Claude Opus 5 API Overview
Claude Opus 5 API is Anthropic's Opus-class model for complex agentic coding, enterprise automation, deep reasoning, long-context analysis, and high-value knowledge work. Anthropic released Claude Opus 5 on July 24, 2026, with API model ID claude-opus-5, a 1M-token context window, 128k maximum synchronous output, adaptive thinking on by default, and new controls for effort, fallback, prompt caching, and tool changes.
Technical Specifications
| Item | Specification |
|---|
| Model name | Claude Opus 5 |
| API model ID | claude-opus-5 |
| Provider | Anthropic |
| Native CometAPI endpoint | POST /v1/messages |
| OpenAI-compatible CometAPI endpoint | POST /v1/chat/completions |
| Input types | Text and image input |
| Output type | Text output |
| Context window | 1M tokens |
| Maximum output tokens | 128k tokens on the synchronous Messages API; up to 300k output tokens on supported Message Batches API requests with Anthropic's output-300k-2026-03-24 beta header |
| Adaptive thinking | Yes; on by default |
| Effort control | low, medium, high, xhigh, and max; high is the default on the Claude API and Claude Code |
| Official Anthropic pricing | $5 per million input tokens and $25 per million output tokens |
| Prompt cache pricing | $6.25 per million 5-minute cache writes, $10 per million 1-hour cache writes, and $0.50 per million cache hits |
| CometAPI listed pricing | $4 per million input tokens and $20 per million output tokens, according to the CometAPI Claude Opus 5 model page checked on July 26, 2026 |
| Reliable knowledge cutoff | May 2026 |
What Is Claude Opus 5 and What Is New?
Claude Opus 5 is the next Opus model after Claude Opus 4.8. Anthropic positions it as the model to start with for complex agentic coding and enterprise work, while Claude Fable 5 remains the higher-capability option for workloads where peak intelligence matters more than price or latency. The practical difference is price-performance: Anthropic says Opus 5 approaches Fable 5 capability at half the official token price and improves substantially over Opus 4.8 at the same official price.
The biggest change for developers is that Claude Opus 5 is not only a stronger model string. Its API behavior changes in ways that affect production integrations. Adaptive thinking is enabled by default, and the effort parameter is now the main way to trade depth against speed and token use. The model also supports a lower prompt-cache minimum of 512 tokens, beta mid-conversation tool changes, beta server-side fallback behavior, and Fast mode on the Claude API. that disabling thinking at xhigh or max effort returns a 400 error; if an application must disable thinking, it should use high effort or below.
Benchmark Performance of Claude Opus 5
Claude Opus 5 has strong benchmark support from Anthropic, ARC Prize, and Artificial Analysis. Anthropic reports that Opus 5 more than doubles Claude Opus 4.8 on Frontier-Bench v0.1 at lower cost per task, comes within 0.5% of Claude Fable 5's peak CursorBench 3.2 score at max effort, and outperforms other models on selected knowledge-work and computer-use cost-performance comparisons.
Independent benchmark providers add more concrete numbers. ARC Prize reports that Claude Opus 5 High scored 30.16% on ARC-AGI-3, while Opus 5 Max scored 97.5% on ARC-AGI-1 and 90.4% on ARC-AGI-2 Semi-Private. Artificial Analysis reports an Intelligence Index score of 61 for Claude Opus 5 Max, 89% on Terminal-Bench v2.1 at max effort, 1861 Elo on GDPval-AA v2, and 1720 Elo on AA-Briefcase.
| Benchmark or metric | Claude Opus 5 result |
|---|
| ARC-AGI-3 Public Demo, High effort | 30.16% |
| ARC-AGI-1, Max effort | 97.5% |
| ARC-AGI-2 Semi-Private, Max effort | 90.4% |
| Artificial Analysis Intelligence Index, Max effort | 61 |
| Terminal-Bench v2.1, Max effort | 89% |
| GDPval-AA v2, Max effort | 1861 Elo |
| AA-Briefcase, Max effort | 1720 Elo |
| Output speed, Max effort | 52.6 tokens per second |
| Time to first answer token, Max effort | 68.04 seconds |
These results suggest Claude Opus 5 is strongest when a workflow rewards planning, verification, tool use, multi-step completion, and long-context reasoning. They also show a latency tradeoff at high reasoning settings, so production teams should evaluate cost per successful task rather than only benchmark rank.
Features and Highlights of Claude Opus 5
1M-Token Context for Large Workloads
Claude Opus 5 supports a 1M-token context window as both the default and maximum context size. That makes it suitable for repository-scale coding, long legal contracts, multi-document research, financial workbooks, incident timelines, customer-support histories, and enterprise knowledge-base analysis.
Adaptive Thinking by Default
Unlike Claude Opus 4.8, which required adaptive thinking to be explicitly enabled, Claude Opus 5 runs with adaptive thinking by default. The model decides how much thinking to spend per turn, while developers use effort to tune the behavior.
Effort Levels for Cost-Quality Control
Claude Opus 5 supports low, medium, high, xhigh, and max effort levels. Anthropic recommends starting at the default high, stepping down when quality holds, and stepping up for the hardest long-horizon coding or agent tasks.
Stronger Agentic Coding and Verification
Anthropic describes Opus 5 as a step-change over Opus 4.8 for agentic coding, long-horizon tasks, code review, and bug-finding. In practice, this is the model class to test when an AI agent must inspect files, call tools, run checks, correct mistakes, and finish multi-file work rather than only draft code snippets.
Better Prompt Caching Economics for Shorter Contexts
The minimum cacheable prompt length drops from 1,024 tokens on Claude Opus 4.8 to 512 tokens on Claude Opus 5. For repeated agent sessions, shared system prompts, tool manifests, or long project context, prompt caching can reduce repeated input cost because cache hits are priced lower than fresh input tokens.
