Chat With Claude Opus 5 on Lorka AI

Code, Plan, and Execute. Try Claude Opus 5 with Lorka AI and start driving complex agentic workflows with the premier deep-analysis model to make your toughest tasks effortless.

Claude
Ask anything...
Reasoning
💡💡💡💡💡
Frontier
Speed
Medium
Context Handling
🧠🧠🧠🧠🧠
Strong
Input
Text, Image
Output
Text

Anthropic's flagship Opus model delivering frontier reasoning, state-of-the-art coding and knowledge work, adaptive thinking, long-context understanding, and highly reliable agentic execution.

Context window1M tokens
Max output tokens128K tokens
Knowledge cutoffMay, 2026

Access Claude Opus 5 for More Reliable, High-Level Work

Use a precision-focused model built to complete demanding professional tasks with steady reasoning, efficient execution, and fewer unnecessary interventions.

Near-frontier intelligence, lower cost

Handle advanced tasks with performance positioned close to Anthropic’s highest-end models while maintaining more practical daily-use economics.

Persistent coding and agentic execution

Work through multi-file changes, tool calls, technical failures, and long-running workflows instead of stopping at a surface-level recommendation.

More practical everyday performanc

Apply premium reasoning to regular coding, research, planning, and business work without reserving the model only for exceptional tasks.

Efficient task completion

Reach useful results with fewer unnecessary iterations, more disciplined outputs, and configurable reasoning effort for different workloads.

Safety-aware advanced capability

Use high-end reasoning within Anthropic’s safety framework, with fallback systems available for some requests that require additional safeguards.

See Claude Opus 5 Complete Real Professional Workflows

The following Claude Opus 5 benchmark examples show how the model can transform a focused prompt into an implementation-ready professional output.

User

Review this service architecture, identify the biggest technical risks, propose a migration plan, and implement the first safe refactor with tests.

Claude
Claude Opus 5Enterprise Codebase Review and Safe Refactoring

Main risks Payment, inventory, database writes, and notifications run inside one method. Retried requests can create duplicate orders. A notification failure can roll back an otherwise valid transaction. External dependencies make the service difficult to test. Migration plan Add idempotency protection. Separate validation from side effects. Move payment and inventory behind interfaces. Publish notifications only after the transaction succeeds.

JSON
1### Step 1: Executive Summary
2- Component: OrderService
3- Primary Purpose: Create orders while preventing duplicates using an idempotency key.
4- Key Behavior: Returns an existing order if the same request is processed more than once.
5
6---
7
8### Step 2: Service Implementation
9
10#### OrderService
11- Dependencies:
12 - Repository
13 - Validator
14- Responsibilities:
15 - Check for an existing order using the idempotency key.
16 - Validate the incoming request before persistence.
17 - Save and return a new order when no duplicate exists.
18
19Method:
20"create(request)"
21
22Execution Flow:
231. Search for an existing order using request.idempotency_key.
242. Return the existing order if one is found.
253. Validate the request.
264. Save the request through the repository.
275. Return the newly created order.
28
29---
30
31### Step 3: Test Scenario
32
33Title:
34"Retry returns existing order"
35
36Purpose:
37"Verify that repeated requests with the same idempotency key do not create duplicate orders."
38
39Execution Steps:
401. Call service.create(request) for the first time.
412. Call service.create(request) again using the same request.
423. Compare both returned orders.
434. Verify that only one order exists in the repository.
44
45---
46
47### Step 4: Assertions
48
49Assertion 1
50
51Condition:
52"The first and second returned orders are equal."
53
54Expected Result:
55"Both calls return the same order instance or equivalent persisted order."
56
57Assertion 2
58
59Condition:
60"Repository contains exactly one order."
61
62Expected Result:
63"No duplicate order is created after a retry."
64
65---
66
67### Step 5: Behavioral Outcome
68
69Verified Behavior:
70- Duplicate requests are detected through the idempotency key.
71- Validation is executed only for new orders.
72- Existing orders are returned immediately on retries.
73- Repository persistence occurs only once.
74
75---
76
77### Step 6: Overall Assessment
78- The service enforces idempotent order creation.
79- Duplicate retries do not generate additional records.
80- Repository integrity is maintained through a single persisted order.
81- The test confirms correct retry behavior.
82
83---
84
85### Step 7: Self-Verification
86- Preserved service responsibilities
87- Maintained execution flow order
88- Included all test assertions
89- Retained retry and idempotency behavior
90- Preserved repository validation outcome
91
92Result: Ready for review

Next step: Extract payment authorization only after this boundary is covered by tests.

