Claude Opus 5: Knowledge Cutoff, Pricing and Context Window for .NET Developers

Claude Opus 5 has a knowledge cutoff of May 2026, a context window of 1M input tokens, and a price of $5 per million input tokens. The table below carries the rest of the numbers, and the article after it is about what they mean when you are actually building on .NET.

Claude Opus 5 at a Glance

The rest of this article is what those numbers actually mean for .NET work, where they hold up, and where I would not trust them without testing them on your own code.

Where Opus 5 Sits in the Claude 5 Family

The Claude 5 family now has four tiers: Fable 5 at the frontier, Opus 5 just behind it, Sonnet 5, and Haiku 4.5. The positioning matters. Fable 5 is the one you pick for the most ambitious long horizon agent work, but it costs $10 per million input tokens and $50 per million output, has a January 2026 knowledge cutoff, and requires 30 day data retention, which rules it out for a lot of enterprise work. Opus 5 is meant to be the default: near frontier capability at $5 and $25 per million tokens, no retention requirement, and a May 2026 cutoff, the freshest of any Claude model.

The release pace is worth noting. Opus 5 shipped on 24 July 2026, the fourth Claude 5 model in under two months. That creates real evaluation overhead if you maintain model selection logic. The API model ID is claude-opus-5 with no date suffix, so pinning is simple, but your evaluation loop has to keep up.

What Actually Matters to Developers

Coding Benchmarks Worth Taking Seriously

SWE-bench Verified is the benchmark I trust most for everyday coding work, because it uses real GitHub issues with solutions that are verified by execution. Opus 5 scores 96.0 percent on Verified and 79.2 percent on the harder SWE-bench Pro, up from 69.2 percent for Opus 4.8. That is a big jump. On Frontier-Bench v0.1, an agentic coding benchmark, Opus 5 scores 43.3 percent and beats both Fable 5 and GPT-5.6 Sol. CursorBench 3.2 puts Opus 5 at max effort within 0.5 percent of Fable 5's best score, at half the cost.

For multimodal coding, reading screenshots, diagrams or UI mockups as part of a task, SWE-bench Multimodal went from 38.4 to 59.4 percent. If any of your agents read architecture diagrams or UI screenshots, that is directly useful.

The number that surprised me most is ARC-AGI-3: 30.2 percent against 7.8 percent for the next best model. ARC-AGI-3 is built to punish pattern memorisation, so a roughly threefold lead suggests the model handles genuinely new reasoning better than the leaders from six months ago.

Effective Context at 1M Tokens

Opus 4.8's 200k window degraded in practice, with measurably worse performance in the middle of the window. Opus 5 goes to 1M tokens and Anthropic says performance holds throughout. I would not take that at face value without testing it on your own codebase, but even an honest 600k effective window changes what is possible for refactoring a large solution or auditing a big dependency graph.

Maximum output is 128k tokens. For .NET projects that generate scaffolding, migration scripts or test suites in one pass, that ceiling matters less often than the input window does.

Opus 5 Inside Claude Code

Switching is one line:

/model claude-opus-5
# or on the command line:
--model claude-opus-5 --effort high

The effort toggle, low through medium, high, xhigh and max, is the most important new control. At xhigh the model beats everything else on the GDPval-AA v2 Elo leaderboard while using 25 percent fewer output tokens than max effort. That is the sweet spot for complex agent work: you get the reasoning depth without paying for an enormous thinking chain.

There is a real trap here. At xhigh or max, the model spends a lot of tokens thinking before it produces anything. If your max_tokens budget was tuned for Opus 4.8 or something smaller, the agent can quietly run out of budget mid task. You see truncated output, abandoned tool calls, or a chain of subagents that just gives up halfway with no error. Raise max_tokens generously when you move to higher effort, and use integration tests that run to completion to prove it.

Two API betas shipped with Opus 5. Automatic fallback routes a request that trips a safety classifier to Opus 4.8 instead of blocking it. Mid conversation tool changes let you swap toolsets between turns without invalidating the prompt cache. The second one is genuinely useful if your agent changes its tools by phase, for example moving from a read only analysis phase to a write capable execution phase in one session.

Some behaviour changes are worth flagging. The model verifies its own output without being asked, follows review instructions literally, so conservative wording in a system prompt suppresses recall and not just tone, produces longer output by default, and will expand the scope of a task on its own. All of that helps in a genuinely autonomous session, but it means an existing pipeline can behave differently after nothing more than a model string change.

Cost and Performance Trade-offs

Opus 5 Fast doubles the price to match Fable 5, but without the retention requirement and with better computer use and automation scores. OSWorld 2.0 is 70.57 percent against Opus 4.8's 55.7 percent, and Zapier AutomationBench is 26.0 percent against Fable 5's 17.4 percent. If you need Fable 5 latency without the retention policy, Opus 5 Fast is the way.

