o3-mini
OpenAI • Reasoning
Context Window200K
Knowledge CutoffUnknown
o3-mini vs Claude 3.7 Sonnet
Claude 3.7 Sonnet for broader task coverage and tool use, o3-mini for structured reasoning under a cost ceiling.
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Claude 3.7 Sonnet
Anthropic • Text + Vision
Context Window200K
Knowledge CutoffUnknown
Editorial Verdict
o3-mini is optimized for hard reasoning; Claude 3.7 Sonnet is optimized for general-purpose production tasks.
o3-mini and Claude 3.7 Sonnet serve different primary purposes — o3-mini is a reasoning model for hard problems; Claude 3.7 Sonnet is a general-purpose coding and analysis specialist. For hard math and science reasoning, o3-mini wins. For coding, instruction following, and general-purpose tasks, Claude 3.7 Sonnet wins. Many teams benefit from using both.
o3-mini
- Superior performance on hard math, science, and competitive programming
- Configurable reasoning depth for task-appropriate inference cost
- Fast inference for a reasoning model — better latency than o1
Best for: Hard math, science, and competitive programming tasks requiring reasoning depth
Claude 3.7 Sonnet
- Versatile general-purpose model — best-in-class coding and instruction following
- Extended thinking mode for complex reasoning when needed
- 200K context and mature API for production applications
Best for: General-purpose coding, analysis, and production applications
Pricing sourced from OpenRouter — updates as their catalog changes.
Pricing Comparison
All values pull from OpenRouter and update as their catalog changes.
| Metric | o3-mini | Claude 3.7 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.
o3-mini Total
VariableClaude 3.7 Sonnet Total
VariableSavings unavailable (pricing not published for one model).
Capability Signals
Scores are directional estimates from model metadata — not official benchmark results.
o3-miniMMLU Signal (Reasoning)Claude 3.7 Sonnet
76%
69%
o3-miniHumanEval Signal (Coding)Claude 3.7 Sonnet
69%
69%
o3-miniAgentic Tooling SignalClaude 3.7 Sonnet
69%
69%
o3-miniMultimodal SignalClaude 3.7 Sonnet
69%
78%
Capabilities Matrix
Feature highlights for architecture and production fit.
o3-mini Strengths
- Large context window for long documents and codebases.
- Balanced general-purpose profile for chat, extraction, and automation tasks.
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.
API Implementation
Quick start snippets for each provider style.
OpenAI (Python)
from openai import OpenAI
client = OpenAI()
response = client.chat.completions.create(
model="openai/o3-mini",
messages=[{"role": "user", "content": "Hello"}]
)
print(response.choices[0].message.content)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)Choose o3-mini when...
- You process large documents or code repositories in a single prompt.
- You want a balanced default for mixed chat and workflow automation workloads.
- You can measure quality with your own benchmark and prompt set.
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.
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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