User

Read these long reports and notes, compare the evidence, and draft a structured decision memo with tradeoffs and recommendations.

Claude
Claude Opus 5Research Synthesis and Decision Memo

Recommendation Choose the smaller central-region warehouse, subject to a three-month demand validation period. Why Regional orders grew 18% year over year. Current delivery time is 3.8 days against a 2.5-day target. The location would place 64% of customers within one-day ground delivery. Labor costs are estimated to be 11% lower than at the coastal site. Tradeoffs The central site offers lower cost and faster payback but less expansion capacity. The coastal site provides more room to grow but risks remaining underused. Key risks Demand depends heavily on two customers. Fuel assumptions differ across reports. Labor data is regional rather than city-specific. Next steps Validate customer concentration, run a 20% lower-growth scenario, and approve only if utilization remains above 65%.

User

Analyze these internal docs, summarize the bottlenecks, and create an action plan with milestones, owners, and priorities.

Claude
Claude Opus 5Operational Bottleneck Analysis

Biggest bottlenecks Manual approvals: Low-value purchases still pass through four approval stages. Duplicate entry: Customer data is re-entered across the CRM, billing system, and onboarding tracker. Incomplete handoffs: Sales closes deals before technical and billing details are confirmed. Action plan Priority 1 — Simplify approvals Owner: Finance Operations Deadline: Week two Goal: Reduce median approval time below one day Priority 2 — Standardize handoffs Owner: Revenue Operations Deadline: Week three Goal: Reduce incomplete handoffs by 60% Priority 3 — Synchronize systems Owner: Business Systems Deadline: Pilot by week six Goal: Reduce record mismatches below 2% Start with approvals because the change is low risk and delivers the fastest measurable improvement.

User

Work through this multi-step task, verify each stage, and revise your answer until the final output is complete and internally consistent.

Claude
Claude Opus 5Multi-Step Agentic Verification

1. Validate the data Detected two duplicate customer IDs, one invalid cancellation date, and seven records without a segment. 2. Calculate churn Active customers: 1,240 Cancellations: 62 Monthly churn: 5.0% 3. Identify the highest-risk segment Small business, monthly: 8.4% Small business, annual: 4.7% Mid-market: 3.1% Enterprise: 1.6% 4. Recommend an intervention Target monthly small-business accounts when usage drops, support tickets remain unresolved, or a payment fails. Actions: Send a personalized usage summary. Offer onboarding before discounts. Escalate product defects. Review retained revenue after 30 and 60 days. 5. Verify the conclusion The recommendation targets the highest churn rate, not simply the segment with the most cancellations, so it matches the stated objective.

Bring Workflows to New Heights With Claude Opus 5 on Lorka AI

Combine Opus 5 with a variety of premium AI models such as Kimi K3, GPT, and more to improve complex professional workflows in one centralized workspace.

Compare leading AI models

Evaluate Claude Opus 5 alongside Fable, Sonnet, GPT, Gemini, Kimi, Grok, GLM, and Meta models through one interface.

Use one workspace for advanced work

Move between coding, research, planning, analysis, and knowledge work without scattering projects across separate tools.

Match the model to the task

Switch based on reasoning depth, price, speed, or workflow complexity.

Keep project context organized

Centralize prompt history and ongoing work so important instructions and decisions remain easier to find.

Get more value from premium intelligence

Use a high-end model positioned to deliver stronger cost-per-task economics than more expensive flagship options.

Understand the Claude Opus 5 Model's Context Window, Pricing, and More

01

MODEL TYPE

  • Anthropic’s premium Opus model for coding, reasoning, knowledge work, and agentic execution
  • Positioned as a practical frontier-level option for frequent professional use
  • Designed to combine high intelligence with more efficient task economics
02

CONTEXT WINDOW AND OUTPUT

  • Supports a context window of up to 1 million tokens according to the supplied analysis
  • Supports outputs of up to 128,000 tokens
  • Built for large repositories, extensive document sets, long conversations, and multi-stage projects
  • Improved context stability is intended to preserve reasoning quality throughout extended sessions
03

