TL;DR
Claude Opus 5.5 and Claude Sonnet 5.5 offer 1M context and 128K standard maximum output, with text-and-image input and a June 2026 knowledge cutoff. Opus targets complex, open-ended work; Sonnet targets faster execution on scoped everyday tasks.
At Anthropic's standard API rates, Sonnet 5.5 costs $2/M input and $10/M output, exactly half Opus 5.5's $4/M input and $20/M output. Several published scores are close, but the ranking varies by benchmark. Opus scores higher on CursorBench, while Sonnet scores higher on Terminal-Bench. These results use different effort settings and should not be treated as a controlled head-to-head test.
Choose the model that meets your quality and latency requirements at the lowest total task cost. Teams should compare cost per accepted task, latency, tool-call behavior, retries, and the amount of judgment required before deciding where Opus earns its premium.
Key Takeaways
- Price: Sonnet 5.5 is half the standard input/output price of Opus 5.5.
- Specs: Both support a 1M-token context window and up to 128K standard output.
- Coding: Opus leads FrontierCode and CursorBench, while Sonnet posts the higher published Terminal-Bench 4.0 result.
- Knowledge work: Opus retains a small advantage on GDPval-AA and AA-Briefcase.
- Deployment: Test faster Sonnet for scoped execution and Opus for complex escalation; validate both against quality, latency, and cost targets.
Claude Opus 5.5 vs Sonnet 5.5 at a Glance
| Decision factor | Claude Opus 5.5 | Claude Sonnet 5.5 |
|---|---|---|
| Context / max standard output | 1M / 128K | 1M / 128K |
| Input / output modalities | Text + image -> text | Text + image -> text |
| Reasoning | Adaptive thinking, always on | Adaptive thinking |
| Default Claude Platform effort | Medium | High |
| Official input / output price | $4 / $20 per 1M | $2 / $10 per 1M |
| Cache read | $0.20 / 1M | $0.10 / 1M |
| Comparative latency | Moderate | Fast |
| Coding highlight | FrontierCode 54.4%; CursorBench 57.8% | Terminal-Bench 70.6%; CursorBench 55.5% |
| Knowledge-work highlight | GDPval-AA 1846 | GDPval-AA 1844 |
| Primary fit | Complex, ambiguous, long-running work | Fast, scoped, repeatable production work |
Claude Opus 5.5
Claude Opus 5.5 was released on September 22, 2026 as the first model in Anthropic's Claude 5.5 family. Anthropic positions it for advanced coding, complex agents, professional knowledge work, and long-running workflows where preserving intent across many steps matters more than minimum latency.
Its most distinctive operational behavior is always-on adaptive thinking. Developers can control reasoning effort, but adaptive thinking itself cannot be disabled. This makes migration testing important for older agents that previously depended on a thinking-off path or different effort defaults.
The Claude Opus 5.5 API in CometAPI provides a unified route for the same model ID, `claude-opus-5-5`, alongside other models for workload routing.
Claude Sonnet 5.5
Claude Sonnet 5.5 was released on September 28, 2026 as the second model in the Claude 5.5 family. Anthropic describes it as a faster, lower-cost complement to Opus 5.5 for well-scoped everyday work, including bug fixing, document creation, coding, agents, and design-oriented tasks.
Anthropic reports that Sonnet 5.5 generates output more than 30% faster than Sonnet 5 and can cost up to 30% less per task than that predecessor. These are provider-reported comparisons with Sonnet 5, not measured speed or task-cost ratios against Opus 5.5.
The Claude Sonnet 5.5 API in CometAPI uses the model ID `claude-sonnet-5-5` and is suitable for testing Sonnet as the lower-cost execution layer in mixed-model applications.
Claude Opus 5.5 vs Sonnet 5.5: Performance
Anthropicโs published results show small score differences on several knowledge-work and computer-use evaluations. Opus reports higher scores on FrontierCode, CursorBench, and Humanityโs Last Exam, while Sonnet reports a higher Terminal-Bench score. The comparisons depend on effort settings and evaluation conditions.
| Benchmark | Claude Opus 5.5 | Claude Sonnet 5.5 | What it measures |
|---|---|---|---|
| Terminal-Bench 4.0 | 66.4% | 70.6% | Command-line agent tasks |
| FrontierCode 1.1 Main | 54.4% | 46.2% (Max) | Real-world software engineering |
| CursorBench 4.0 | 57.8% | 55.5% | Ambiguous multi-file coding tasks |
| GDPval-AA v2.1 | 1846 | 1844 | Professional knowledge work |
| AA-Briefcase v1.1 | 1822 | 1811 | Long-horizon knowledge work |
| Humanity's Last Exam, tools | 67.7% | 64.5% | Multidisciplinary reasoning |
| OSWorld 2.1 | 81.8% | 80.1% | Computer use |
| Chartography | 64.4% | 61.6% | Visual chart recognition |
These are published results, not a controlled comparison conducted for this article.
