Claude Opus 4.7 vs o4-mini
Claude Opus 4.7 vs o4-mini: o4-mini is cheaper for input-heavy usage ($1.10/M vs $5.00/M input tokens), while o4-mini is better for long-context tasks (2,000,000 tokens).
Direct answer: choose o4-mini for lower token spend and choose o4-mini when your workload needs longer context.
Common pricing searches covered on this page: Claude Opus 4.7 vs o4-mini • Claude Opus 4.7 vs o4-mini pricing • Claude Opus 4.7 vs o4-mini API pricing and opus 4 7 vs o4 mini pricing.
Cost Comparison (1000 input + 500 output tokens, 100 requests/day)
Claude Opus 4.7
o4-mini
Cost Differences
o4-mini costs less than Claude Opus 4.7
Quick Recommendation
Winner for direct API pricing: o4-mini. At the default workload, o4-mini saves about $42.60/month ($518.30/year) versus Claude Opus 4.7.
Feature Comparison
| Feature | Claude Opus 4.7 | o4-mini |
|---|---|---|
| Provider | Anthropic | OpenAI |
| Input Price | $5.00/1M tokens | $1.10/1M tokens |
| Output Price | $25.00/1M tokens | $4.40/1M tokens |
| Context Window | 1,000,000 tokens | 2,000,000 tokens |
| Max Output | 128,000 tokens | 131,072 tokens |
| Category | flagship | reasoning |
| Capabilities | textvisionreasoningcode | textreasoningcode |
| Release Date | 4/16/2026 | 4/16/2025 |
Claude Opus 4.7 vs o4-mini: Which Should You Choose?
Choosing between Claude Opus 4.7 and o4-mini depends on your priorities: cost efficiency, context length, or raw capability. o4-mini is the more affordable option at $1.10/1M input tokens — 78% cheaper than Claude Opus 4.7. Meanwhile, o4-mini offers a significantly larger context window at 2,000,000 tokens vs 1,000,000 for Claude Opus 4.7.
These models come from different providers — Anthropic and OpenAI — which means different API ecosystems, SDKs, rate limits, and terms of service. If you're already integrated with Anthropic, switching to OpenAIinvolves migration effort beyond just pricing. Factor in your existing infrastructure when deciding.
These models target different tiers: Claude Opus 4.7 is a flagship model while o4-mini is reasoning. This means they're optimized for different workloads. Claude Opus 4.7 is built for complex tasks that require deeper reasoning, while o4-mini offers better value for routine operations.
Output costs matter too. Claude Opus 4.7 charges $25.00/1M output tokens vs $4.40 for o4-mini. For generation-heavy workloads (content creation, code generation, summarization), output pricing often dominates your bill. o4-mini has the edge here at $4.40/1M output tokens.
Multimodal capabilities: Claude Opus 4.7 supports vision (image inputs) while o4-mini is text-only. If your application needs image understanding, this narrows your choice.
Best Use Cases
Choose Claude Opus 4.7 when:
- • You need more capabilities (vision)
- • You're already using Anthropic's API ecosystem
Choose o4-mini when:
- • Budget is a primary concern
- • You need a larger context window (2,000,000 tokens)
- • You need longer outputs (up to 131,072 tokens)
- • You're already using OpenAI's API ecosystem
Pros and Caveats at a Glance
Claude Opus 4.7
- • Input pricing: $5.00/M tokens
- • Output pricing: $25.00/M tokens
- • Context window: 1,000,000 tokens
- • Max output: 128,000 tokens
Watch out for
- • Higher input cost than o4-mini
- • Higher output cost than o4-mini
- • Smaller context window than o4-mini
o4-mini
- • Input pricing: $1.10/M tokens
- • Output pricing: $4.40/M tokens
- • Context window: 2,000,000 tokens
- • Max output: 131,072 tokens
Watch out for
- • Trade-offs are minor in this matchup.
Try Different Scenarios
Use the calculator below to see how costs change with different usage patterns
Claude Opus 4.7 (Anthropic)
o4-mini (OpenAI)
Start using Claude Opus 4.7 today
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Sign Up for OpenAI →Frequently Asked Questions
Which is cheaper, Claude Opus 4.7 or o4-mini?▼
What is the context window difference between Claude Opus 4.7 and o4-mini?▼
Which model is better for AI Agent / Agentic Workflows?▼
Which model has better overall pricing for heavy usage?▼
Where can I compare Anthropic and OpenAI API pricing beyond this model matchup?▼
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