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llama.cpp and other GGUF-compatible inference clients (such as LM Studio, Ollama, AnythingLLM, etc.).| File Name | Type | File Size | Recommended RAM/VRAM | Description |
|---|---|---|---|---|
JT-Math-8B-Thinking-Q8_0.gguf | Q8_0 Quantization | ~8.5 GB | >= 12 GB | Recommended Choice. Almost lossless 8-bit quantization that perfectly balances inference speed and model performance. Suitable for most modern CPUs and GPUs. |
JT-Math-8B-Thinking-F16.gguf | F16 Native | ~16.1 GB | >= 24 GB | Lossless Version. Retains the original Float16 precision. Ideal for resource-rich environments (e.g., 24GB VRAM GPUs) where any quantization loss is unacceptable. |