read ratios
- latency to a usable answer
- human review and correction time
The real AI coding cost guide explains why token price alone can misrepresent economics.
Reasoning and effort controls
Sonnet 5.5 uses adaptive thinking and defaults to high effort. It can use between_tools behavior at high effort or below. Opus 5.5 keeps adaptive thinking on and defaults to medium effort.
The different defaults mean a naive test can compare unlike configurations. Record effort settings, tool access and maximum latency in every evaluation. Higher labels do not guarantee a better result, and greater reasoning can add tokens and delay.
Both models require care with preserved thinking and message history. Integrations should not edit thinking blocks or assume they can switch models inside an existing preserved-thinking conversation. Use separate conversations when a router changes model families unless the documented protocol supports the transition.
Coding and agent workloads
Sonnet 5.5 is the natural first candidate for repository maintenance, test generation, code review and tool-driven development at scale. Its lower price and fast positioning make it easier to run repeated checks.
Opus 5.5 is worth evaluating for ambiguous architecture work, long-horizon planning, difficult debugging and tasks where one incorrect decision creates expensive downstream rework. It may also be useful as an escalation model after Sonnet fails a confidence or verification gate.
A robust router should not ask the cheaper model to judge itself. Use external tests, schemas and deterministic conditions to decide whether escalation is necessary. The coding-agent testing guide covers sandboxing and review gates.
Vendor-reported benchmarks
Anthropic’s launch materials show mixed workload leadership rather than a universal hierarchy. The published Terminal-Bench 4 table reports 70.6% for Sonnet 5.5 and 66.4% for Opus 5.5 at the stated settings. The same materials show Opus ahead on some coding evaluations, while a Cursor benchmark lists 55.5 for Sonnet and 57.8 for Opus.
These are first-party figures using different harnesses and settings. They support a workload-dependent conclusion. They do not justify merging scores or saying one model always wins.
Reproduce the tasks that matter to you. Include repository size, required tools, permissions, flaky tests and human acceptance criteria.
Context, caching and long-running agents
Both models support a 1M context window and 128K output. Large context is helpful for repositories and document collections, but sending everything on every turn is rarely efficient.
Use retrieval to select relevant files, cache stable system instructions and reference material, and compact tool logs. Cache reads cost $0.20 per million tokens for both models. Sonnet’s 5-minute cache writes cost $2.50, while Opus costs $5.
Long-running agents need state management beyond context size. Store checkpoints, approvals and tool results so a transient failure does not require replaying an entire session. The AI Application Architecture hub covers reliable workflow design.
Availability and integrations
Both model generations are available through Anthropic and major cloud integrations, but identifiers, regions and feature timing can differ. Verify the exact provider record rather than copying the direct Claude API model ID.
GitHub Copilot availability is product-specific. A model offered in Copilot does not automatically appear under an Anthropic API account, and Copilot usage billing does not equal one raw API request.
For the complete current Sonnet reference, read the Claude Sonnet 5.5 guide. For Opus migration and pricing, use the Claude Opus 5.5 guide.
Decision framework
Start with Sonnet 5.5 when:
- the workflow runs frequently
- interactive latency matters
- tests can verify quality
- failures are inexpensive to retry
- the task is coding, extraction or ordinary tool orchestration
Evaluate Opus 5.5 when:
- mistakes have a high review or business cost
- tasks are long-horizon and ambiguous
- Sonnet repeatedly misses architecture or planning constraints
- a premium pass can replace several failed attempts
- your evidence shows a higher acceptance rate
A practical architecture can use Sonnet by default and Opus for selected escalation. Put explicit limits around escalation so routing does not become an uncontrolled cost multiplier.
My take
Sonnet 5.5 is the better default, not the automatic winner. Its list-price advantage is clear and its vendor-reported performance makes it credible for serious agent work. Opus 5.5 earns its place when difficult tasks produce measurably better accepted outcomes. Use real acceptance criteria rather than prestige or a single leaderboard.
Specifications and vendor benchmark context were checked against Anthropic’s Sonnet 5.5 model overview and Sonnet 5.5 announcement.
Frequently asked questions
Is Sonnet 5.5 cheaper than Opus 5.5?
Yes. Sonnet costs $2/$10 per million input/output tokens, while Opus costs $4/$20. Cache reads are $0.20 for both.
Do both models have 1M context?
Yes. Both document a 1 million token context window and up to 128,000 output tokens.
Which is faster?
Anthropic positions Sonnet as fast and Opus as moderate. Actual latency depends on effort, output length, provider and workload.
Which is better for coding agents?
Start with Sonnet for most repeated workflows. Test Opus on difficult tasks where higher acceptance can offset its price.
Can an agent switch between the models mid-conversation?
Do not assume so when preserved thinking is present. Use provider documentation and test message-history compatibility before routing within a conversation.