koboldcpp-1.82.4

Old kobo yells at cloud edition

• NEW: Added OuteTTS for Text-To-Speech: OuteTTS is a text-to-speech model that can be used for narration by generating audio from KoboldCpp.
• You need two models, an OuteTTS GGUF and a WavTokenizer GGUF which you can find here.
• Once downloaded, load them in the Audio tab or using --ttsmodel and --ttswavtokenizer. You can also use --ttsgpu to load them on the GPU instead, and --ttsthreads to set a custom thread count used.
• When enabled, sets up OpenAI Speech API and XTTS API compatibility endpoints allowing you to easily hook KoboldCpp TTS into existing TTS frontends.
• Comes with a set of included voices, as well as New Speaker Synthesis, allowing you to create hundreds of new unique voices just by entering a random name. Read more here.
• All OuteTTS GGUF v0.2 and the NEW v0.3 models are supported, including both 500m and 1B models.
• Credits to @ggerganov and @edwko for the original upstream implementation
• NEW: Bundled GGUF file analyzer: In the GUI Extras tab, or with --analyze, you can now analyze any GGUF file, which will display the metadata and tensor names, dimensions and types within that file.
• TAESD is now also available for SD3 and Flux! Enable with --sdvaeauto or "AutoFix VAE" in the GUI. TAESD is now compressed to fp8, making this VAE only about 3mb in size.
• VAE tiling for image generation can now be disabled with --sdnotile, this fixes the bleeding graphical artifacts on some cards.
• Adjusted compatibility build targets: CLBlast (Older CPU) mode now no longer requires AVX, providing a good option for very old/cheap systems to still have some level of GPU support. For users with AVX but not AVX2, you can use the Vulkan (Old CPU) mode instead.
• mmap is no longer the default option. To enable it, you now need --usemmap or set it in the GUI.
• Fix for save file GUI prompt not working
• Fix for web browser not launching with --launch in Linux GUI.
• Added more GUI slider options for context sizes.
• Max supported images per API request for Multimodal Vision is now increased to 8.
• Enabled multilingual support for Whisper (Voice Recognition) setting specific language codes.
• KoboldCpp now displays what capabilities and endpoints enabled on launch.
• Available Modules: TextGeneration ImageGeneration VoiceRecognition MultimodalVision NetworkMultiplayer WebSearchProxy TextToSpeech ApiKeyPassword
• Available APIs: KoboldCppApi OpenAiApi OllamaApi A1111ForgeApi ComfyUiApi WhisperTranscribeApi XttsApi OpenAiSpeechApi
• Updated Kobold Lite, multiple fixes and improvements
• Added Whisper language selection: Instead of automatically detecting the speaker language, you can now optionally specify it with a 2 character language code (e.g. ja for Japanese, fr for French). This ensures the output is in the right language.
• Added Text-To-Speech support for KoboldCpp backend
• Merged fixes and improvements from upstream

Hotfix 1.82.1: Fixed --analyze which should be working correctly now. Minor fixes to OuteTTS v0.3 handling and updated Lite UI. Whisper now accepts 8 bit and 32bit wav files, and form data input. Hotfix 1.82.2: Added support for Deepseek R1 Qwen Distill Hotfix 1.82.3: Fixed a TTS crash, CLBlast mislabeling, quiet now overrides debug Hotfix 1.82.4: Fixed deepseek adapter, draft decoding now accepts slightly different vocabs

To use, download and run the koboldcpp.exe, which is a one-file pyinstaller. If you don't need CUDA, you can use koboldcpp_nocuda.exe which is much smaller. If you have an Nvidia GPU, but use an old CPU and koboldcpp.exe does not work, try koboldcpp_oldcpu.exe If you have a newer Nvidia GPU, you can use the CUDA 12 version koboldcpp_cu12.exe (much larger, slightly faster). If you're using Linux, select the appropriate Linux binary file instead (not exe). If you're on a modern MacOS (M1, M2, M3) you can try the koboldcpp-mac-arm64 MacOS binary. If you're using AMD, we recommend trying the Vulkan option (available in all releases) first, for best support. Alternatively, you can try koboldcpp_rocm at YellowRoseCx's fork here

Run it from the command line with the desired launch parameters (see --help), or manually select the model in the GUI. and then once loaded, you can connect like this (or use the full koboldai client): http://localhost:5001

For more information, be sure to run the program from command line with the --help flag. You can also refer to the readme and the wiki.