Claude Opus 5 (Low)

Claude Opus 5 (Low)

Anthropic • text#76 of 704 in intelligence

Data source: Artificial Analysis · ID AA: 20928ba9-3a3f-415f-9519-b84ff64ecf34 · Snapshot published: 10/27/2026, 6:00:26 PM · Methodology version: 4.3

API Available

Specifications

AA Intelligence Index

39.4

Artificial Analysis · 4.3 · 10/27/2026, 6:00:26 PM

Context Window

—

Input Price/1M

$5.00

#403 of 445

Output Price/1M

$25.00

Parameters

—

Cost per Task

$1.0983

USD / task · lower is better · Artificial Analysis · 4.3 · 10/27/2026, 6:00:26 PM

Benchmarks

Artificial Analysis metrics for Claude Opus 5 (Low). Higher is better for capability indexes; lower is better for cost per task.

Agentic

BenchmarkScoreMaximumMethodologySource / version / date
AA Agentic Index36.0100.0Artificial Analysis official APIArtificial Analysis · 4.3 · 10/27/2026

Coding

BenchmarkScoreMaximumMethodologySource / version / date
AA Coding Index66.9100.0Artificial Analysis official APIArtificial Analysis · 4.3 · 10/27/2026

Cost

BenchmarkScoreMaximumMethodologySource / version / date
AA Cost Per Task1.1100.0Artificial Analysis official APIArtificial Analysis · 4.3 · 10/27/2026

overall

BenchmarkScoreMaximumMethodologySource / version / date
AA Intelligence Index39.4100.0Artificial Analysis official APIArtificial Analysis · 4.3 · 10/27/2026

Information

Release date
July 24, 2026
Tool Calling
❌ Not supported
Vision
❌ Not supported
Audio
❌ Not supported

Full Analysis: Claude Opus 5 (Low)

What is Claude Opus 5 (Low)?

Claude Opus 5 (Low) is an AI model developed by Anthropic, classified as a text model. It focuses on text processing and natural language generation. As a proprietary model, it is available via Anthropic's cloud API.

Pricing & Costs in 2026

Claude Opus 5 (Low) is usage-based, priced at $5/1M input tokens and $25/1M output tokens. For context: 1 million tokens is approximately 750,000 words, or about 10 average-length books. The mid-range pricing balances quality and cost for most professional applications.

Benchmarks & Performance

Claude Opus 5 (Low) was evaluated on 4 different benchmarks, covering categories like Agentic, Coding, Cost, overall. Results show moderate performance across available evaluations.

It's important to note that benchmarks measure specific aspects and don't capture the full user experience. Factors like instruction adherence, behavior in long conversations, and real-world task quality vary significantly between models and aren't always reflected in standard scores.

Recommended Use Cases

Claude Opus 5 (Low) specializes in text, offering advanced capabilities for creating and processing text content.

Comparison with Alternatives

In the 2026 AI model ecosystem, Claude Opus 5 (Low) competes directly with similarly capable models. Key competitors include GPT (OpenAI), Gemini (Google), and open source models like Llama (Meta) and DeepSeek. The choice between models depends on the specific use case, budget, latency requirements, and need for features like multimodality and tool calling.

For a detailed side-by-side comparison, use our comparison tool or check the overall model ranking.

Frequently Asked Questions

What is Claude Opus 5 (Low)?

Claude Opus 5 (Low) is an AI model developed by Anthropic. It is a text model.

How much does Claude Opus 5 (Low) cost?

Claude Opus 5 (Low) costs $5/1M input tokens and $25/1M output tokens. For heavy usage (e.g., a chatbot handling 100k messages/month), costs can range from $10 to $1,000 depending on volume.

How does Claude Opus 5 (Low) compare with other models?

In available benchmarks, Claude Opus 5 (Low) scored: AA Agentic Index: 36/100, AA Coding Index: 66.9/100, AA Cost Per Task: 1.0983/100. See the full table above for a detailed comparison.

Is Claude Opus 5 (Low) open source?

No, Claude Opus 5 (Low) is a proprietary model from Anthropic. It is available via cloud API. For open source alternatives, check our open source model ranking.

What is Claude Opus 5 (Low) best for?

Claude Opus 5 (Low) excels at general-purpose language tasks.

Last updated: October 27, 2026 • View methodology →