MODALITIES

  • Accepts text and image inputs
  • Produces text outputs
  • Can interpret screenshots, diagrams, interfaces, and technical visuals
  • Supports visual verification workflows, such as reviewing layouts and identifying hidden interface elements
04

REASONING AND AGENTIC EXECUTION

  • Uses configurable Low, Medium, High, X-high, and Max effort settings
  • High is positioned as the default balanced reasoning level
  • Higher effort settings allocate more test-time compute to complex problems
  • Built to iterate, use tools, recover from failures, and continue toward task completion
  • Supports multi-agent and writer-verifier workflows
05

CLAUDE OPUS 5 PRICING AND EFFICIENCY

  • Base API pricing in the supplied analysis is $5 per million input tokens and $25 per million output tokens
  • Fast Mode is listed at $10 per million input tokens and $50 per million output tokens
  • Fast Mode is described as providing up to 2.5 times faster performance through the Claude API
  • Prompt caching can reduce repeated-context costs, with the source listing a 90% discount for cache hits
06

LIMITS AND CONSIDERATIONS

  • Claude Opus 5 remains a premium proprietary AI model
  • The supplied assessment reports a higher hallucination rate than Opus 4.8, making verification important for consequential work
  • Complex concurrency and race-condition problems can still produce errors
  • Some restricted requests may pass through Anthropic’s safety or fallback systems
  • The model is positioned below Mythos 5 for specialized offensive cybersecurity and biological research

Try Claude Opus 5 to Simplify Complex Work, Research, and Product Development

Repository analysis and refactoring for software engineers

Debug failures, evaluate architecture, plan migrations, and produce tested changes across large or interconnected codebases.

ClaudeTry this prompt
"

Analyze this repository, identify its highest-risk architecture issue, implement the safest, most valuable fix, and add focused regression tests.

"

Evidence synthesis and decision support for research analysts

Compare long reports, inspect conflicting evidence, and turn complex material into concise conclusions that support real decisions.

ClaudeTry this prompt
"

Compare these reports, identify conflicting evidence, and write a decision memo covering market risks, opportunities, assumptions, and recommendations.

"

Roadmap creation and prioritization for product managers

Convert research, stakeholder notes, product data, and more into clearer priorities and implementation requirements.

ClaudeTry this prompt
"

Turn these sprint notes and customer requests into a prioritized roadmap with rationale, dependencies, milestones, and success metrics.

"

Process improvement and automation for operations leaders

Find workflow delays, clarify ownership, design automations, and produce practical plans for improving performance across connected business systems.

ClaudeTry this prompt
"

Review these process notes and metrics, identify the three largest bottlenecks, and create an owner-based improvement plan.

"

Strategic analysis for consultants and knowledge workers

Build executive summaries, scenario analyses, operating recommendations, and structured deliverables from dense or incomplete source material.

ClaudeTry this prompt
"

Analyze these materials, compare the available strategic options, and recommend the strongest choice with risks, assumptions, and tradeoffs

"

Reliable agent workflows for AI builders

Design multi-step assistants that use tools, verify intermediate results, recover from errors, and return structured implementation-ready outputs.

ClaudeTry this prompt
"

Complete this multi-step workflow, verify each stage against the source data, correct inconsistencies, and produce a final implementation plan.

"

Claude Opus 5 Chat vs. GPT-5.6 and Other Top LLMs

Analyze Opus 5 with other AI models found on Lorka AI, such as GLM 5.2, Sonnet 5, and more, in the table below.

Legend:
💡Reasoning
Speed
🤖Multimodality
🧠Context
(1: Poor – 5: Very good)
Claude

Claude Opus 5

Reasoning
💡💡💡💡💡
Speed
Multimodality
🤖🤖🤖🤖🤖
Context
🧠🧠🧠🧠🧠
Ideal Use Cases

Complex programming, high-level logical reasoning, enterprise due diligence, and long-horizon agentic workflows.

Claude

Claude Fable 5

Reasoning
💡💡💡💡💡
Speed
Multimodality
🤖🤖🤖🤖🤖
Context
🧠🧠🧠🧠🧠
Ideal Use Cases

Deep analytical research, advanced reasoning capabilities, and complex codebase architecture.

Claude

Claude Sonnet 5

Reasoning
💡💡💡💡💡
Speed
Multimodality
🤖🤖🤖🤖🤖
Context
🧠🧠🧠🧠🧠
Ideal Use Cases

High-ROI automated programming, strategic planning, and optimized professional workflows.

