koboldcpp-1.110

KoboldCpp 3 Year Anniversary Edition

• NEW: OpenAI Compatible Router Mode: - Automatic model and config hotswapping is finally available in the OpenAI Compatible API. Note that this functions differently from the llama.cpp version, it's more like llama-swap, allowing you to perform full config-reloads similar to the existing admin endpoint, but also within the existing request and response via a reverse proxy. Requires admin mode enabled. Enable it with --routermode. Streaming is supported with a small delay.
  • Model swapping now has an extra option "initial_model" which was the model that was originally loaded.
• NEW: Auto Unload Timeout - Unloads the existing config (unloading all models) after a specified number of seconds. Works best with router mode to allow for auto reloading. Can also manually reload with admin endpoint.
• NEW: Qwen3TTS now supports the 1.7B TTS model, with even better voice quality and voice cloning!
  • Check out the above video for sample audio.
  • Grab TTS GGUFs here: Qwen3TTS 1.7B Model and Qwen3TTS WavTokenizer
• AceStep 1.5 Music Generation Improvements: Better quality, Reference Audio uploads are now supported, Mp3 outputs (ported from @ServeurpersoCom's MIT mp3 implementation), better LM defaults allowing audio-code generation to work better, make stereo output default. Recommended .kcppt template for 6GB users
• Qwen3TTS loader improvements, supports --ttsgpu toggle, vulkan speed improvements for Qwen3TTS (cuda is still slow)
• NEW: Improved Ollama Emulation - Can now handle requests from endpoints that only support streaming (buffers responses). However, OpenAI endpoint is still recommended if supported.
• New: Multiple dynamic LoRAs: --sdlora now supports specifying directories as well. All the image LoRAs there will be loadable at runtime by using the LoRA syntax in your image generation prompt in the form <lora:filename:multiplier>. Also, merged multiple fixes and updates from upstream, include optional cache mode. Big thanks to @wbruna for the contributions.
• NEW: Revamped Colab Cloud Notebook: The official KoboldCpp colab notebook has been updated and reworked. Music generation is now enabled, and image gen and text gen can now be used separately.
• MCP improvements: Added notification support, now can handle simultaneous STDIO requests and request with multiple parts.
• Adjustments to forcing --autofit, now disables moecpu and overridetensors automatically if used together.
• Disable smartcache if slots is zero. Improved smartcache snapshot logic to use conserve slots.
• Add warning that RNN models currently do not support anti-slop sampler.
• Fixed some single token phrase bans not registering
• OpenAI compatible endpoints now have dynamics IDs and reflect token usage accurately (thanks @gustrd)
• Updated Kobold Lite, multiple fixes and improvements
• Merged fixes, new model support, and improvements from upstream, including Nemotron support and Qwen3.5 improvements.

Download and run the koboldcpp.exe (Windows) or koboldcpp-linux-x64 (Linux), which is a one-file pyinstaller for NVIDIA GPU users.
If you have an older CPU or older NVIDIA GPU and koboldcpp does not work, try oldpc version instead (Cuda11 + AVX1).
If you don't have an NVIDIA GPU, or do not need CUDA, you can use the nocuda version which is smaller.
If you're using AMD, we recommend trying the Vulkan option in the nocuda build first, for best support. Alternatively, you can download our rolling ROCm binary here if you use Linux.
If you're on a modern MacOS (M-Series) you can use the koboldcpp-mac-arm64 MacOS binary.
Click here for .gguf conversion and quantization tools

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.

