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c305fa5 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 | # llama.cpp INI Presets
## Introduction
The INI preset feature, introduced in [PR#17859](https://github.com/ggml-org/llama.cpp/pull/17859), allows users to create reusable and shareable parameter configurations for llama.cpp.
### Using Presets with the Server
When running multiple models on the server (router mode), INI preset files can be used to configure model-specific parameters. Please refer to the [server documentation](../tools/server/README.md) for more details.
### Using a Hugging Face Preset
> [!IMPORTANT]
>
> Please only use presets that you can trust! Unknown presets may be unsafe
You can push your preset to Hugging Face Hub and share with other users by:
1. Creating an empty model repository on Hugging Face
2. Creating a `preset.ini` file in the root directory of the repository
Example of a `preset.ini`:
```ini
[*]
ctx-size = 0
mmap = 1
kv-unified = 1
parallel = 4
spec-default = 1
[Qwen3.5-4B]
hf = unsloth/Qwen3.5-4B-GGUF:Q4_K_M
ctx-size = 262144
batch-size = 2048
ubatch-size = 2048
top-p = 1.0
top-k = 0
min-p = 0.01
temp = 1.0
[gpt-oss-120b-hf]
hf = ggml-org/gpt-oss-120b-GGUF
ctx-size = 262144
batch-size = 2048
ubatch-size = 2048
top-p = 1.0
top-k = 0
min-p = 0.01
temp = 1.0
chat-template-kwargs = {"reasoning_effort": "high"}
```
The preset will be loaded similarly to the `--models-preset` option. Therefore, you can also override certain params via CLI arguments:
```sh
# Force temp = 0.1, overriding the preset value
llama-cli -hf username/my-preset --temp 0.1
```
### Named presets
If you want to define multiple preset configurations for one or more GGUF models, you can create a blank HF repo containing a single `preset.ini` file that references the actual model(s):
```ini
[*]
mmap = 1
[gpt-oss-20b-hf]
hf = ggml-org/gpt-oss-20b-GGUF
batch-size = 2048
ubatch-size = 2048
top-p = 1.0
top-k = 0
min-p = 0.01
temp = 1.0
chat-template-kwargs = {"reasoning_effort": "high"}
[gpt-oss-120b-hf]
hf = ggml-org/gpt-oss-120b-GGUF
batch-size = 2048
ubatch-size = 2048
top-p = 1.0
top-k = 0
min-p = 0.01
temp = 1.0
chat-template-kwargs = {"reasoning_effort": "high"}
```
You can then use it via `llama-cli` or `llama-server`, example:
```sh
llama-server -hf user/repo:gpt-oss-120b-hf
```
Please make sure to provide the correct `hf-repo` for each child preset. Otherwise, you may get error: `The specified tag is not a valid quantization scheme.`
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