Claude Haiku 4.5 vs o4-mini Deep Research
Claude Haiku 4.5 vs o4-mini Deep Research: Claude Haiku 4.5 is cheaper for input-heavy usage ($1.00/M vs $2.00/M input tokens), while Claude Haiku 4.5 is better for long-context tasks (200,000 tokens).
Direct answer: choose Claude Haiku 4.5 for lower token spend and choose Claude Haiku 4.5 when your workload needs longer context.
Compare input and output token pricing, context windows, and monthly cost estimates on one page so you can pick the cheaper model fast.
Cost Comparison (1000 input + 500 output tokens, 100 requests/day)
Claude Haiku 4.5
o4-mini Deep Research
Cost Differences
o4-mini Deep Research costs more than Claude Haiku 4.5
Quick Recommendation
Winner for direct API pricing: Claude Haiku 4.5. At the default workload, Claude Haiku 4.5 saves about $7.50/month ($91.25/year) versus o4-mini Deep Research.
Feature Comparison
| Feature | Claude Haiku 4.5 | o4-mini Deep Research |
|---|---|---|
| Provider | Anthropic | OpenAI |
| Input Price | $1.00/1M tokens | $2.00/1M tokens |
| Output Price | $5.00/1M tokens | $8.00/1M tokens |
| Context Window | 200,000 tokens | 200,000 tokens |
| Max Output | 64,000 tokens | 32,768 tokens |
| Category | efficient | reasoning |
| Capabilities | textvision | textreasoningcode |
| Release Date | 10/15/2025 | 6/26/2025 |
Claude Haiku 4.5 vs o4-mini Deep Research: Which Should You Choose?
Choosing between Claude Haiku 4.5 and o4-mini Deep Research depends on your priorities: cost efficiency, context length, or raw capability. Claude Haiku 4.5 is the more affordable option at $1.00/1M input tokens — 50% cheaper than o4-mini Deep Research.
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 Haiku 4.5 is a efficient model while o4-mini Deep Research is reasoning. This means they're optimized for different workloads. o4-mini Deep Research targets more demanding workloads, while Claude Haiku 4.5 provides a cost-effective option for everyday tasks.
Output costs matter too. Claude Haiku 4.5 charges $5.00/1M output tokens vs $8.00 for o4-mini Deep Research. For generation-heavy workloads (content creation, code generation, summarization), output pricing often dominates your bill. Claude Haiku 4.5 has the edge here at $5.00/1M output tokens.
Multimodal capabilities: Claude Haiku 4.5 supports vision (image inputs) while o4-mini Deep Research is text-only. If your application needs image understanding, this narrows your choice.
Best Use Cases
Choose Claude Haiku 4.5 when:
- • Budget is a primary concern
- • You need longer outputs (up to 64,000 tokens)
- • You're already using Anthropic's API ecosystem
- • You're running high-volume, latency-sensitive workloads
Choose o4-mini Deep Research when:
- • You need more capabilities (reasoning, code)
- • You're already using OpenAI's API ecosystem
Pros and Caveats at a Glance
Claude Haiku 4.5
- • Input pricing: $1.00/M tokens
- • Output pricing: $5.00/M tokens
- • Context window: 200,000 tokens
- • Max output: 64,000 tokens
Watch out for
- • Trade-offs are minor in this matchup.
o4-mini Deep Research
- • Input pricing: $2.00/M tokens
- • Output pricing: $8.00/M tokens
- • Context window: 200,000 tokens
- • Max output: 32,768 tokens
Watch out for
- • Higher input cost than Claude Haiku 4.5
- • Higher output cost than Claude Haiku 4.5
Try Different Scenarios
Use the calculator below to see how costs change with different usage patterns
Claude Haiku 4.5 (Anthropic)
o4-mini Deep Research (OpenAI)
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Which is cheaper, Claude Haiku 4.5 or o4-mini Deep Research?▼
What is the context window difference between Claude Haiku 4.5 and o4-mini Deep Research?▼
Which model is better for AI Chatbot?▼
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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