Fixed gguf-vram-estimator.py path
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@@ -21,7 +21,7 @@ This repo provides a tool, **`gguf-vram-estimator.py`**, which reads a `.gguf` m
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Make sure you have the estimator script (in `tools/`):
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```sh
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python3 tools/gguf-vram-estimator.py <path-to-model.gguf>
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gguf-vram-estimator.py <path-to-model.gguf>
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```
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* Supply one or more context lengths to get the corresponding VRAM footprint.
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@@ -34,7 +34,7 @@ python3 tools/gguf-vram-estimator.py <path-to-model.gguf>
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### 3.1 Llama-4-Scout 17B Q4\_K\_XL, up to 1M tokens
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```
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$ python3 tools/gguf-vram-estimator.py models/llama-4-scout-17b-16e/Q4_K_XL/Llama-4-Scout-17B-16E-Instruct-UD-Q4_K_XL-00001-of-00002.gguf --contexts 4096 32768 1048576
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$ gguf-vram-estimator.py models/llama-4-scout-17b-16e/Q4_K_XL/Llama-4-Scout-17B-16E-Instruct-UD-Q4_K_XL-00001-of-00002.gguf --contexts 4096 32768 1048576
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--- Model 'Llama-4-Scout-17B-16E-Instruct' ---
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Max Context: 10,485,760 tokens
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@@ -58,7 +58,7 @@ Incl. Overhead: 2.00 GiB
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### 3.2 Qwen3-235B Q3\_K XL, high context
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```
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$ python3 tools/gguf-vram-estimator.py models/qwen3-235B-Q3_K-XL/UD-Q3_K_XL/Qwen3-235B-A22B-Instruct-2507-UD-Q3_K_XL-00001-of-00003.gguf --contexts 65536 131072 262144
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$ gguf-vram-estimator.py models/qwen3-235B-Q3_K-XL/UD-Q3_K_XL/Qwen3-235B-A22B-Instruct-2507-UD-Q3_K_XL-00001-of-00003.gguf --contexts 65536 131072 262144
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--- Memory Footprint Estimation ---
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Context Size | Context Memory | Est. Total VRAM
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