For batch workloads or background agents where latency does not matter, standard Opus 5 at medium effort is a good deal. Anthropic's own numbers put medium effort at roughly $0.89 per task on AutomationBench with 24 percent success, about half the cost of max effort and only a few points behind on routine work.

Practical Guidance for .NET AI Applications

A straightforward way to pick a model for .NET coding agents:

• Interactive assistant or IDE integration. Opus 5 at medium or high effort. The 96 percent SWE-bench Verified score and the self verification make this the default.
• Background CI agent for refactoring, test generation or migration scripts. Opus 5 at xhigh. The 25 percent token saving over max effort adds up at scale.
• Zero retention requirement. Opus 5 is the strongest Claude model available to you. Fable 5 is out.
• Latency critical paths, inline completions or live chat. Opus 5 Fast, or drop to Sonnet 5 if the task allows.
• The most advanced autonomous research agents with no retention constraint. Fable 5 still leads on FrontierCode and on Humanity's Last Exam without tools.

For a .NET application on the Anthropic SDK, migration is a model string change plus a careful look at max_tokens:

using Anthropic.SDK;
using Anthropic.SDK.Messaging;
 
var client = new AnthropicClient();
 
var request = new MessageRequest
{
    Model = "claude-opus-5", // was claude-opus-4-8
    MaxTokens = 16384,        // raise this, effort spends thinking tokens
    Messages = new List<Message>
    {
        new Message(RoleType.User, "Refactor this C# service to use the new IHostedService pattern.")
    },
    System = "You are a senior .NET engineer. Respond with complete, compilable C# code."
};
 
var response = await client.Messages.GetClaudeMessageAsync(request);
Console.WriteLine(response.Content[0].Text);

Using the effort toggle through the API:

// Effort is passed as a beta header or an extended parameter depending on SDK version.
// Check the Anthropic SDK release notes for the exact field name.
var request = new MessageRequest
{
    Model = "claude-opus-5",
    MaxTokens = 32768, // generous budget for xhigh effort thinking tokens
    Messages = messages,
    AdditionalProperties = new Dictionary<string, object>
    {
        ["effort"] = "xhigh"
    }
};

Check the field name against the current SDK release notes. The effort parameter was still settling when this was written.

Caveats, and How to Evaluate It on Your Own Workload

Priority Tier is gone. Opus 4.8 supported it, Opus 5 does not. If your capacity planning relies on Priority Tier for throughput guarantees, sort that out before you migrate.

Behaviour drift is the real risk. The API surface has not changed, but the model's defaults have. Longer output, scope expansion and self verification can change what your pipeline does with no code change at all. Run your integration suite against Opus 5 before promoting it, and check specifically that agents finish inside the token budget and do not widen scope in ways that break whatever consumes their output.

Be careful with security tooling. Opus 5 has raised cybersecurity safeguards, similar to Fable 5. Legitimate security work, penetration test scaffolding, vulnerability scanners, security research agents, can sometimes trip those classifiers. The automatic fallback to Opus 4.8 stops a hard failure, but if accuracy on security tasks matters to you, confirm that the fallback behaviour is acceptable rather than assuming you will not notice.

Indirect prompt injection is better, not solved. On the Gray Swan benchmark, attacker success within 15 attempts drops from 5.5 percent to 2.0 percent. For agents that read untrusted input, emails, documents, web pages, that is a real improvement, but 2.0 percent is not zero. Keep your other defences.

The benchmarks are strong enough that Opus 5 is my default recommendation for a new .NET agent project today. But the evaluation that counts is your own task distribution, your token budget and your latency requirements, not a leaderboard.

Common Questions About Claude Opus 5

What is the knowledge cutoff for Claude Opus 5?

May 2026, the freshest cutoff of any Claude model at the time of writing. Fable 5, which sits above it at the frontier, is still on January 2026.

Is the cutoff date the same across the Claude 5 family?

No, and the order is not the one you would expect. Opus 5 is on May 2026 while Fable 5, which sits above it at the frontier and costs twice as much, is still on January 2026. The stronger model knows less about recent releases, so for anything published this year you have to supply the information yourself rather than trusting either of them.

How much does Claude Opus 5 cost?

$5 per million input tokens and $25 per million output tokens. Opus 5 Fast is $10 and $50, runs about 2.5 times faster, and still carries no data retention requirement.

How large is the context window?

1M input tokens, with a maximum output of 128k. Anthropic says performance holds across the window rather than degrading in the middle the way Opus 4.8's 200k window did. Verify that on your own codebase before you build a workflow that depends on it.

What is the API model ID?

claude-opus-5, with no date suffix, so pinning it is straightforward.

How does it score on coding benchmarks?

96.0 percent on SWE-bench Verified and 79.2 percent on the harder SWE-bench Pro, up from 69.2 percent for Opus 4.8. On ARC-AGI-3, which is built to punish pattern memorisation, it scores 30.2 percent against 7.8 percent for the next best model.