- Effort: Opusโs Terminal-Bench result uses Xhigh. Sonnetโs FrontierCode score is higher at Xhigh than at Max.
- Scoring and tools: OSWorld uses partial credit; Chartography results here use no tools.
- Deployment: Sonnetโs GDPval-AA and AA-Briefcase results were measured on a pre-release deployment with a structured-output bug that has since been fixed.
Agentic Coding
Sonnet 5.5's 70.6% Terminal-Bench 4.0 result is higher than Opus 5.5's 66.4% reported score, but the official footnote says the Opus result is at Xhigh effort. On FrontierCode 1.1 Main, Opus leads 54.4% to Sonnet's 46.2% Max result; on CursorBench 4.0, Opus leads 57.8% to 55.5%.
This split matters because coding-agent benchmarks reward different behaviors. Terminal-Bench emphasizes successful multi-step execution in a command-line environment, while CursorBench uses ambiguous multi-file tasks from real coding sessions. For bounded coding and iterative execution, Sonnet can be highly competitive; for broader repository-scale work, Opus retains stronger evidence in Anthropic's published evaluations.
Knowledge Work and Reasoning
On GDPval-AA v2.1, Sonnet 5.5 scores 1844 compared with Opus 5.5 at 1846. On AA-Briefcase v1.1 the gap is 1811 versus 1822. These results are notable because the pricing gap is much larger than the benchmark gap.
Anthropic identifies Opus 5.5 as stronger at complex, open-ended work requiring sustained judgment. For research, architecture, and audits, test whether that behavior reduces incorrect decisions or human correction in your own tasks rather than inferring an economic advantage from small benchmark margins.
Computer Use and Visual Tasks
On OSWorld 2.1, using partial-credit scoring, Opus scores 81.8% and Sonnet 80.1%. On Chartography without tools, the scores are 64.4% and 61.6%, respectively. For browser or GUI agents, this suggests that latency, tool-call efficiency, and task-level cost may matter as much as the headline benchmark gap.
Benchmark Interpretation
The benchmark story is not that Sonnet has replaced Opus. It is that Anthropic has narrowed the capability gap enough that workload shape now matters more than model tier alone. Well-scoped and latency-sensitive tasks increasingly favor Sonnet's economics, while ambiguity, long horizons, and expensive failure modes remain the strongest reasons to test Opus.
Claude Opus 5.5 vs Sonnet 5.5: Pricing
Official Claude API Pricing
The Opus pricing specification and Sonnet pricing specification distinguish standard token rates, cache retention windows, and Batch discounts. Prices below are USD per million tokens; confirm optional service modifiers separately.
| Pricing metric | Claude Opus 5.5 | Claude Sonnet 5.5 |
|---|---|---|
| Input / 1M tokens | $4.00 | $2.00 |
| Output / 1M tokens | $20.00 | $10.00 |
| Cache read / 1M tokens | $0.10 | $0.20 |
| 5-minute cache write / 1M tokens | $5.00 | $2.50 |
| 1-hour cache write / 1M tokens | $8.00 | $4.00 |
| Batch input / 1M tokens | $2.00 | $1.00 |
| Batch output / 1M tokens | $10.00 | $5.00 |
Sonnet has half the standard input, output, and cache-write rates.
Cache reads follow the same 2:1 price ratio: Sonnet 5.5 costs $0.10/M cached input, while Opus 5.5 costs $0.20/M. Reusing cached prefixes reduces input costs for both models while preserving Sonnet's lower per-token rate. Total task savings still depend on output length, cache writes, retries, and acceptance rate.
Cost per Accepted Task
For a simple illustration, a request with 100K uncached input tokens and 10K output tokens costs about $0.60 on Opus 5.5 and $0.30 on Sonnet 5.5 at standard rates. But a 2x token-rate difference does not guarantee a 2x cost-per-success difference. Retries, tool calls, output length, cache hits, failed attempts, and human correction can change the result.
Production evaluations should therefore log cost per accepted task alongside completion rate, p50/p95 latency, retries, tool calls, and human intervention.
CometAPI Pricing
CometAPI's model catalog advertises a 20% discount on many supported Anthropic routes. For the Claude Opus 5.5 API in CometAPI, the referenced catalog pricing is $3.20/M input and $16/M output. For the Claude Sonnet 5.5 API in CometAPI, localized catalog data shows $1.60/M input and $8/M output. Because gateway pricing can change, confirm the live model route before budgeting production traffic.
| CometAPI rate | Claude Opus 5.5 | Claude Sonnet 5.5 |
|---|---|---|
| Input / 1M | $3.20 | $1.60 |
| Output / 1M | $16.00 | $8.00 |
| Relative discount vs official | 20% | 20% |
Claude Opus 5.5 vs Sonnet 5.5: Technical Specifications
Both models share the core context and output limits shown in the At a Glance table. The additional 300K output limit is a Batch API beta capability, rather than the standard interactive output limit.
Context length is not the differentiator between these two models. Both support the same 1M-token window and 128K standard output ceiling. The more meaningful differences are reasoning behavior, speed, and how much difficult judgment the task requires.
