OpenAI
GPT-5.6 Luna
- Benchmark records
- 7
- Snapshot
- 2026-07-30
Independent model comparison
GPT-5.6 Luna vs Qwen3.5 Plus 2026-02-15: evidence side by side
Compare the models using only evidence that can be identified and attributed. Exact benchmark matches appear first; independent facts and user reports remain separate and do not create an overall ranking.
Exact comparison coverage
1 benchmark record share an exact reviewed comparison key.
Evidence strength
Limited exact coverage
The page is useful for inspection but does not yet contain enough pair-native evidence for Search publication.
Models at a glance
Key differences
Alibaba
Qwen3.5 Plus 2026-02-15
- Benchmark records
- 2
- Snapshot
- 2026-04-02
| Detail | GPT-5.6 Luna | Qwen3.5 Plus 2026-02-15 |
|---|---|---|
| Provider |
OpenAI |
Alibaba |
| Release date Shown only where an exact reviewed release date is available. |
Not verified |
Not verified |
| Exact benchmark coverage Only records carrying the same reviewed comparison identity are counted. |
1 shared record |
1 shared record |
Price and speed appear only when an exact reviewed operational reference is attached to that model identity.
Primary comparison evidence
Exact matched benchmark evidence
A shared benchmark name is not enough. A result appears side by side only when both model records carry the same reviewed comparison key. Duplicate or unversioned records are omitted rather than guessed into alignment.
ROASBench
A 12-month performance-marketing simulation scored on business outcomes, planning, behavior, and persona fit.
GPT-5.6 Luna
4 configurations
Average ROASBench score
Configuration: 4 configurations compared separately
Spring Prompt · Reviewed public-catalogue SQLite projection · 12-month simulation
Qwen3.5 Plus 2026-02-15
26.07
Average ROASBench score
Configuration: Qwen: Qwen3.5 Plus 2026-02-15
Spring Prompt · Reviewed public-catalogue SQLite projection · 12-month simulation
Secondary context · not head-to-head
Independent signals for each model
The sources below evaluated or discussed each model independently. Putting them in adjacent columns makes them easier to inspect, but it does not make their metrics, samples, or observations directly comparable.
Independent early-test reports
Early technical field tests from X
Editor-paraphrased reports from independent authors in each model's fixed 14-day launch window. These selectively surfaced anecdotes are not direct head-to-head tests unless they also appear in the dedicated direct-report section above.
GPT-5.6 Luna
No editor-reviewed X field-test paragraph is active for this model snapshot.
Qwen3.5 Plus 2026-02-15
Early technical field tests
Early Qwen3.5 Plus reports diverged by workflow. One builder used it through a coding plan to extend an open-source, multi-speaker text-to-speech project and shared the resulting repository and video. Another intensive user found both the native CLI and an OpenCode configuration materially weaker at understanding and tool use than a Claude Code baseline. The launch-window evidence points to practical build capability with uneven agent reliability across harnesses.
Source venue: X · window: 2026-02-16 to 2026-03-02 · 2 tests · 2 independent authors · 2 with a method or artifact · identity reviewed
X field tests remain separate from Reddit community opinions, Artificial Analysis facts, and every scored benchmark.
How to read this comparison
Spring Prompt does not name an overall winner from unrelated benchmark scores, third-party metrics, Reddit opinions, or X field-test reports.
Different benchmarks measure different constructs and may use different populations, prompts, harnesses, model revisions, tools, and score scales. This page does not average those values or infer a winner from source coverage. Test both models on your own production work before making a consequential choice.