GPT-5.6 Luna Pro vs Extract
Updated October 22, 2026; no benchmark has tested both models yet.
- Coding
- No data
- Overall
- No data
- Output $/M
- $1.20
- Coding
- No data
- Overall
- No data
- Output $/M
- No data
GPT-5.6 Luna Pro or Extract: which to pick
Neither model has a coding score yet, so the two cannot be ranked on coding.
Pick GPT-5.6 Luna Pro for a larger context window (1.05M against 1M tokens).
No benchmark has tested either model yet, so price and context are the only way to compare them.
Which one for your work
Each card is decided by one number both models carry. Where only one has it, the card says so and makes no call.
Coding
Vibe Coding Index, six public coding benchmarks
No call
Neither has a coding score yet.
One side not measured
Long documents
Listed context window
GPT-5.6 Luna Pro
GPT-5.6 Luna Pro takes 1.05M tokens against 1M.
Listed by OpenRouter
Everyday cost
1K input + 500 output tokens
Extract
GPT-5.6 Luna Pro $0.0008, Extract $0.0000 per turn.
List prices
At a glance
- Coding index
- GPT-5.6 Luna Pro not benchmarked, Extract not benchmarked.
- Widest category
- None yet: no category has been tested on both models.
- Widest single gap
- None yet: no benchmark has tested both models.
- Output price
- GPT-5.6 Luna Pro $1.20 against Extract Free per million output tokens.
- Context window
- GPT-5.6 Luna Pro takes 1.05M tokens, Extract 1M.
Benchmark by benchmark
Every board either model has a result on, a category to a fold; bars are each result on a 0 to 100 scale. Only one model is measured on each, so no row names a leader.
What each workload costs
Three fixed token mixes at each model's listed price, so per-token rates become a bill.
Chat turn
1K input + 500 output tokens
Extract costs less
Repository review
50K input + 3K output tokens
Extract costs less
Agent loop
200K input + 10K output tokens
Extract costs less
Listed OpenRouter rates, without cache or batch discounts. A workload that does not fit a model's context window would need splitting.
Specification differences
The leading value in a row is marked; a row with a missing value names no leader. Our two rows are marked in red.
| Specification | OpenAI GPT-5.6 Luna Pro | ScaleDown Extract |
|---|---|---|
| Maker | OpenAI | Scaledown |
| Weights | No public weights listed | No public weights listed |
| Released | July 9, 2026 | October 13, 2026 |
| Context window | 1.05M | 1M |
| Input $/Mtok | $0.20 | $0.04 |
| Output $/Mtok | $1.20 | Free |
| Coding index | Not benchmarked | Not benchmarked |
| Independent measurements behind it | 0 | 0 |
| Cost per solved task | Not computable | Not computable |
| Source | OpenRouter listing | OpenRouter listing |
Questions
Is GPT-5.6 Luna Pro better than Extract for coding?
Neither model has a coding score yet, so the two cannot be ranked on coding. Pick GPT-5.6 Luna Pro for a larger context window (1.05M against 1M tokens).
Which is cheaper, GPT-5.6 Luna Pro or Extract?
GPT-5.6 Luna Pro costs $0.20 per million input tokens and $1.20 per million output tokens; Extract costs $0.04 and Free. Cost per solved task is known for neither of them.
Which has the bigger context window, GPT-5.6 Luna Pro or Extract?
GPT-5.6 Luna Pro, with 1.05M tokens against 1M.
Has any benchmark tested both GPT-5.6 Luna Pro and Extract?
No benchmark has tested either model yet, so price and context are the only way to compare them. Data as of October 22, 2026.