# Supported Models
The following tables detail the models supported by LMDeploy's TurboMind engine and PyTorch engine across different platforms.
## TurboMind on CUDA Platform
| Model | Size | Type | FP16/BF16 | KV INT8 | KV INT4 | W4A16 |
| :------------------------------: | :--------------: | :--: | :-------: | :-----: | :-----: | :---: |
| Llama | 7B - 65B | LLM | Yes | Yes | Yes | Yes |
| Llama2 | 7B - 70B | LLM | Yes | Yes | Yes | Yes |
| Llama3 | 8B, 70B | LLM | Yes | Yes | Yes | Yes |
| Llama3.1 | 8B, 70B | LLM | Yes | Yes | Yes | Yes |
| Llama3.2\[2\] | 1B, 3B | LLM | Yes | Yes\* | Yes\* | Yes |
| InternLM | 7B - 20B | LLM | Yes | Yes | Yes | Yes |
| InternLM2 | 7B - 20B | LLM | Yes | Yes | Yes | Yes |
| InternLM2.5 | 7B | LLM | Yes | Yes | Yes | Yes |
| InternLM3 | 8B | LLM | Yes | Yes | Yes | Yes |
| InternLM-XComposer2 | 7B, 4khd-7B | MLLM | Yes | Yes | Yes | Yes |
| InternLM-XComposer2.5 | 7B | MLLM | Yes | Yes | Yes | Yes |
| Qwen | 1.8B - 72B | LLM | Yes | Yes | Yes | Yes |
| Qwen1.5\[1\] | 1.8B - 110B | LLM | Yes | Yes | Yes | Yes |
| Qwen2\[2\] | 0.5B - 72B | LLM | Yes | Yes\* | Yes\* | Yes |
| Qwen2-MoE | 57BA14B | LLM | Yes | Yes | Yes | Yes |
| Qwen2.5\[2\] | 0.5B - 72B | LLM | Yes | Yes\* | Yes\* | Yes |
| Mistral\[1\] | 7B | LLM | Yes | Yes | Yes | No |
| Mixtral | 8x7B, 8x22B | LLM | Yes | Yes | Yes | Yes |
| DeepSeek-V2 | 16B, 236B | LLM | Yes | Yes | Yes | No |
| DeepSeek-V2.5 | 236B | LLM | Yes | Yes | Yes | No |
| Qwen-VL | 7B | MLLM | Yes | Yes | Yes | Yes |
| DeepSeek-VL | 7B | MLLM | Yes | Yes | Yes | Yes |
| Baichuan | 7B | LLM | Yes | Yes | Yes | Yes |
| Baichuan2 | 7B | LLM | Yes | Yes | Yes | Yes |
| Code Llama | 7B - 34B | LLM | Yes | Yes | Yes | No |
| YI | 6B - 34B | LLM | Yes | Yes | Yes | Yes |
| LLaVA(1.5,1.6) | 7B - 34B | MLLM | Yes | Yes | Yes | Yes |
| InternVL | v1.1 - v1.5 | MLLM | Yes | Yes | Yes | Yes |
| InternVL2\[2\] | 1 - 2B, 8B - 76B | MLLM | Yes | Yes\* | Yes\* | Yes |
| InternVL2.5(MPO)\[2\] | 1 - 78B | MLLM | Yes | Yes\* | Yes\* | Yes |
| ChemVLM | 8B - 26B | MLLM | Yes | Yes | Yes | Yes |
| MiniCPM-Llama3-V-2_5 | - | MLLM | Yes | Yes | Yes | Yes |
| MiniCPM-V-2_6 | - | MLLM | Yes | Yes | Yes | Yes |
| MiniGeminiLlama | 7B | MLLM | Yes | - | - | Yes |
| GLM4 | 9B | LLM | Yes | Yes | Yes | Yes |
| CodeGeeX4 | 9B | LLM | Yes | Yes | Yes | - |
| Molmo | 7B-D,72B | MLLM | Yes | Yes | Yes | No |
"-" means not verified yet.
```{note}
* [1] The TurboMind engine doesn't support window attention. Therefore, for models that have applied window attention and have the corresponding switch "use_sliding_window" enabled, such as Mistral, Qwen1.5 and etc., please choose the PyTorch engine for inference.
