Impish_QWEN_7B-Q4_K_M isn’t working on KoboldCcp. I have Qwen2.5-7B.i1-Q4_K_M downloaded on my computer, but it still keeps on saying that the text model cannot load. How do I fix it?
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Without specific error details, I can only offer very general and broad advice…
Most likely cause: KV-cache memory blow-up from long context
Both of the models you mention are long-context Qwen2-family GGUFs, and KoboldCpp/llama.cpp allocates the KV cache up-front when the model loads. If the loader/UI is trying to use anything close to the model’s max context, the KV cache allocation can fail and KoboldCpp reports that the text model cannot load.
- Qwen2.5-7B (base) lists 131,072 tokens context length. (Hugging Face)
- The “1M” Qwen2.5 variants support ~1,010,000 tokens context. (Hugging Face)
- There are known cases where using the model’s large trained context (or auto-using it when
--ctx-sizeisn’t set) causes OOM during KV allocation, and setting a smaller context fixes it. (GitHub)
This is especially relevant if your “Impish” model is actually the Impish_QWEN_7B-1M line (it is based on Qwen2.5-7B-Instruct-1M in the model tree). (Hugging Face)
Fix (do this first)
-
Before loading the model in KoboldCpp, set Context Size to something small:
- Start with 8192 (or 4096 if you’re tight on VRAM/RAM).
- Then try 16384 if it loads and you want more context.
-
If you’re using GPU offload:
- Start with 0 GPU layers (CPU-only) to confirm it loads.
- Then increase GPU layers gradually.
CLI example (works as a sanity test):
-
Linux/macOS:
./koboldcpp --model "/path/Qwen2.5-7B.i1-Q4_K_M.gguf" --contextsize 8192 --gpulayers 0 -
Windows:
koboldcpp.exe --model "C:\path\Qwen2.5-7B.i1-Q4_K_M.gguf" --contextsize 8192 --gpulayers 0
If this works, your original failure was almost certainly KV cache allocation / memory pressure (not the GGUF being “invalid”).
Second common cause: KoboldCpp version/build mismatch
If you’re on an older KoboldCpp build (or the wrong binary for your CPU), Qwen2-family GGUFs and/or newer GGUF metadata can fail to load. The KoboldCpp release notes explicitly call out using oldpc builds for older CPUs and nocuda builds when CUDA isn’t applicable. (GitHub)
Fix
-
Download the latest KoboldCpp release from the official releases page. (GitHub)
-
Pick the correct binary:
- oldpc if your CPU doesn’t have AVX2 (common reason for “won’t load” symptoms)
- nocuda if you don’t use NVIDIA CUDA
- Vulkan option if you’re on AMD/no CUDA (per release guidance). (GitHub)
Third: wrong file / corrupt download / model variant confusion
Verify you have the expected GGUF
For mradermacher/Qwen2.5-7B-i1-GGUF, the listing shows i1-Q4_K_M exists and is ~4.7–4.9 GB in size. (Hugging Face)
If your local file is much smaller, it may be incomplete/corrupt.
If you accidentally grabbed a “1M” model
If the model is a 1M-context variant (Impish “-1M”, or Qwen2.5 “-1M”), you generally should not try to load it at anywhere near 1M context on consumer hardware; always set a smaller context first. (Hugging Face)
Try a non-imatrix (“static”) quant as a fallback
The same author notes static quants are available separately (often the most compatible choice). (Hugging Face)
What to look for in the console (to confirm)
If you see lines like “failed to allocate buffer for kv cache” or CUDA/Vulkan allocation failures during load, that confirms the context/KV cache memory issue. (Framework Community)
The local file is much smaller. So, I think that’s the problem. However, from what I’ve heard, I need to run a 7B Q4_K_M as my daily driver to get the best writing quality and the fastest responses and Qwen2.5-7B-i1-GGUF only has one 7B Q4_K_M model I can download, the incomplete/corrupt version. What do I do about that?
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