Grok

Grok 4.5

Reasoning
💡💡💡💡💡
Speed
Multimodality
🤖🤖🤖🤖🤖
Context
🧠🧠🧠🧠🧠
Ideal Use Cases

Faster automated programming, technical troubleshooting, document generation, and tool-driven workflow optimization.

Gemini

Gemini 3.6 Flash

Reasoning
💡💡💡💡💡
Speed
Multimodality
🤖🤖🤖🤖🤖
Context
🧠🧠🧠🧠🧠
Ideal Use Cases

Advanced coding, multimodal execution, and agentic workflows

OpenAI

GPT-5.6 Sol

Reasoning
💡💡💡💡💡
Speed
Multimodality
🤖🤖🤖🤖🤖
Context
🧠🧠🧠🧠🧠
Ideal Use Cases

Autonomous agents, sophisticated programming, digital defense, and biotechnological workflows.

Z.ai

GLM-5.2

Reasoning
💡💡💡💡💡
Speed
Multimodality
🤖🤖🤖🤖🤖
Context
🧠🧠🧠🧠🧠
Ideal Use Cases

Autonomous project execution, system automation, codebase refactoring, and advancing deep open-weight model development.

Kimi

Kimi K3

Reasoning
💡💡💡💡💡
Speed
Multimodality
🤖🤖🤖🤖🤖
Context
🧠🧠🧠🧠🧠
Ideal Use Cases

Visual and UI design, extensive repository engineering, systemic analysis, and multi-phase agent workflows.

MetaAI

Muse Spark 1.1

Reasoning
💡💡💡💡💡
Speed
Multimodality
🤖🤖🤖🤖🤖
Context
🧠🧠🧠🧠🧠
Ideal Use Cases

Agentic computer utilization and multimodal reasoning

Strengths and Weaknesses of Claude Opus 5 and Other AI Models

Claude

Claude Opus 5

Strengths

Near-Fable intelligence for coding, reasoning, and agentic work at roughly half the price.

Limitations

Premium and proprietary, while still trailing Fable 5 in frontier cyber and biology tasks.

Claude

Claude Fable 5

Strengths

Mythos-class public model for elite long-horizon reasoning, coding, and demanding public-facing tasks.

Limitations

Higher costs, stronger safeguards, and frequent interventions reduce practicality for everyday use.

Claude

Claude Sonnet 5

Strengths

Balances speed, price, and agentic coding performance for everyday professional workflows.

Limitations

Falls behind Opus 5 and Fable 5 on demanding reasoning and long-horizon tasks.

OpenAI

GPT-5.6 Sol

Strengths

Excels at deep reasoning, advanced coding, and specialized cyber and scientific workflows.

Limitations

Preview access and tighter safeguards limit availability and flexibility for some teams.

Gemini

Gemini 3.6 Flash

Strengths

Fast multimodal model combining strong coding, reasoning, high throughput, and lower cost.

Limitations

Not Google’s Pro-tier flagship and less suited to the hardest reasoning tasks.

Z.ai

GLM-5.2

Strengths

Open-weight long-horizon model with 1M context and attractive self-hosting potential.

Limitations

Text-only, with less mature tooling and ecosystem support than proprietary platforms.

Grok

Grok 4.5

Strengths

Fast, lower-cost frontier model for coding, STEM, and agentic technical tasks.

Limitations

Smaller context, text-only focus, and regional rollout gaps reduce multimodal flexibility.

How to Chat With Claude Opus 5 on Lorka

Try Opus 5on Lorka with other AI models like GLM 5.2, Kimi K3, and more.

1. Select Opus 5

Access the model dropdown list and choose Claude Opus 5.

2. Enter your prompt

Type in instructions to begin your chat. Attach a PDF or media for more context.

3. Get your output

Claude will answer in seconds to begin your workflow.

Chat With Claude Opus 5 Today

Access Claude Opus 5 on Lorka now. Create an account and start a multi-LLM workflow with Opus, GPT, and more.

Claude Opus 5 FAQs

You can access Claude Opus 5 through Claude Pro, Claude Max, Anthropic's API, and supported cloud platforms. However, on Lorka AI, simply select Claude Opus 5 from the available models and start chatting in your browser. You can also use other strong AI models like DeepSeek, Kimi, and more under a single $19.99/month plan.