Failed to load model: GGUF version mismatch

Q: How do you fix "Failed to load model: GGUF version mismatch"?

**1. Update llama.cpp / Ollama / LM Studio** to the latest release: ```bash # llama.cpp from source cd llama.cpp && git pull && make clean && make GGML_CUDA=1 -j # Homebrew brew upgrade llama.cpp # Ollama curl -fsSL https://ollama.com/install.sh | sh # LM Studio: in-app "Check for updates" ``` **2. If you can't update the runner**, find an older GGUF of the same model. Hugging Face shows multiple uploaders per model — one of them usually has a v2-format file. **3. Convert from safetensors yourself** with the matching llama.cpp version: ```bash python convert_hf_to_gguf.py /path/to/hf-model --outfile model.gguf --outtype f16 ./llama-quantize model.gguf model.Q4_K_M.gguf Q4_K_M ``` **4. Check the GGUF version** from the file header: ```bash xxd model.gguf | head -1 # Bytes 4-7 are the version (little-endian) ```

llama_model_load: error loading model: this GGUF file is version X but llama.cpp supports up to version Y

By Eruo Fredoline · Last verified May 8, 2026

Cause

GGUF has been versioned several times: v1 (early 2024), v2 (mid-2024), v3 (late 2024). Each bump added fields (chat templates, tokenizer config, KV cache hints). Older llama.cpp builds reject newer GGUFs; very old GGUFs may also be rejected by current builds if backward compatibility was dropped for a deprecated field.

A common form: download a fresh quant from a recent uploader (bartowski, lmstudio-community), point an old llama.cpp at it, and hit this on load.

Solution

1. Update llama.cpp / Ollama / LM Studio to the latest release:

# llama.cpp from source
cd llama.cpp && git pull && make clean && make GGML_CUDA=1 -j

# Homebrew
brew upgrade llama.cpp

# Ollama
curl -fsSL https://ollama.com/install.sh | sh

# LM Studio: in-app "Check for updates"

2. If you can't update the runner, find an older GGUF of the same model. Hugging Face shows multiple uploaders per model — one of them usually has a v2-format file.

3. Convert from safetensors yourself with the matching llama.cpp version:

python convert_hf_to_gguf.py /path/to/hf-model --outfile model.gguf --outtype f16
./llama-quantize model.gguf model.Q4_K_M.gguf Q4_K_M

4. Check the GGUF version from the file header:

xxd model.gguf | head -1
# Bytes 4-7 are the version (little-endian)

Related errors

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