koboldcpp-1.109.2

• SmartCache improvements - SmartCache should work better for RNN/hybrid models like Qwen 3.5 now. Additionally, smartcache is automatically enabled when using such models for a smoother experience, unless fast forwarding is disabled.
• NEW: Added experimental support for Music Generation via Ace Step - KoboldCpp now optionally supports generating music natively in as little as 4GB of VRAM, thanks to @ServeurpersoCom's acestep.cpp.
  • Requires 4 files (AceStep LM, diffusion, embedder and VAE which are found https://huggingface.co/koboldcpp/music/tree/main), but for your convenience we made templates for 6GB of vram (recommended option) 1.7B LM. (you can also try alternative templates for 4GB of vram here, and 4B 6GB (Tight fit, not recommended as a first option), 4B 8GB of vram and 4B 10GB of vram
  • When used, a brand new UI has been added at http://localhost:5001/musicui
  • New CLI args added --musicllm --musicdiffusion --musicembeddings --musicvae and --musiclowvram
  • To keep KoboldCpp lightweight our implementation re-uses the existing GGML libraries from Llamacpp, we are currently waiting on ace-step.cpp to upstream its GGML improvements.
  • As usual the ace-step specific backend components are only loaded if you are trying to load a music generation model, if you only wish to use KoboldCpp for text generation this addition does not impact your performance or memory usage.
• NEW: Added Qwen3-TTS support with high quality voice cloning - Finally, support for qwen3tts has been added from @predict-woo's qwen3-tts.cpp, this allows for high quality voice cloning at the level of XTTS, and much better than the OuteTTS one.
  • You'll need the TTS model and the qwen3tts tokenizer, remember to also specify a TTS directory if you want to use voice cloning.
  • Specify a directory of short voice audio samples (.mp3 or .wav) with --ttsdir, you'll be able to use TTS narration with those voices.
  • For the fastest generation speed use Vulkan.
• Fix follow-up tool call check with assistant prefills
• Fixed image importing in SDUI
• Config packing improvements as a minor sd.cpp update from @wbruna
• Fixed a wav header packing issue that could cause a click in output audio
• Relaxes size restrictions in image gen, also support high res reference images.
• --admindir now also indexes subdirectories up to 1 level deep.
• Show timestamps when image gen is completed
• Updated Kobold Lite, multiple fixes and improvements
• Merged fixes, new model support, and improvements from upstream

Hotfix 1.109.1 - Optimize the batch splitting for RNN models, fixed moecpu interaction with autofit, added music gen documentation, fixed a SSE streaming repeat bug in chat completions

Hotfix 1.109.2 - Added support for importing SillyTavern JSONL exports, fixed Qwen3TTS to allow running without GPU unless TTS GPU selected, added ComfyUI auth token support (from @RubenGarcia)

Download and run the koboldcpp.exe (Windows) or koboldcpp-linux-x64 (Linux), which is a one-file pyinstaller for NVIDIA GPU users.
If you have an older CPU or older NVIDIA GPU and koboldcpp does not work, try oldpc version instead (Cuda11 + AVX1).
If you don't have an NVIDIA GPU, or do not need CUDA, you can use the nocuda version which is smaller.
If you're using AMD, we recommend trying the Vulkan option in the nocuda build first, for best support. Alternatively, you can download our rolling ROCm binary here if you use Linux.
If you're on a modern MacOS (M-Series) you can use the koboldcpp-mac-arm64 MacOS binary.
Click here for .gguf conversion and quantization tools

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.

koboldcpp-1.108.2

• Try to fix broken pipe errors due to timeouts during long tool calls
• Updated SDUI, added toggle to send img2img as a reference.
• Added ollama /api/show endpoint emulation
• Try to fix autofit on rocm going oom
• Improved MCP behavior with multipart content
• Prevent swapping config at runtime from changing the download directory
• Adjust GUI for fractional scaling
• Fix output filenames incorrect path in some cases
• llama.cpp UI handling of common think tags.
• --autofit mode now hides the GUI layers selector
• Fixed extra spam from autofit mode
• Autofit toggle is now in the Quick Launch menu
• Autofit is now triggered if -1 gpulayers (default) is selected and tensor splits or tensor overrides are not set. Setting your own GPU layers overrides this behavior
• Now allow Image Gen soft limit to be overridden to 2048x2048 if user chooses. Note that this may crash if you don't know what you're doing.
• Updated upstream stable-diffusion.cpp by @wbruna
• Updated Kobold Lite, multiple fixes and improvements
• Merged fixes, new model support, and improvements from upstream

