LLManthropicPlan: Pro and up

Claude Opus 5

Claude Opus 5 is Anthropic’s flagship model for demanding reasoning, coding, and long-horizon agentic work. It is particularly strong at end-to-end software tasks, code review and bug finding, visual analysis...

Anyone in the Project can @-mention Claude Opus 5 with the team's shared context - pooled credits, one chat, one memory.

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Verdict

Claude Opus 5 is Anthropic's flagship reasoning model with a million-token context window and strong multimodal capabilities across text, images, and files. At $5 input / $25 output per Mtok, it sits at the premium end of pricing — roughly 2.5× more expensive than GPT-4o for output tokens. Reach for this when you need deep reasoning over massive documents or complex multimodal tasks where cost takes a back seat to quality. For routine work, Claude Sonnet 4.5 delivers better value.

Best for

Deep reasoning over 500k+ token documents
Complex multimodal analysis with images and files
High-stakes tasks where accuracy justifies premium cost
Long-context legal or technical document review

Strengths

The million-token context window handles entire codebases, book-length documents, or multi-file analysis in a single pass. Multimodal support extends beyond images to structured file formats, making it useful for parsing PDFs, spreadsheets, or mixed-media reports. Anthropic's Constitutional AI training typically yields strong instruction-following and nuanced reasoning on ambiguous prompts, though public benchmarks for Opus 5 specifically aren't yet available.

Trade-offs

Output pricing at $25 per Mtok makes this the most expensive mainstream model for generation-heavy workflows — a 10k-token response costs $0.25 versus $0.10 on GPT-4o. Without published benchmarks, it's hard to quantify where Opus 5 outperforms Sonnet 4.5 enough to justify the 5× cost difference. For most teams, Sonnet 4.5 hits the sweet spot of capability and price; reserve Opus 5 for the 10% of tasks where you genuinely need the extra horsepower.

Specifications

Provider: anthropic
Category: llm
Context length: 1,000,000 tokens
Max output: 128,000 tokens
Modalities: text, image, file
License: proprietary
Released: 2026-07-24

Pricing

Input: $5.00/Mtok
Output: $25.00/Mtok
Model ID: anthropic/claude-opus-5

Per-token prices show what the model costs upstream. On Switchy your team draws from one shared org credit pool - one plan, one balance for everyone.

Team cost calculator

Seats5 peopleMessages / seat / day80Avg turn size2 ktokOutput share30 %

Estimated monthly spend

$193.60

17.6M tokens / month
5 seats · 80 msgs/day

Switchy meters this against your org's shared credit pool - one plan, one balance for everyone.

Providers

Provider-level routing data is not available yet for this model.

Performance

Performance snapshots are collected daily. Check back after the next ingestion run.

Benchmarks

Public benchmark scores are not available yet for this model. Check back after the next ingestion run.

Works well with

Top MCPs

Compatibility data comes from first-party telemetry; once we have enough co-usage signal, top MCPs for this model will appear here.

How Switchy teams use it

Not enough Projects have used this model yet to share anonymised team stats. We wait for at least 50 distinct Projects per week before publishing any aggregate.

Starter prompts

Multi-Document Legal Analysis

I'm uploading three contracts (attached). Identify any conflicting clauses across all three documents, then summarize the key obligations for Party A in each. Highlight discrepancies in termination terms.

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Codebase Architecture Review

Here's a compressed archive of our Python backend (attached). Map out the dependency graph between modules, identify circular imports, and propose a refactoring plan to improve modularity.

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Financial Report Deep Dive

Attached is our Q4 earnings report (PDF). Extract revenue by segment, compare YoY growth rates, and flag any footnotes that materially affect the headline numbers. Present findings in a table.

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Multimodal Research Synthesis

I'm attaching two research papers and three figures from a third source. Synthesize the consensus view on X, note where the papers disagree, and explain what the figures add to the argument.

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Complex Scenario Planning

Our company is considering three M&A targets. For each, model the integration risks, synergy potential, and regulatory hurdles. Rank them by strategic fit and explain your reasoning in detail.

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