Claude 3 Opus
Anthropic • Text + Vision
Context Window200K
Knowledge CutoffUnknown
Claude 3 Opus vs Claude 3.5 Sonnet
Claude 3 Opus for highest-tier reasoning tasks, Claude 3.5 Sonnet for best value in the Claude family.
Open model page
Claude 3.5 Sonnet
Anthropic • Text + Vision
Context Window200K
Knowledge CutoffUnknown
Editorial Verdict
Claude 3 Opus is Anthropic's ceiling model; Claude 3.5 Sonnet is the best value for most production tasks.
Claude 3 Opus is Anthropic's highest capability model; Claude 3.5 Sonnet is their best value model with nearly the same capability on most tasks. For maximum quality on the hardest tasks, Claude 3 Opus wins. For everyday production workloads where quality is high but cost matters, Claude 3.5 Sonnet wins.
Claude 3 Opus
- Highest benchmark scores on the most complex reasoning and analysis tasks
- Better at maintaining coherence over extremely long conversations
- Preferred for research-grade analysis and high-stakes decision support
Best for: Research-grade analysis and maximum quality on the hardest tasks
Claude 3.5 Sonnet
- Nearly the same quality as Opus on most tasks at significantly lower cost
- Faster inference with better price-to-performance ratio
- Extended thinking mode available for complex tasks when needed
Best for: Cost-conscious production applications and everyday high-quality workloads
Pricing sourced from OpenRouter — updates as their catalog changes.
Pricing Comparison
All values pull from OpenRouter and update as their catalog changes.
| Metric | Claude 3 Opus | Claude 3.5 Sonnet | Winner |
|---|---|---|---|
| Input (per 1M tokens) | Custom | Custom | N/A |
| Output (per 1M tokens) | Custom | Custom | N/A |
| Request fee | N/A | N/A | N/A |
| Image fee | N/A | N/A | N/A |
Cost Estimator
Estimate monthly billing using real OpenRouter prices.
Claude 3 Opus Total
VariableClaude 3.5 Sonnet Total
VariableSavings unavailable (pricing not published for one model).
Capability Signals
Scores are directional estimates from model metadata — not official benchmark results.
Claude 3 OpusMMLU Signal (Reasoning)Claude 3.5 Sonnet
76%
69%
Claude 3 OpusHumanEval Signal (Coding)Claude 3.5 Sonnet
69%
69%
Claude 3 OpusAgentic Tooling SignalClaude 3.5 Sonnet
69%
69%
Claude 3 OpusMultimodal SignalClaude 3.5 Sonnet
78%
78%
Capabilities Matrix
Feature highlights for architecture and production fit.
Claude 3 Opus Strengths
- Supports image inputs for multimodal analysis workflows.
- Large context window for long documents and codebases.
- Balanced general-purpose profile for chat, extraction, and automation tasks.
Claude 3.5 Sonnet Strengths
- Supports image inputs for multimodal analysis workflows.
- Large context window for long documents and codebases.
- Balanced general-purpose profile for chat, extraction, and automation tasks.
API Implementation
Quick start snippets for each provider style.
Anthropic (Python)
import anthropic
client = anthropic.Anthropic()
message = client.messages.create(
model="anthropic/claude-3-opus",
max_tokens=1024,
messages=[{"role": "user", "content": "Hello"}]
)
print(message.content)Anthropic (Python)
import anthropic
client = anthropic.Anthropic()
message = client.messages.create(
model="anthropic/claude-3.5-sonnet",
max_tokens=1024,
messages=[{"role": "user", "content": "Hello"}]
)
print(message.content)Choose Claude 3 Opus when...
- Your application includes visual reasoning and image understanding tasks.
- You process large documents or code repositories in a single prompt.
- You want a balanced default for mixed chat and workflow automation workloads.
Choose Claude 3.5 Sonnet when...
- Your application includes visual reasoning and image understanding tasks.
- You process large documents or code repositories in a single prompt.
- You want a balanced default for mixed chat and workflow automation workloads.
Frequently Asked Questions
Practical checks before selecting a production model.
Which model is better for coding?
Coding preference depends on your stack and tool-calling needs. Compare the coding signal row, test with your repository tasks, and validate latency in your target region.
Which model is cheaper at scale?
Input and output token pricing can diverge by workload profile. Use the estimator with your monthly request count and token mix to get a realistic cost difference.
Are these official benchmark numbers?
Pricing is live from OpenRouter. Benchmark rows are ModelsAtlas metadata-based signals and should be treated as directional guidance, not official leaderboard scores.
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