Hotfix 1.108.1 - Fix DPI handling issues, fixed wrong backend selected in some cases, added support for loading multiple image LoRAs
Hotfix 1.108.2 - Fixed OuteTTS broken audio, fixed cuda graph memory leak

Download and run the koboldcpp.exe (Windows) or koboldcpp-linux-x64 (Linux), which is a one-file pyinstaller for NVIDIA GPU users.
If you have an older CPU or older NVIDIA GPU and koboldcpp does not work, try oldpc version instead (Cuda11 + AVX1).
If you don't have an NVIDIA GPU, or do not need CUDA, you can use the nocuda version which is smaller.
If you're using AMD, we recommend trying the Vulkan option in the nocuda build first, for best support. Alternatively, you can download our rolling ROCm binary here if you use Linux.
If you're on a modern MacOS (M-Series) you can use the koboldcpp-mac-arm64 MacOS binary.
Click here for .gguf conversion and quantization tools

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.

koboldcpp-1.107.3

down comes the claw edition

• Added a new option for Vulkan (Older PC) in the oldpc builds. This provides GPU support via Vulkan without any CPU intrinsics (no AVX2, no AVX). This replaces the removed CLBlast options.
• Breaking Changes:
  • Pipeline parallel is enabled by default now in CLI. Disable it in the launcher or with --nopipelineparallel
  • Flash attention is enabled by default now in CLI. Disable it in the launcher or with --noflashattention
• Added a few fixes for GLM 4.7 Flash. Note that this model is extremely sensitive to rep-pen, recommend disabling rep pen when using it. Make sure you use a fixed gguf model as some early quants were broken. It may be helpful to use the GLM4.5 NoThink template, or enable forced thinking if you desire it.
• Fixes for mcp.json importing and MCP tool listing handshake (thanks @Rose22)
• Changed MCP user agent string as some sites were blocking it.
• Added the fractional scaling workaround fix for the GUI launcher for KDE on Wayland.
• Added support for SDXS, a really fast Stable Diffusion Image Generation model. This model is so fast that it can generate images on pure CPU in under 10 seconds on a raspberry Pi. Running it on GPU allows generating images in under half a second. An excellent way to get image generation if you do not have a GPU. For convenience, a GGUF quant of SDXS is provided here.
• Added support for ESRGAN 4x upscaler. Load this as an upscaler model to be able to upscale your generated images.
• Merged Image Gen improvements and Flux Klein model support from upstream (thanks @wbruna). Get Flux Klein's image model, VAE and text encoder.
• Added TAE SD support for Flux2, enable with --sdvaeauto.
• Increase image generation hard total resolution limit from 1 megapixel to 1.6 megapixels.
• Updated SDUI with some quality of life fixes by @Riztard
• Updated Kobold Lite, multiple fixes and improvements
  • Added even more themes from @Rose22
  • Added experimental TTS chunked streaming mode (works for all TTS APIs)
  • Added customizable sampler presets from @lubumbax
  • Removed manual admin state caching panel since it's made obsolete by --smartcache. The API still exists but should be unnecessary.
• Merged fixes, model support, and improvements from upstream, including Vulkan speedup from occam's coopmat1 optimization. Coopmat1 is used by GPU's with matrixcores such as the 7000 and 9000 series AMD GPU's.

Important Notice: The CLBlast backend is fully deprecated and has been REMOVED as of this version. If you require CLBlast, you will need to use an earlier version.

Hotfix 1.107.1 - SDUI improvements, Flux2 Image Editing support, MCP cert validation fixes, KDE scaling fix, Z-Image cfg clamp increased, reduce cuda graph spam, updated lite with minor refactors.

Hotfix 1.107.2 - This was grouped into a hotfix as 1.107.1 was unstable. Though this release is larger and out-of-band, you're encouraged to update to it from 1.107/1.107.1 for stability reasons. Barring unforeseen circumstances, the next major release will likely be delayed.

