GPT-5.3 Codex vs GPT-5.6 Luna
Pricing verdict: GPT-5.3 Codex vs GPT-5.6 Luna: GPT-5.6 Luna is cheaper for input-heavy usage ($1.00/M vs $1.75/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-5.3 Codex
GPT-5.6 Luna
Cost Differences
GPT-5.6 Luna costs less than GPT-5.3 Codex
Quick Recommendation
Winner for direct API pricing: GPT-5.6 Luna. At the default workload, GPT-5.6 Luna saves about $14.25/month ($173.375/year) versus GPT-5.3 Codex.
Feature Comparison
| Feature | GPT-5.3 Codex | GPT-5.6 Luna |
|---|---|---|
| Provider | OpenAI | OpenAI |
| Input Price | $1.75/1M tokens | $1.00/1M tokens |
| Output Price | $14.00/1M tokens | $6.00/1M tokens |
| Context Window | 256,000 tokens | 1,050,000 tokens |
| Max Output | 32,768 tokens | 128,000 tokens |
| Category | coding | efficient |
| Capabilities | textcode | textvisioncodereasoning |
| Release Date | 3/1/2026 | 6/26/2026 |
GPT-5.3 Codex vs GPT-5.6 Luna: Which Should You Choose?
Choosing between GPT-5.3 Codex and GPT-5.6 Luna 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 — 43% cheaper than GPT-5.3 Codex. Meanwhile, GPT-5.6 Luna offers a significantly larger context window at 1,050,000 tokens vs 256,000 for GPT-5.3 Codex.
These models target different tiers: GPT-5.3 Codex is a coding model while GPT-5.6 Luna is efficient. This means they're optimized for different workloads. GPT-5.6 Luna targets more demanding workloads, while GPT-5.3 Codex provides a cost-effective option for everyday tasks.
Output costs matter too. GPT-5.3 Codex charges $14.00/1M output tokens vs $6.00 for GPT-5.6 Luna. 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 GPT-5.3 Codex is text-only. If your application needs image understanding, this narrows your choice.
Best Use Cases
Choose GPT-5.3 Codex when:
- • You're already using OpenAI's API ecosystem
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, reasoning)
- • 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
Pros and Caveats at a Glance
GPT-5.3 Codex
- • Input pricing: $1.75/M tokens
- • Output pricing: $14.00/M tokens
- • Context window: 256,000 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
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.
Try Different Scenarios
Use the calculator below to see how costs change with different usage patterns
GPT-5.3 Codex (OpenAI)
GPT-5.6 Luna (OpenAI)
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