GPT-5.6 Luna vs o4-mini Deep Research
Pricing verdict: GPT-5.6 Luna vs o4-mini Deep Research: GPT-5.6 Luna is cheaper for input-heavy usage ($1.00/M vs $2.00/M input tokens), while GPT-5.6 Luna is better for long-context tasks (1,050,000 tokens).
Direct answer: choose GPT-5.6 Luna for lower token spend and choose GPT-5.6 Luna when your workload needs longer context.
Compare API pricing, input and output token costs, context windows, and monthly estimates on one page so you can pick the right model fast.
Cost Comparison (1000 input + 500 output tokens, 100 requests/day)
GPT-5.6 Luna
o4-mini Deep Research
Cost Differences
o4-mini Deep Research costs more than GPT-5.6 Luna
Quick Recommendation
Winner for direct API pricing: GPT-5.6 Luna. At the default workload, GPT-5.6 Luna saves about $6.00/month ($73.00/year) versus o4-mini Deep Research.
Feature Comparison
| Feature | GPT-5.6 Luna | o4-mini Deep Research |
|---|---|---|
| Provider | OpenAI | OpenAI |
| Input Price | $1.00/1M tokens | $2.00/1M tokens |
| Output Price | $6.00/1M tokens | $8.00/1M tokens |
| Context Window | 1,050,000 tokens | 200,000 tokens |
| Max Output | 128,000 tokens | 32,768 tokens |
| Category | efficient | reasoning |
| Capabilities | textvisioncodereasoning | textreasoningcode |
| Release Date | 6/26/2026 | 6/26/2025 |
GPT-5.6 Luna vs o4-mini Deep Research: Which Should You Choose?
Choosing between GPT-5.6 Luna and o4-mini Deep Research depends on your priorities: cost efficiency, context length, or raw capability. GPT-5.6 Luna is the more affordable option at $1.00/1M input tokens — 50% cheaper than o4-mini Deep Research. Meanwhile, GPT-5.6 Luna offers a significantly larger context window at 1,050,000 tokens vs 200,000 for o4-mini Deep Research.
These models target different tiers: GPT-5.6 Luna 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 GPT-5.6 Luna provides a cost-effective option for everyday tasks.
Output costs matter too. GPT-5.6 Luna charges $6.00/1M 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. GPT-5.6 Luna has the edge here at $6.00/1M output tokens.
Multimodal capabilities: GPT-5.6 Luna 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 GPT-5.6 Luna when:
- • Budget is a primary concern
- • You need a larger context window (1,050,000 tokens)
- • You need more capabilities (vision)
- • You need longer outputs (up to 128,000 tokens)
- • You're already using OpenAI's API ecosystem
- • You're running high-volume, latency-sensitive workloads
Choose o4-mini Deep Research when:
- • You're already using OpenAI's API ecosystem
Pros and Caveats at a Glance
GPT-5.6 Luna
- • Input pricing: $1.00/M tokens
- • Output pricing: $6.00/M tokens
- • Context window: 1,050,000 tokens
- • Max output: 128,000 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 GPT-5.6 Luna
- • Higher output cost than GPT-5.6 Luna
- • Smaller context window than GPT-5.6 Luna
Try Different Scenarios
Use the calculator below to see how costs change with different usage patterns
GPT-5.6 Luna (OpenAI)
o4-mini Deep Research (OpenAI)
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