• Scaling fixes for some linux desktops
• Updated SDUI and sdcpp
• Template parser fix from @Reithan
• Added "error" as a possible stop reason (e.g. backend failed to generate).
• Fixed SSE parsing in MCP
• Added GLM4.7-NoThink adapter template
• NEW: Reworked newbie help menu, added simple configs they can use
• NEW: Added optional --downloaddir to specify where model downloads are stored for URL references.
• Fixed GLM4 and GLM4.7 Flash coherency after shifting issues, ref ggml-org#19292

Hotfix 1.107.3 - Made on special request, merging upstream support for Step 3.5 Flash and Kimi Linear

Download and run the koboldcpp.exe (Windows) or koboldcpp-linux-x64 (Linux), which is a one-file pyinstaller for NVIDIA GPU users.
If you have an older CPU or older NVIDIA GPU and koboldcpp does not work, try oldpc version instead (Cuda11 + AVX1).
If you don't have an NVIDIA GPU, or do not need CUDA, you can use the nocuda version which is smaller.
If you're using AMD, we recommend trying the Vulkan option in the nocuda build first, for best support. Alternatively, you can download our rolling ROCm binary here if you use Linux.
If you're on a modern MacOS (M-Series) you can use the koboldcpp-mac-arm64 MacOS binary.
Click here for .gguf conversion and quantization tools

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.

koboldcpp-1.106.2

MCP for the masses edition

• NEW: MCP Server and Client Support Added to KoboldCpp - KoboldCpp now supports running an MCP bridge that serves as a direct drop-in replacement for Claude Desktop.
  • KoboldCpp can connect to any HTTP or STDIO MCP server, using a mcp.json config format compatible with Claude Desktop.
  • Multiple servers are supported, KoboldCpp will automatically combine their tools and dispatch request appropriately.
  • Recommended guide for MCP newbies: Here is a simple guide on running a Filesystem MCP Server to let your AI browse files locally on your PC and search the web - https://github.com/LostRuins/koboldcpp/wiki#mcp-tool-calling
  • CAUTION: Running ANY MCP SERVER gives it full access to your system. Their 3rd party scripts will be able to modify and make changes to your files. Be sure to only run servers you trust!
  • The example music playing MCP server used in the screenshot above was this audio-player-mcp
• Flash Attention is now enabled by default when using the GUI launcher.
• Improvements to tool parsing (thanks @AdamJ8)
• API field continue_assistant_turn is now enabled by default in all chat completions (assistant prefill)
• Interrogate image max length increased
• Various StableUI fixes by @Riztard
• Using the environment variable GGML_VK_VISIBLE_DEVICES externally now always overrides whatever vulkan device settings set from KoboldCpp.
• Updated Kobold Lite, multiple fixes and improvements
  • NEW: Full settings UI overhaul from @Rose22, the settings menu is now much cleaner and more organized. Feedback welcome!
  • NEW: Added 4 new OLED themes from @Rose22
  • Improved performance when editing massive texts
  • General cleanup and multiple minor adjustments
  • Browser MCP implementation adapted from @ycros simple-mcp-client
• Merged fixes, model support, and improvements from upstream

Hotfix 1.106.1 - Allow overriding selected GPU devices directly with --device e.g. --device Vulkan0,Vulkan1, Updated lite
Hotfix 1.106.2 - Increase logprobs from 5 to 10, fixed memory usage with embeddings, allow device override to be set in gui (thanks @pi6am)

Important Notice: The CLBlast backend may be removed soon, as it is very outdated and no longer receives and updates, fixes or improvements. It can be considered superceded by the Vulkan backend. If you have concerns, please join the discussion here.

Download and run the koboldcpp.exe (Windows) or koboldcpp-linux-x64 (Linux), which is a one-file pyinstaller for NVIDIA GPU users.
If you have an older CPU or older NVIDIA GPU and koboldcpp does not work, try oldpc version instead (Cuda11 + AVX1).
If you don't have an NVIDIA GPU, or do not need CUDA, you can use the nocuda version which is smaller.
If you're using AMD, we recommend trying the Vulkan option in the nocuda build first, for best support. Alternatively, you can download our rolling ROCm binary here if you use Linux.
If you're on a modern MacOS (M-Series) you can use the koboldcpp-mac-arm64 MacOS binary.
Click here for .gguf conversion and quantization tools

