LongCat-2.0 and GPT-5.6 Luna: Open-Weight vs Closed Economy Tier Compared
A source-based comparison of LongCat-2.0 (1.6T MoE, MIT License, $0.30/M input) and GPT-5.6 Luna (OpenAI's economy tier, proprietary, $0.20/M input after an 80% price cut on July 30, 2026). Covers architecture, pricing, licensing, context, and deployment.
Independent third-party resource. Not affiliated with or endorsed by LongCat, Meituan, DeepSeek, or any other publisher discussed on this page.
Published: 2026-08-06
This is an independent, source-based comparison of LongCat-2.0 (Meituan) and GPT-5.6 Luna (OpenAI's economy tier). It compares documented architecture, pricing, licensing, context windows, and deployment options. It does not report performance as a verdict — for publisher-reported scores, see the individual model pages and benchmark index linked below. Every claim in this page is sourced from the linked publisher documentation.
| Dimension | LongCat-2.0 | GPT-5.6 Luna |
|---|---|---|
| Developer | Meituan (LongCat team) | OpenAI |
| Total parameters | 1.6T (MoE) | Undisclosed (proprietary) |
| Active parameters | ~48B per token (33B—56B dynamic) | Undisclosed |
| Architecture | ScMoE + LSA sparse attention + N-gram Embedding | Proprietary frontier architecture (undisclosed) |
| Context window | 1M tokens (native) | 1.05M tokens |
| Max output | 128K tokens | 128K tokens |
| Modalities | Text | Text, image, file input; text output |
| API pricing (per 1M tokens) | $0.30 input / $1.20 output (OpenRouter) | $0.20 input / $1.20 output (after 80% cut on 2026-07-30) |
| Cache pricing | Free (cache hits not billed) | $0.02/M cached input |
| Cost ratio (relative) | 1× | ~0.67× input (cheaper), ~1× output (parity) |
| License | MIT License (open-source weights) | Proprietary (closed model) |
| Reasoning mode | Dynamic (MOPD distilled, adaptive) | Configurable reasoning effort (None to Max, default Medium) |
| Training hardware | 50,000 domestic AI ASICs (no NVIDIA) | Undisclosed (likely NVIDIA-based) |
| Self-hosted deployment | Yes — SGLang, vLLM, Transformers, NPU path | No (API only) |
What GPT-5.6 Luna Is, and Is Not
GPT-5.6 Luna is OpenAI's economy tier within the GPT-5.6 family — positioned below Terra (balanced) and Sol (flagship). It is a closed, API-only model: parameters and architecture are undisclosed, and OpenAI prices it at $0.20/M input and $1.20/M output after an 80% price cut on July 30, 2026 — a cut widely interpreted as a response to Chinese open-weight pricing. It is text-and-image-in, text-out, with a 1.05M-token context and configurable reasoning effort.
LongCat-2.0 is a fully documented open-weight model: 1.6T MoE, ~48B active per token, MIT license, trained on domestic AI ASICs. The comparison is therefore not just model-vs-model; it is a comparison of two distribution models — open weights that can be self-hosted and audited, versus a closed API service.
Pricing After the 80% Cut
After OpenAI's July 30 cut, Luna's input rate ($0.20/M) is actually cheaper than LongCat-2.0's OpenRouter input rate ($0.30/M), while output rates are at parity ($1.20/M). Luna charges $0.02/M for cached input; LongCat-2.0 does not bill cache hits at all.
The headline numbers, however, only tell part of the story. LongCat-2.0's weights can be self-hosted, eliminating per-token fees entirely at the cost of infrastructure. DeepSeek V4-Flash ($0.14/$0.28) remains cheaper than both on metered API pricing. For teams evaluating metered API cost alone, Luna's post-cut pricing is competitive; for teams that can host weights, the cost calculus changes completely.
Third-party indexing (Artificial Analysis) scores Luna at 51 on the Intelligence Index — the economy tier of the GPT-5.6 family, with Sol at 59. These figures are third-party and not independently verified by this site.
Licensing and Control
LongCat-2.0 is MIT-licensed: commercial use, modification, redistribution, and distillation are permitted, and the model can be inspected and self-hosted. GPT-5.6 Luna is proprietary and available only through OpenAI's API under commercial terms of service; fine-tuning is not offered on this tier. For regulated industries with data-sovereignty or auditability requirements, this remains the decisive difference.
Ecosystem and Tooling
GPT-5.6 Luna operates inside the OpenAI ecosystem: Responses API, Codex, ChatGPT for Work, function calling, structured output, and reasoning-effort controls — with mature SDKs and documentation. It is positioned for high-volume, latency- sensitive, well-scoped tasks such as summarization, classification, and routine automation.
LongCat-2.0 integrates through third-party harnesses via its OpenAI-compatible and Anthropic-compatible endpoints (Claude Code, OpenClaw, and similar), and can be deployed on SGLang, vLLM, or HuggingFace Transformers. Its tool ecosystem is less vertically integrated than OpenAI's, but its self-hosting option gives organizations infrastructure-level control.
This comparison is based on publicly available publisher documentation accessed on 2026-08-06. LongCat-2.0 specifications are from the publisher blog and GitHub repository. GPT-5.6 Luna specifications are from OpenAI's model documentation and pricing page, with third-party context from Artificial Analysis.
This is a feature-level comparison, not a performance evaluation. This site has not independently tested either model. Benchmark scores published by either vendor have not been independently verified.
Pricing is current as of the access date and may change. The July 30, 2026 price cut is reflected in the figures above; verify the current rates on OpenAI's pricing page before deployment.
Related pages
- LongCat-2.0 model profile
Full technical brief covering architecture, training, benchmarks, and deployment options.
- LongCat-2.0 vs GPT-5.5 comparison
The earlier comparison against OpenAI's previous flagship, kept for reference.
- LongCat-2.0 vs DeepSeek V4-Flash comparison
The open-weight comparison that frames the price-competition context for GPT-5.6 Luna.
- LongCat-2.0 Publisher-Reported Benchmark Scores
The benchmark data cited in this comparison with source attribution.
Sources
- LongCat-2.0 Publisher Blog Post
Publisher documentationAccessed 2026-08-06
Publisher announcement detailing LongCat-2.0 architecture (ScMoE, LSA, N-gram Embedding, MOPD), 1.6T parameters, domestic-ASIC training, and MIT License.
- LongCat-2.0 GitHub Repository
Primary sourceAccessed 2026-08-06
Model code, weights, MIT License terms, and deployment instructions.
- OpenAI GPT-5.6 Luna Developer Docs
Publisher documentationAccessed 2026-08-06
OpenAI model documentation for gpt-5.6-luna: 1.05M context, 128K max output, reasoning effort controls, text+image input.
- GPT-5.6 Family Pricing
Publisher documentationAccessed 2026-08-06
Pricing page showing the July 30, 2026 80% price cut: Luna at $0.20/M input, $0.02/M cached input, $1.20/M output; Terra and Sol tiers at higher rates.
- Artificial Analysis Intelligence Index
Third-partyAccessed 2026-08-06
Third-party index scoring GPT-5.6 Luna at 51 (vs Sol at 59) on the Intelligence Index, with speed and cost benchmarks.
Independent third-party disclosure
This page is published by an independent third-party site. It is not affiliated with, endorsed by, sponsored by, or operated by Meituan, LongCat, or any of their affiliates. The content summarizes publicly-available primary documentation and does not represent the views of any referenced organization.
Last reviewed: 2026-08-06