* [2] When the head_dim of a model is not 128, such as llama3.2-1B, qwen2-0.5B and internvl2-1B, turbomind doesn't support its kv cache 4/8 bit quantization and inference
```
## PyTorchEngine on CUDA Platform
| Model | Size | Type | FP16/BF16 | KV INT8 | KV INT4 | W8A8 | W4A16 |
| :----------------------------: | :---------: | :--: | :-------: | :-----: | :-----: | :--: | :---: |
| Llama | 7B - 65B | LLM | Yes | Yes | Yes | Yes | Yes |
| Llama2 | 7B - 70B | LLM | Yes | Yes | Yes | Yes | Yes |
| Llama3 | 8B, 70B | LLM | Yes | Yes | Yes | Yes | Yes |
| Llama3.1 | 8B, 70B | LLM | Yes | Yes | Yes | Yes | Yes |
| Llama3.2 | 1B, 3B | LLM | Yes | Yes | Yes | Yes | Yes |
| Llama3.2-VL | 11B, 90B | MLLM | Yes | Yes | Yes | - | - |
| InternLM | 7B - 20B | LLM | Yes | Yes | Yes | Yes | Yes |
| InternLM2 | 7B - 20B | LLM | Yes | Yes | Yes | Yes | Yes |
| InternLM2.5 | 7B | LLM | Yes | Yes | Yes | Yes | Yes |
| InternLM3 | 8B | LLM | Yes | Yes | Yes | Yes | Yes |
| Baichuan2 | 7B | LLM | Yes | Yes | Yes | Yes | No |
| Baichuan2 | 13B | LLM | Yes | Yes | Yes | No | No |
| ChatGLM2 | 6B | LLM | Yes | Yes | Yes | No | No |
| Falcon | 7B - 180B | LLM | Yes | Yes | Yes | No | No |
| YI | 6B - 34B | LLM | Yes | Yes | Yes | Yes | Yes |
| Mistral | 7B | LLM | Yes | Yes | Yes | Yes | Yes |
| Mixtral | 8x7B, 8x22B | LLM | Yes | Yes | Yes | No | No |
| QWen | 1.8B - 72B | LLM | Yes | Yes | Yes | Yes | Yes |
| QWen1.5 | 0.5B - 110B | LLM | Yes | Yes | Yes | Yes | Yes |
| QWen1.5-MoE | A2.7B | LLM | Yes | Yes | Yes | No | No |
| QWen2 | 0.5B - 72B | LLM | Yes | Yes | No | Yes | Yes |
| Qwen2.5 | 0.5B - 72B | LLM | Yes | Yes | No | Yes | Yes |
| QWen2-VL | 2B, 7B | MLLM | Yes | Yes | No | No | Yes |
| QWen2.5-VL | 3B - 72B | MLLM | Yes | No | No | No | No |
| DeepSeek-MoE | 16B | LLM | Yes | No | No | No | No |
| DeepSeek-V2 | 16B, 236B | LLM | Yes | No | No | No | No |
| DeepSeek-V2.5 | 236B | LLM | Yes | No | No | No | No |
| DeepSeek-VL2 | 3B - 27B | MLLM | Yes | No | No | No | No |
| MiniCPM3 | 4B | LLM | Yes | Yes | Yes | No | No |
| MiniCPM-V-2_6 | 8B | LLM | Yes | No | No | No | Yes |
| Gemma | 2B-7B | LLM | Yes | Yes | Yes | No | No |
| Dbrx | 132B | LLM | Yes | Yes | Yes | No | No |
| StarCoder2 | 3B-15B | LLM | Yes | Yes | Yes | No | No |
| Phi-3-mini | 3.8B | LLM | Yes | Yes | Yes | Yes | Yes |
| Phi-3-vision | 4.2B | MLLM | Yes | Yes | Yes | - | - |
| CogVLM-Chat | 17B | MLLM | Yes | Yes | Yes | - | - |
| CogVLM2-Chat | 19B | MLLM | Yes | Yes | Yes | - | - |
| LLaVA(1.5,1.6)\[2\] | 7B-34B | MLLM | No | No | No | No | No |
| InternVL(v1.5) | 2B-26B | MLLM | Yes | Yes | Yes | No | Yes |
| InternVL2 | 1B-76B | MLLM | Yes | Yes | Yes | - | - |
| InternVL2.5(MPO) | 1B-78B | MLLM | Yes | Yes | Yes | - | - |
| Mono-InternVL\[1\] | 2B | MLLM | Yes | Yes | Yes | - | - |
| ChemVLM | 8B-26B | MLLM | Yes | Yes | No | - | - |
| Gemma2 | 9B-27B | LLM | Yes | Yes | Yes | - | - |
| Gemma3 | 1B-27B | MLLM | Yes | Yes | Yes | - | - |
| GLM4 | 9B | LLM | Yes | Yes | Yes | No | No |
| GLM-4V | 9B | MLLM | Yes | Yes | Yes | No | Yes |
| CodeGeeX4 | 9B | LLM | Yes | Yes | Yes | - | - |
| Phi-3.5-mini | 3.8B | LLM | Yes | Yes | No | - | - |
| Phi-3.5-MoE | 16x3.8B | LLM | Yes | Yes | No | - | - |
| Phi-3.5-vision | 4.2B | MLLM | Yes | Yes | No | - | - |
```{note}
* [1] Currently Mono-InternVL does not support FP16 due to numerical instability. Please use BF16 instead.
* [2] PyTorch engine removes the support of original llava models after v0.6.4. Please use their corresponding transformers models instead, which can be found in https://huggingface.co/llava-hf
```
## PyTorchEngine on Huawei Ascend Platform
| Model | Size | Type | FP16/BF16(eager) | FP16/BF16(graph) | W4A16(eager) |
| :------------: | :------: | :--: | :--------------: | :--------------: | :----------: |
| Llama2 | 7B - 70B | LLM | Yes | Yes | Yes |
| Llama3 | 8B | LLM | Yes | Yes | Yes |
| Llama3.1 | 8B | LLM | Yes | Yes | Yes |
| InternLM2 | 7B - 20B | LLM | Yes | Yes | Yes |
| InternLM2.5 | 7B - 20B | LLM | Yes | Yes | Yes |
| InternLM3 | 8B | LLM | Yes | Yes | Yes |
| Mixtral | 8x7B | LLM | Yes | Yes | No |
| QWen1.5-MoE | A2.7B | LLM | Yes | - | No |
| QWen2(.5) | 7B | LLM | Yes | Yes | No |
| QWen2-MoE | A14.57B | LLM | Yes | - | No |
| InternVL(v1.5) | 2B-26B | MLLM | Yes | - | Yes |
| InternVL2 | 1B-40B | MLLM | Yes | Yes | Yes |
| CogVLM2-chat | 19B | MLLM | Yes | No | - |
| GLM4V | 9B | MLLM | Yes | No | - |