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.

koboldcpp-1.105.4

new year edition

• NEW: Added --gendefaults, accepts a JSON dictionary where you can specify any API fields to append or overwrite (e.g. step count, temperature, top_k) on incoming payloads. Incoming API payloads will have this modification applied. This can be useful when using frontends that don't behave well, as you will be able to override or correct whatever fields they send to koboldcpp.
  • Note: If this marks the horde worker with a debug flag if used on AI Horde.
  • --sdgendefaults has been deprecated and merged into this flag
• Added support for a new "Adaptive-P" sampler by @MrJackSpade, a sampler that allows selecting lower probability tokens. Recommended to use together with min-P. Configure with adaptive target and adaptive decay parameters. This sampler may be subject to change in future.
• StableUI SDUI: Fixed generation queue stacking, allowed requesting AVI formatted videos (enable in settings first), added a dismiss button, various small tweaks
• Minor fixes to tool calling
• Added support for Ovis Image and new Qwen Image Edit, added support for TAEHV for WAN VAE (you can use it with Wan2.2 videos and Qwen Image/Qwen Image Edit, simply enable "TAE SD" checkbox or --sdvaeauto, greatly saves memory), thanks @wbruna for the sync.
• Fixed LoRA loading issues with some Qwen Image LoRAs
• --autofit now allocates some extra space if used with multiple models (image gen, embeddings etc)
• Improved snapshotting logic with --smartcache for RNN models.
• Attempted to fix tk scaling on some systems.
• Renamed KCPP launcher's Tokens tab to Context, moved Flash Attention toggle into hardware tab
• Updated Kobold Lite, multiple fixes and improvements
  • Added support for using remote http MCP servers for tool calling. KoboldCpp based MCP may be added at a later date.
• Merged fixes, model support, and improvements from upstream

Hotfix 1.105.1 - Allow configuring number of smartcache slots, updated lite + SDUI, handle tool calling images from remote MCP responses.
Hotfix 1.105.2 - Fixed various minor bugs, allow transcribe to be used with an LLM with audio projector.
Hotfix 1.105.3 - Merged fix for CUDA MoE CPU regression
Hotfix 1.105.4 - Merged vulkan glm4.6 fix

Important Notice: The CLBlast backend may be removed soon, as it is very outdated and no longer receives and updates, fixes or improvements. It can be considered superceded by the Vulkan backend. If you have concerns, please join the discussion here.

Download and run the koboldcpp.exe (Windows) or koboldcpp-linux-x64 (Linux), which is a one-file pyinstaller for NVIDIA GPU users.
If you have an older CPU or older NVIDIA GPU and koboldcpp does not work, try oldpc version instead (Cuda11 + AVX1).
If you don't have an NVIDIA GPU, or do not need CUDA, you can use the nocuda version which is smaller.
If you're using AMD, we recommend trying the Vulkan option in the nocuda build for best support.
If you're on a modern MacOS (M-Series) you can use the koboldcpp-mac-arm64 MacOS binary.
Click here for .gguf conversion and quantization tools

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.

