Meituan's LongCat-2.0: A 1.6-Trillion-Parameter Coding Model Trained Entirely on Chinese Chips, Now MIT-Licensed
Meituan has officially open-sourced LongCat-2.0, a Mixture-of-Experts (MoE) coding model with a massive 1.6 trillion parameters. This is more than just another model release: it's believed to be the largest frontier AI model ever trained completely on domestic Chinese chips, with no Nvidia GPUs involved.
For the global AI industry, LongCat-2.0 sends a clear signal: despite chip export controls, China retains the capability to train models that compete with the world's best.
Model Specifications
| Item | Specification |
|---|---|
| Developer | Meituan |
| Architecture | Sparse MoE |
| Total Parameters | 1.6 Trillion (1.6T) |
| Active Parameters | ~48 Billion (48B, dynamic range 33B-56B) |
| Context Window | 1M tokens |
| Training Data | 35 Trillion tokens |
| License | MIT (Fully Open-Source) |
| Training Hardware | 50,000 domestic AI chips (No Nvidia GPUs) |
| Communication Library | Huawei HCCL |
| Special Techniques | LongCat Sparse Attention, 135B N-gram Embedding Module |
Benchmark Performance
| Benchmark | LongCat-2.0 | GPT-5.5 | Claude Opus 4.8 |
|---|---|---|---|
| SWE-bench Pro | 59.5 | 58.6 | 69.2 |
| Terminal-Bench 2.1 | 70.8 | 78.2 | 82.7 |
LongCat-2.0 achieved a score of 59.5 on SWE-bench Pro, surpassing GPT-5.5's 58.6. This is a landmark achievement: an open-source model trained entirely on domestic chips has beaten OpenAI's flagship model on a coding benchmark.
However, on broader agent benchmarks (FORTE, BrowseComp), LongCat-2.0 still trails Claude Opus 4.8, indicating closed-source flagships maintain an advantage in complex reasoning and multi-step tasks.
API Pricing
LongCat-2.0 is available on OpenRouter (previously listed anonymously as "Owl Alpha"):
| Pricing Tier | Input Price (per 1M tokens) | Output Price (per 1M tokens) |
|---|---|---|
| Standard | $0.75 | $2.95 |
| Promotional | $0.30 | $1.20 |
| Cache Hit | Free | — |
Competitive Comparison:
| Model | Input Price | Output Price |
|---|---|---|
| LongCat-2.0 | $0.75 | $2.95 |
| Kimi K2.7 Code | $0.95 | $4.00 |
| Claude Sonnet 5 | $2.00 | $10.00 |
| GPT-5.5 | $5.00 | $30.00 |
LongCat-2.0's pricing is approximately one-seventh that of GPT-5.5. It's also about 20% cheaper than Kimi K2.7 Code, another open-source model.
Why This Matters
1. Independent Innovation Amid Chip Sanctions
Trained on 50,000 domestic AI chips using Huawei's HCCL library, without a single Nvidia GPU, LongCat-2.0 demonstrates:
- China can train frontier-scale AI models under chip sanctions.
- Domestic AI chip clusters have reached production-ready levels.
- The software ecosystem (HCCL) is progressively replacing CUDA.
2. Fully Open-Source Under MIT License
Unlike many "open-weight" models with restrictions, LongCat-2.0 uses the MIT License—one of the most permissive open-source licenses. This means:
- Commercial use without royalties.
- Modification and redistribution are allowed.
- Full local deployment with no usage limits.
3. Coding Capability Approaches the Frontier
A SWE-bench Pro score of 59.5 means LongCat-2.0 performs comparably to GPT-5.5 on real-world GitHub issue resolution tasks. For enterprises looking to deploy large-scale coding agents, it offers an extremely cost-effective option.
What This Means for Developers
| Use Case | Recommended Model | Rationale |
|---|---|---|
| Cost-sensitive large-scale coding agents | LongCat-2.0 | $0.75/M input, MIT license |
| Everyday coding assistance | Kimi K2.7 Code | Better Copilot integration & ecosystem |
| Complex reasoning & architecture design | Claude Sonnet 5 | Strongest reasoning capabilities |
| Data-sensitive environments | LongCat-2.0 | MIT license, fully local deployment |
| IDE-integrated workflows | GPT-4o | Most mature Copilot ecosystem |
Conclusion
The release of LongCat-2.0 represents more than just a new model—it signals a potential shift in the AI industry landscape.
Key takeaways:
- A 1.6-trillion-parameter MoE model trained entirely on domestic chips, without Nvidia GPUs.
- SWE-bench Pro 59.5 surpasses GPT-5.5, setting a new bar for open-source coding models.
- MIT License offers maximum permissiveness for commercial use.
- API pricing at $0.75/M input—roughly one-seventh the cost of GPT-5.5.
- A major milestone in chip sovereignty, proving frontier models can be trained under sanctions.
For developers and enterprises, LongCat-2.0 presents a compelling option: near-frontier performance, extremely low cost, and full open-source freedom. In an increasingly diverse model landscape, cost and flexibility are becoming as critical as raw capability in the decision-making process.
Loading...