github unslothai/unsloth v0.1.48-beta
DeepSeek-V4 + NVFP4 Exporting
on GitHub

6 hours ago

Unsloth Studio can now export to NVFP4, FP8, imatrix GGUFs after training, can act as a llama-swap API system, includes Japanese and Brazilian language support, includes MLX, safetensors tool calling + healing support and much more! Unsloth core makes GRPO 1.3x faster, have HTTP fallback for stalled downloads, better offline mode, makes MoE training 3 to 5x faster, and fixes many bugs! This release series uses unsloth>=2026.7.1.

DeepSeek-V4-Flash is now supported with Thinking toggles and with all our fixes including improved chat template!
Deepseek-v4 in unsloth

Smarter OpenAI-Compatible API Serving

Run one local API endpoint across with safer automatic model swapping and better agent-tool recovery.

  • API requests can opt into model auto switching, so a request for a different downloaded local GGUF can load and serve that model automatically.
  • The model swap path is safe by default: unknown model names keep using the current model and do not trigger surprise downloads.
  • /v1/models now returns clean model IDs and the local GGUF catalog, so API clients do not see local .gguf file paths.
  • Idle auto-unload can free VRAM after inactivity while still reloading the last model on the next API request.
  • API clients can control tool-call healing per request and opt into the extra nudge retry when a model tries to call a tool but returns malformed markup.

Export Improvements

Exports are more flexible and avoid more unnecessary downloads.

  • Unsloth now lets you select multiple export formats at once.
  • Unsloth now supports portable FP8/INT8 exports, GGUF LoRA, and source-matched exports.
  • save_pretrained_merged now supports compressed FP8/FP4 exports.
  • The Unsloth export UI now includes imatrix GGUF and compressed export options.
  • Exporting multiple checkpoints now avoids more repeated base-model downloads.
  • FP8, INT8, and GGUF-LoRA exports now respect trust_remote_code.
  • GGUF export now handles models with missing quantization settings more reliably.

RAG and File Chat

Chat with files should be more useful on real documents.

  • RAG attachments can now use whole-document context.
  • File chat now reads more PDFs and Word documents correctly, including right-to-left text, Indic text, and DOCX tables.
  • Local RAG checks are less likely to fail because of proxy settings.
  • The embedding model is now customizable, with Hugging Face search and a reorganized settings tab.

Unsloth Polish and Reliability

Unsloth is smoother and more reliable during everyday use.

  • Training and chat progress are less likely to freeze silently during long runs.
  • Compare mode starts more reliably.
  • Switching or cancelling models during loading is less likely to get stuck.
  • Hub browsing now recovers better from invalid Hugging Face tokens and shows clearer local file paths.
  • Hub Discover now shows all models by default, with a cleaner model picker and a fits-on-device filter.
  • Project export menus are clearer, with combined project exports and individual chat exports grouped separately.
  • Unsloth training runs now show project names.
  • Guided tours, reasoning timers, thinking stops, settings, file dialogs, and update screens now feel cleaner and more consistent.
  • Japanese and Portuguese (Brazil) are now available in the Unsloth UI.
  • Installer and package checks were tightened to catch more unsafe or unexpected dependency changes.

Installer, Hardware and Platform Fixes

Unsloth installs and runs more reliably across different machines, GPUs, and network setups.

  • Installer pins were updated to unsloth>=2026.6.9.
  • macOS installs no longer require CMake or Homebrew when a prebuilt llama.cpp is available.
  • Apple Silicon installs now handle paths with spaces more reliably and size GGUF context for unified memory.
  • macOS installs work better behind corporate TLS-inspection proxies.
  • Linux and macOS path handling is more reliable when folders contain spaces.
  • Windows ROCm RAG embedding avoids a torchao import crash.
  • Windows Unsloth startup handles UTF-8 text more reliably.
  • ROCm-on-WSL now supports discrete Radeon RDNA 3/4 GPUs, not just Strix Halo.
  • Blackwell sm_100 and sm_103 data-center GPUs now use the correct llama.cpp prebuilt selection.
  • GGUF fit checks now reserve memory for CUDA context and vision/model overhead more accurately.
  • Tensor parallelism fixed for vision and mmproj GGUF models.
  • Existing local llama.cpp builds can now be reused with --with-llama-cpp-dir.

Training, Models and Kernels

Training and model loading are more reliable across more model types, GPUs, and fine-tuning setups.

  • GRPO training now supports sequence packing by default for old/ref log-probability calculations.
  • GRPO now avoids repeating the same shared prompt across grouped completions.
  • GRPO logit scaling now works correctly with DDP-wrapped models.
  • Full fine-tuning now uses the correct precision on V100 and other GPUs without bf16 support.
  • RL trainers no longer reject valid full fine-tuning precision settings.
  • Unsloth gradient checkpointing is no longer silently disabled by TrainingArguments.
  • DDP training no longer crashes from a CPU-resident RoPE buffer.
  • MoE LoRA detection now targets the correct expert MLP layers.
  • Grouped MoE can now turn on automatically for loaded and PEFT models.
  • FP8 quantization now handles odd tensor shapes and scale formats more reliably.
  • FP8 dequant kernels now use safer offset handling.
  • Llama 3 RoPE scaling is preserved with Transformers v5.
  • LoRA reloads continue to work with PEFT 0.19.
  • fast_generate now shows a clearer error when vLLM-style inputs are used without fast inference.

Updating Unsloth

To update Unsloth or install a fresh Unsloth Unsloth, use the commands below:
macOS, Linux, WSL: 

curl -fsSL https://unsloth.ai/install.sh | sh

Windows: 

irm https://unsloth.ai/install.ps1 | iex

What's Changed in Unsloth

New Contributors

Full Changelog: v0.1.471-beta...v0.1.48-beta

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