koboldcpp-1.104

calm before the storm edition

• NEW: Added --smartcache adapted from @Pento95: This is a 2-in-1 dynamic caching solution that intelligently creates KV state snapshots automatically. Read more here
  • This will greatly speed up performance when different contexts are swapped back to back (e.g. hosting on AI Horde or shared instances).
  • Also allows snapshotting when used with a RNN or Hybrid model (e.g. Qwen3Next, RWKV) which avoids having to reprocess everything.
  • Reuses the KV save/load states from admin mode. Max number of KV states increased to 6.
• NEW: Added --autofit flag which utilizes upstream's "automatic GPU fitting (-fit )" behavior from ggml-org#16653. Note that this flag overwrites all your manual layer configs and tensor overrides and is not guaranteed to work. However, it can provide a better automatic fit in some cases. Will not be accurate if you load multiple models e.g. image gen.
• Pipeline parallelism is no longer the default, instead its now a flag you can enable with --pipelineparallel. Only affects multi-gpu setups, faster speed at the cost of memory usage.
• Key Improvement - Vision Bugfix: A bug in mrope position handling has been fixed, which improves vision models like Qwen3-VL. You should now see much better visual accuracy in some multimodal models compared to earlier koboldcpp versions. If you previously had issues with hallucinated text or numbers, it should be much better now.
• Increased default gen amount from 768 to 896.
• Deprecated obsolete --forceversion flag.
• Fixed safetensors loading for Z-Image
• Fixed image importer in SDUI
• Capped cfg_scale to max 3.0 for Z-Image to avoid blurry gens. If you want to override this, set remove_limits to 1 in your payload or inside --sdgendefaults.
• Removed cc7.0 as a CUDA build target, Volta (V100) will fall back to PTX from cc6.1
• Tweaked branding in llama.cpp UI to make it clear it's not llama.cpp
• Added indentation to .kcpps configs
• Updated Kobold Lite, multiple fixes and improvements
• Merged fixes and improvements from upstream
  • GLM4.6V and GLM4.6V Flash are now supported. You can get the model and the mmproj here.
  • If you want to test out GLM ASR Nano, I've made quants here, works best with short audio clips, for longer audio please stick to Whisper.

Important Notice: The CLBlast backend may be removed soon, as it is very outdated and no longer receives and updates, fixes or improvements. It can be considered superceded by the Vulkan backend. If you have concerns, please join the discussion here.

Download and run the koboldcpp.exe (Windows) or koboldcpp-linux-x64 (Linux), which is a one-file pyinstaller for NVIDIA GPU users.
If you have an older CPU or older NVIDIA GPU and koboldcpp does not work, try oldpc version instead (Cuda11 + AVX1).
If you don't have an NVIDIA GPU, or do not need CUDA, you can use the nocuda version which is smaller.
If you're using AMD, we recommend trying the Vulkan option in the nocuda build for best support.
If you're on a modern MacOS (M-Series) you can use the koboldcpp-mac-arm64 MacOS binary.
Click here for .gguf conversion and quantization tools

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.

koboldcpp-1.103

• NEW: Added support for Flux2 and Z-Image Turbo! Another big thanks to @leejet for the sd.cpp implementation and @wbruna for the assistance with testing and merging.
  • To obtain models for Z-Image (Most recommended, lightweight):
    • Get the Z-Image Image model here
    • Get the Z-Image VAE here, which is the same vae as FluxOne.
    • Get the Z-Image text encoder here (load this as Clip 1)
    • Alternative: Load this template to download all 3 automatically
  • To obtain models for Flux2 (Not recommended as this model is huge so i will link the q2k. Remember to enable cpu offload. Running anything larger requires a very powerful GPU):
    • Get the Flux 2 Image model here
    • Get the Flux 2 VAE here
    • Get the Flux 2 text encoder here, load this as Clip 1
• NEW: Mistral and Ministral 3 model support has been merged from upstream.
• Improved "Assistant Continue" in llama.cpp UI mode, now can be used to continue partial turns.
  • We have added prefill support to chat completions if you have /lcpp in your URL (/lcpp/v1/chat/completions), the regular chat completions is meant to mimick OpenAI and does not do this. Point your frontend to the URL that most fits your use case, we'd like feedback on which one of these you prefer and if the /lcpp behavior would break an existing use case.
• Minor tool calling fix to avoid passing base64 media strings into the tool call.
• Tweaked resizing behavior of the launcher UI.
• Added a secondary terminal UI to view the console logging (only for Linux), can be used even when not launched from CLI. Launch this auxiliary terminal from the Extras tab.
• AutoGuess Template fixes for GPT-OSS and Kimi
• Fixed a bug with --showgui mode being saved into some configs
• Updated Kobold Lite, multiple fixes and improvements
• Merged fixes and improvements from upstream