Sonnet's reported output-speed improvement is relative to Sonnet 5. Opus also has Fast mode with up to 2.5x output-token throughput, priced at $8/M input and $40/M output. It is a research preview on the Claude API; this is not a guarantee of 2.5x faster end-to-end tasks or time to first token.
Architecture Disclosure and Integration Behavior
The cited materials do not disclose parameter counts or sufficient internal architecture details for a defensible dense-versus-MoE comparison. Compare documented interfaces and behavior instead. Both migrations require testing tool-choice constraints and preserved thinking; Opus adaptive thinking cannot be disabled. Validate conversation state when routing between models rather than forwarding opaque thinking blocks without checking compatibility.
Claude Opus 5.5 vs Sonnet 5.5: Use Cases
A useful deployment strategy is to treat Sonnet 5.5 as the default execution model and Opus 5.5 as an escalation model. This can reduce spending on well-specified, repeatable tasks while reserving Opus for work that benefits from sustained judgment. Savings depend on Sonnetโs acceptance rate and how often tasks need escalation.
Workload-Based Selection
| Workload | Claude Opus 5.5 | Claude Sonnet 5.5 |
|---|---|---|
| Routine coding | Capable, higher cost | Strong fit |
| Bug fixing | Useful for difficult cases | Strong fit |
| High-volume API traffic | Higher unit cost | Strong fit |
| Document / slide generation | Strong | More economical |
| Coding sub-agents | Use selectively | Strong fit |
| Repository-scale migration | Strong fit | Test for bounded work |
| Ambiguous architecture | Strong fit | Depends on complexity |
| Long-running autonomous agents | Strong fit | Good execution layer |
| Difficult research / analysis | Strong fit | Good for bounded work |
| Latency-sensitive UX | Moderate | Strong fit |
| Mixed production workload | Escalation model | Default execution model |
A practical router can start with Sonnet and escalate when the task crosses a threshold for ambiguity, tool-loop length, repeated failures, or business impact. The routing rule should be validated against production-like tasks rather than assumed from benchmark scores.
How to Call Opus 5.5 and Sonnet 5.5 Through CometAPI
Create a CometAPI API key and configure an Anthropic-compatible client to use the CometAPI endpoint. Choose the model ID for the task, send your prompt through the Messages API, and read the text response. When comparing the models, keep the prompt, output limit, tools, and acceptance criteria consistent, and record effective reasoning effort.
Opus 5.5 Example
For a migration-plan review, select claude-opus-5-5 and ask the model to identify the highest-risk steps, explain their impact, and suggest safeguards. Send the request through the CometAPI Messages API and review the returned text.
Sonnet 5.5 Example
For the same migration-plan review, select claude-sonnet-5-5 and submit the same prompt and output limit through CometAPI. Compare the response against the same acceptance criteria, then record latency, retries, and actual cost before deciding which model fits the workload.
For production routing, keep both model IDs behind the same application interface and log completion quality, latency, retries, and actual billed cost. Avoid escalating purely because a prompt is long; ambiguity and failure cost are usually better signals.
Conclusion
Claude Opus 5.5 and Sonnet 5.5 now share almost the same technical envelope, so model choice is increasingly about economics and workload behavior rather than context size. Sonnet combines faster execution and half-price standard tokens with benchmark performance that is often close to Opus.
Opus becomes more valuable as ambiguity, task duration, and the cost of a wrong decision increase. Its value is less about having a larger context window and more about sustaining judgment through difficult, open-ended workflows.
For many production teams, the most efficient architecture will use both: Sonnet for the repeatable majority of work, and Opus for the subset of tasks where stronger reasoning measurably reduces failure, retries, or human intervention.
FAQ
How should a Claude 5.5 router prevent expensive escalation loops?
Set a maximum attempt count and a budget before execution. Escalate after a reproducible failure, missing evidence, or a task-specific quality gate, rather than after every uncertain answer. Record which failure triggered Opus and whether it improved the accepted result. If neither model passes, return the unresolved issue for review instead of retrying indefinitely.
How can Opus and Sonnet be compared fairly on one workload?
Use the same task corpus, available tools, input evidence, output limit, and scoring rubric. Record effective effort and test cold-cache and warm-cache runs separately. Review results without revealing the model when practical. Report acceptance rate and total cost including unsuccessful attempts; equal token prices or one benchmark do not establish equal value.
What should be retained when switching Claude 5.5 models mid-task?
Preserve user instructions, relevant evidence, tool results, and an explicit progress summary. Treat opaque thinking state as model- and conversation-specific; do not assume it can be replayed across routes. Test the provider-supported handoff behavior before production, especially if the workflow mixes accounts, gateways, or SDKs.
When should a Claude 5.5 model choice be reevaluated?
Rerun the affected acceptance tests after a deployment fix, routing change, price change, tool change, or material prompt update. Keep the earlier run as a baseline and record date, model ID, endpoint, configuration, and harness version. This distinguishes a model change from changes in the surrounding application.