LTX2.3 10Eros GGUF

--- base_model: TenStrip/LTX2.3-10Eros library_name: gguf pipeline_tag: image-to-video tags: - gguf - quantized --- # LTX2.3-10Eros - GGUF This repository contains GGUF format model files for [TenStrip's LTX2.3-10Eros](https://huggingface.co/TenStrip/LTX2.3-10Eros). ## Model Details * **Original Model:** [TenStrip/LTX2.3-10Eros](https://huggingface.co/TenStrip/LTX2.3-10Eros) * **Format:** GGUF ## Available Quantizations The following quantization tiers are provided to accommodate different hardware capabilities and VRAM constraints. | Filename | Quantization Type | Size | Recommended Use | |:---|:---|:---|:---| | `10Eros_v1-Q8_0.gguf` | Q8_0 (8-bit) | 22.8 GB | Extremely high quality, near unquantized performance. Requires high VRAM. | | `10Eros_v1-Q6_K.gguf` | Q6_K (6-bit) | 17.8 GB | Very high quality, minimal precision loss. | | `10Eros_v1-Q5_K_M.gguf` | Q5_K_M (5-bit) | 16.1 GB | Excellent balance of quality and performance. | | `10Eros_v1-Q5_K_S.gguf` | Q5_K_S (5-bit) | 15.0 GB | Slightly smaller 5-bit variant for strict memory limits. | | `10Eros_v1-Q4_K_M.gguf` | Q4_K_M (4-bit) | 14.3 GB | Recommended standard. Fast inference with very low quality degradation. | | `10Eros_v1-Q4_K_S.gguf` | Q4_K_S (4-bit) | 13.2 GB | Smaller 4-bit variant, slightly lower quality than K_M. | | `10Eros_v1-Q4_0.gguf` | Q4_0 (4-bit) | 13.0 GB | Legacy 4-bit quant. Very fast inference but higher perplexity than K-quants. | | `10Eros_v1-Q3_K_M.gguf` | Q3_K_M (3-bit) | 11.1 GB | High compression. Best for constrained environments with limited RAM/VRAM. | | `10Eros_v1-Q3_K_S.gguf` | Q3_K_S (3-bit) | 10.3 GB | Maximum compression. Lowest footprint but highest quality loss. |