Download and run the koboldcpp.exe (Windows) or koboldcpp-linux-x64 (Linux), which is a one-file pyinstaller for NVIDIA GPU users.
If you have an older CPU or older NVIDIA GPU and koboldcpp does not work, try oldpc version instead (Cuda11 + AVX1).
If you don't have an NVIDIA GPU, or do not need CUDA, you can use the nocuda version which is smaller.
If you're using AMD, we recommend trying the Vulkan option in the nocuda build for best support.
If you're on a modern MacOS (M-Series) you can use the koboldcpp-mac-arm64 MacOS binary.
Click here for .gguf conversion and quantization tools

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.

koboldcpp-1.102.3

cold november rain edition

• New: Now bundles the llama.cpp UI into KoboldCpp, as an extra option for those who prefer it. Access it at http://localhost:5001/lcpp
  • The llama.cpp UI is designed strongly for assistant use-cases and provides a ChatGPT like interface, with support for importing documents like .pdf files. It can be accessed in parallel to the usual KoboldAI Lite UI (which is recommended for roleplay/story writing) and does not take up any additional resources while not in use.
• New: Massive universal tool calling improvement from @Rose22, with the new format KoboldCpp is now even better at calling tools and using multiple tools in sequence correctly. Works automatically with all tool calling capable frontends (OpenWebUI / SillyTavern etc) in chat completions mode and may work on models that normally do not support tool calling (in the correct format).
• New: Added support for jinja2 templates via /v1/chat/completions, for those that have been asking for it. There are 3 modes:
  • Current Default: Uses KoboldCpp ChatAdapter templates, KoboldCpp universal toolcalling module (current behavior, most recommended).
  • Using --jinja: Uses jinja2 template from GGUF in chat completions mode for normal messages, uses KoboldCpp universal toolcalling module. Use this only if you love jinja. There are GGUF models on Huggingface which will explicitly mention --jinja must be used to get normal results, this does not apply to KoboldCpp as our regular modes cover these cases.
  • Using --jinja_tools: Uses jinaja2 template from GGUF in chat completions mode for all messages and tools. Not recommended in general. In this mode the model and frontend are responsible for the compatibility.
• Synced and updated Image Generation to latest stable-diffusion.cpp, big thanks to @wbruna. Please report any issues you encounter.
• Updated google Colab notebook with easier default selectable presets, thanks @henk717
• Allow GUI launcher window to be resized slightly larger horizontally, in case some text gets cut off.
• Fixed a divide by zero error with audio projectors
• Added Vulkan support for whisper.
• Filename insensitive search when selecting chat completion adapters
• Fixed an old bug that caused mirostat to swap parameters. To get the same result as before, swap values for tau and eta.
• Added a debug command --testmemory to check what values auto GPU detection retrieves (not needed for most)
• Now serves KoboldAI Lite UI gzipped to browsers that can support it, for faster UI loading.
• Added sampler support for smoothing curve
• Updated Kobold Lite, multiple fixes and improvements
  • Web Link-sharing now defaults to dpaste.com as dpaste.org is shut down
  • Added option to save and load custom scenarios in a Scenario Library (like stories but do not contain most settings)
  • Allow single-turn deletion and editing in classic theme instruct mode (click on the icon)
  • Better turn chunking and repacking after editing a message
• Merged new model support, fixes and improvements from upstream

Hotfix 1.102.2 - Try to fix some issues with flash attention, fixed media attachments in jinja mode
Hotfix 1.102.3 - Merged Qwen3Next support. Note that you need to use batch size 512 or less.

Separately our docker image has been updated to a newer faster Vulkan driver for some AMD GPU's, if you use our docker image a manual docker pull is recommended as these drivers are not always covered by the automatic updates.

