FreeLLMAll models › meituan-longcat
LongCat-2.5
meituan-longcat · released 4 Nov 2026
Where to use it for free
- Run it in one command with whichllm (free, open source):
uvx whichllm@latest plan "LongCat-2.5"shows the GPU you need,uvx whichllm@latest run "LongCat-2.5 gguf"downloads it and starts a chat - Download and run it at home: official weights · GGUF files for Ollama and LM Studio
New: waiting for Arena votes
Released on 4 Nov 2026. Arena has not voted on this model yet. As soon as it does, the model moves into the ranking automatically, usually the next night. Until then you can still check its size, memory needs and speed below.
Speed on popular hardware
| Hardware | GPU memory | Fits? | Speed |
|---|---|---|---|
| RTX 3060 12 GB | 12 GB | Does not fit | — |
| RTX 4060 Ti 16 GB | 16 GB | Does not fit | — |
| RTX 3090 | 24 GB | Does not fit | — |
| RTX 4090 | 24 GB | Does not fit | — |
| RTX 5090 | 32 GB | Does not fit | — |
| RX 7900 XTX | 24 GB | Does not fit | — |
| 2 × RTX 3090 | 48 GB | Does not fit | — |
| 4 × RTX 3090 | 96 GB | Does not fit | — |
| Mac M4 Max 128 GB | 96 GB | Does not fit | — |
| Ryzen AI Max+ 395 128 GB | 96 GB | Does not fit | — |
| 8 × H100 SXM | 640 GB | Does not fit | — |
Estimate at 4-bit with 32K context, 64 GB of DDR5 for offload. Speed ≈ memory bandwidth × 78% ÷ data read per token, plus a fixed cost per token, calibrated on 44 real llama.cpp tests; typical error about ±10%. Compare all GPUs.
GPU memory needed
| Level | 8K context | 32K context | 128K context | Quality vs full |
|---|---|---|---|---|
| Q3_K_M | 891 GB | 892 GB | 896 GB | +4.7% noticeable loss |
| Q4_K_M | 1080 GB | 1081 GB | 1085 GB | +1.2% very small loss |
| Q5_K_M | 1266 GB | 1267 GB | 1272 GB | +0.4% near-lossless |
| Q6_K | 1460 GB | 1461 GB | 1466 GB | +0.2% near-lossless |
| Q8_0 | 1892 GB | 1893 GB | 1897 GB | ≈ 0% same as full |
| F16 | 3561 GB | 3562 GB | 3566 GB | ≈ 0% same as full |
Weights + context cache (from the model's architecture) + runtime. Quality: increase in perplexity against the full model, from llama.cpp tests, scaled by model size. Simulate your own setup.
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