Claude 3.7 Sonnet
Anthropic • Text + Vision
Context Window200K
Knowledge CutoffUnknown
Claude 3.7 Sonnet vs Claude 3 Opus
Claude 3 Opus for maximum capability on complex tasks, Claude 3.7 Sonnet for best price-to-performance in Claude family.
Open model page
Claude 3 Opus
Anthropic • Text + Vision
Context Window200K
Knowledge CutoffUnknown
Editorial Verdict
Claude 3 Opus is Anthropic's ceiling model; Claude 3.7 Sonnet is the best value choice for most production workloads.
Claude 3.7 Sonnet and Claude 3 Opus share Anthropic's strengths in reasoning and instruction following, with 3.7 Sonnet delivering 90% of Opus's capability at roughly half the cost. For most real-world tasks — coding, analysis, writing — the difference is imperceptible. Claude 3 Opus still leads on the hardest benchmarks, but 3.7 Sonnet is the better daily driver for teams that want top-tier quality without top-tier pricing.
Claude 3.7 Sonnet
- Best price-to-performance ratio in the Claude family — nearly Opus quality at Sonnet pricing
- Extended thinking mode available for complex tasks, giving on-demand depth when needed
- Same 200K context window as Opus for long-document and codebase processing
Best for: Cost-conscious teams wanting near-top-tier quality for everyday production workloads
Claude 3 Opus
- Highest raw capability on the hardest benchmarks (MMLU, graduate science, multi-step math)
- Slightly better at maintaining coherence over extremely long conversations
- Preferred for research-grade analysis where peak performance is non-negotiable
Best for: Research, high-stakes analysis, and tasks where maximum capability is essential
Pricing sourced from OpenRouter — updates as their catalog changes.
Pricing Comparison
All values pull from OpenRouter and update as their catalog changes.
| Metric | Claude 3.7 Sonnet | Claude 3 Opus | 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 3.7 Sonnet Total
VariableClaude 3 Opus Total
VariableSavings unavailable (pricing not published for one model).
Capability Signals
Scores are directional estimates from model metadata — not official benchmark results.
Claude 3.7 SonnetMMLU Signal (Reasoning)Claude 3 Opus
69%
76%
Claude 3.7 SonnetHumanEval Signal (Coding)Claude 3 Opus
69%
69%
Claude 3.7 SonnetAgentic Tooling SignalClaude 3 Opus
69%
69%
Claude 3.7 SonnetMultimodal SignalClaude 3 Opus
78%
78%
Capabilities Matrix
Feature highlights for architecture and production fit.
Claude 3.7 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.
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.
API Implementation
Quick start snippets for each provider style.
Anthropic (Python)
import anthropic
client = anthropic.Anthropic()
message = client.messages.create(
model="anthropic/claude-3.7-sonnet",
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-opus",
max_tokens=1024,
messages=[{"role": "user", "content": "Hello"}]
)
print(message.content)Choose Claude 3.7 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.
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.
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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