Mid-Conversation Tool Changes
Claude Opus 5 supports beta mid-conversation tool changes. Developers can add or remove available tools between turns while preserving the prompt cache, which is useful when an agent moves from research to coding, from coding to testing, or from analysis to deployment.
Server-Side Fallback for Refusal Cases
Anthropic's beta fallbacks parameter can use a default fallback mode for safety-classifier refusal categories. This is not a general availability or rate-limit retry system; it is designed for cases where Anthropic has a recommended fallback model for a refusal category.
Claude Opus 5 vs Claude Sonnet 5 vs Opus 4.8 vs Fable 5
| Dimension | Claude Opus 5 | Claude Sonnet 5 | Claude Opus 4.8 | Claude Fable 5 |
|---|
| Best role | Complex agentic coding and enterprise work | Faster high-intelligence production work | Previous Opus baseline and migration fallback | Highest broadly released Claude capability |
| API model ID | claude-opus-5 | claude-sonnet-5 | claude-opus-4-8 | claude-fable-5 |
| Official Anthropic price | $5/M input, $25/M output | $2/M input and $10/M output through August 31, 2026; $3/M input and $15/M output starting September 1, 2026 | $5/M input, $25/M output | $10/M input, $50/M output |
| Comparative latency | Moderate | Fast | Not listed in the current latest-model comparison table; prior Opus tier baseline | Slower |
| Adaptive thinking | On by default | On by default | Available but not default for requests unless specified | Always on |
| Effort support | low, medium, high, xhigh, max | low, medium, high, xhigh, max | low, medium, high, xhigh, max | low, medium, high, xhigh, max |
| Knowledge cutoff | May 2026 | January 2026 | Not shown in Anthropic's current latest-model table | January 2026 |
| When to choose it | Use when Opus-level accuracy matters but Fable 5 is too expensive or slow | Use for high-volume coding, support, document, and agent workflows | Keep for pinned legacy behavior, fallback, or migration comparison | Use when the highest available Claude capability justifies the higher price |
In addition, their maximum input and context window are the same.
Claude Opus 5 is the most balanced premium choice in this group. Claude Sonnet 5 is better for volume-sensitive production traffic, Claude Opus 4.8 is mainly a legacy baseline after the Opus 5 launch, and Claude Fable 5 is the upper-capability choice when cost is secondary.
How to Use the Claude Opus 5 API on CometAPI
Step 1: Create a CometAPI Key
Sign in to CometAPI, open the API key page, create a key, and store it in an environment variable such as COMETAPI_KEY. Do not put production API keys in client-side code, public repositories, screenshots, or support tickets.
Step 2: Call the Native Anthropic Messages Endpoint
Use the native /v1/messages route when you want Claude-specific behavior such as adaptive thinking, effort control, prompt caching, tool use, web search, streaming, and Anthropic-style response content blocks.
Step 3: Use the OpenAI-Compatible Endpoint for Portable Routing
Use /v1/chat/completions when your application already uses OpenAI-compatible SDKs or when you want to compare Claude Opus 5 with GPT, Gemini, DeepSeek, Kimi, Qwen, and other models behind one routing layer.
For production, test both endpoints with real prompts, log input tokens, output tokens, cache behavior, effort level, latency, refusal behavior, and final task success. Use Anthropic's official documentation as the authority for Claude-specific parameters and CometAPI's docs for how that request shape is forwarded.
What’s Possible With Claude Opus 5
Claude Opus 5 is best suited to applications where correctness and follow-through matter more than a cheap one-shot answer. Developers can build repository-scale coding agents, migration assistants, bug investigation tools, code review systems, long-context research assistants, legal and financial document analyzers, scientific-literature workflows, technical support escalation bots, spreadsheet and slide generation tools, and autonomous operations assistants.
It is also useful as an escalation model inside a multi-model architecture. A product can route ordinary support or extraction traffic to Claude Sonnet 5 or lower-cost models, then escalate ambiguous, risky, or high-value turns to Claude Opus 5. This pattern keeps the premium model focused on work where deeper reasoning changes the outcome.
Use Claude Opus 5 API for hard coding agents, root-cause debugging, multi-file refactors, code review, enterprise document analysis, financial modeling, legal review, scientific reasoning, long-context research, professional report generation, and operations automation. On CometAPI, the strongest deployment pattern is selective escalation: test Claude Opus 5 against Claude Sonnet 5, Claude Fable 5, and non-Claude alternatives, then route each workload by cost per accepted result rather than by model reputation alone.
Why Use CometAPI for Claude Opus 5?
CometAPI is useful for Claude Opus 5 when a team wants one API key, unified billing, model comparison, and easier migration across providers. CometAPI documents both a native Anthropic Messages endpoint and an OpenAI-compatible Chat Completions endpoint, so teams can choose Claude-native controls for advanced workflows or keep a portable integration shape for multi-model routing.
Limitations
Claude Opus 5 is a premium reasoning model, not the default choice for every request. At higher effort settings, it can spend more tokens and produce higher time-to-first-token latency than lighter models. Artificial Analysis reports 68.04 seconds to first answer token for its max-effort measurement, which makes routing and effort selection important for user-facing apps.
Developers should also avoid assuming unsupported behavior. Anthropic has not disclosed model parameter count, and the model weights are proprietary. Fast mode is in research preview on the Claude API, not all cloud platforms. Server-side fallback and mid-conversation tool changes are beta features. For security workflows, Anthropic states that Opus 5 can support beneficial vulnerability-finding use cases but applies safeguards to higher-risk tasks such as binary-based vulnerability scanning, penetration testing, and exploit generation.