Download and run the koboldcpp.exe (Windows) or koboldcpp-linux-x64 (Linux), which is a one-file pyinstaller for NVIDIA GPU users.
If you have an older CPU or older NVIDIA GPU and koboldcpp does not work, try oldpc version instead (Cuda11 + AVX1).
If you don't have an NVIDIA GPU, or do not need CUDA, you can use the nocuda version which is smaller.
If you're using AMD, we recommend trying the Vulkan option in the nocuda build for best support.
If you're on a modern MacOS (M-Series) you can use the koboldcpp-mac-arm64 MacOS binary.
Click here for .gguf conversion and quantization tools

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.

koboldcpp-1.101.1

very spooky edition

• Support for Qwen3-VL is merged - For a quick test, get the Qwen3-VL-2B-Instruct model here and the mmproj here. Larger versions exist, but this will work well enough for simple tasks.
• Added Qwen Image and Qwen Image Edit - Support is now officially available for Qwen Image generation models. These have much better prompt adherence than SDXL or even Flux. Here's how to set up qwen image edit:
  • Get the Qwen Image Edit 2509 model here and load it as the image gen model
  • Get the Qwen Image VAE and load it as VAE
  • Get Qwen2.5-VL-7B-Instruct and load it as Clip-1
  • Get Qwen2.5-VL-7B mmproj and load it as Clip-2
  • That's basically it! You can now generate images normally in Kobold or any connected frontend.
  • You can do image editing using the SDUI (http://localhost:5001/sdui) by uploading a source Reference Image and asking the AI to make changes. Alternatively, providing no reference image allows normal txt2img generation.
  • To use the non-edit version of Qwen Image, you can use these models instead
  • For a quick setup, you can use this .kcppt launcher template by @henk717
• Added aliases for the OpenAI compatible endpoints without /v1/ prefix.
• Supports using multiple --overridekv, split by commas.
• Renamed --blasbatchsize to just --batchsize (old name will still work)
• Made preview in GUI GPU layer count more accurate, no more +2 extra layers.
• Added experimental support for fractional scaling in the GUI launcher for Wayland on GNOME. You're still recommended to use KDE or disable fractional scaling for better results.
• Image generation precision fixes and fallbacks. SDUI also now supports copy with right click on the image preview.
• Added selection for image generation scheduler
• Added support for logprobs streaming in openai chat completions API (sent at end)
• Added VITS api server compatibility endpoint
• PyInstaller upgraded from 5.11 to 5.12 to fix a crashing bug
• Added Horde worker Job stats by @xzuyn
• Updated Kobold Lite, multiple fixes and improvements
  • New: Added branching support! You can now create ST style "branches" in the same story, allowing you to explore multiple alternate possibilities without requiring multiple save files. You can create and delete branches at any point in your story and swap between them at will.
  • Better inline markdown and code rendering
  • Better turn history segmenting after leaving edit mode, also improved AutoRole turn packing
  • Improve trim sentences behavior, improve autoscroll behavior, improve mobile detection
  • Added ccv3 tavern card support
  • Aborted gens will now request for logprobs if enabled
• Merged new model support, fixes and improvements from upstream, including some Vulkan speedups from occam
• NOTE: Qwen3Next support is NOT merged yet. It is still undergoing development upstream, follow it here: ggml-org#16095

Hotfix 1.101.1 - Fixed a regression with rowsplit, fixed issue loading very old mmproj files, fixed a crash with qwen image edit.

Starting at 1.101.1 we have upgraded the bundled ROCm library of our ROCm Linux Binary to 7.1, this will have an impact on which GPU's are supported. You should now be able to use KoboldCpp on your 9000 GPU on Linux without having to compile from source. If your system's driver was capable of running the last ROCm release updating drivers is not required, it will automatically use ROCm 7.1 even if you have an older ROCm installed.

Download and run the koboldcpp.exe (Windows) or koboldcpp-linux-x64 (Linux), which is a one-file pyinstaller for NVIDIA GPU users.
If you have an older CPU or older NVIDIA GPU and koboldcpp does not work, try oldpc version instead (Cuda11 + AVX1).
If you don't have an NVIDIA GPU, or do not need CUDA, you can use the nocuda version which is smaller.
If you're using AMD, we recommend trying the Vulkan option in the nocuda build first, for best support. Alternatively, you can try koboldcpp_rocm at YellowRoseCx's fork here if you are a Windows user or download our rolling ROCm binary here if you use Linux.
If you're on a modern MacOS (M-Series) you can use the koboldcpp-mac-arm64 MacOS binary.
Click here for .gguf conversion and quantization tools

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.