Unverified50% confidenceReleaseExact time
North-South Grid 4.3-33B has introduced GGUF-quantized full-weight support, with the base model supporting contexts up to 512K tokens and providing configuration examples for Llama.cpp and Ollama.
1
Sources
50%
Confidence
Medium-term (~90 days)
Relevance
10/30/2026
First Seen
Valid until: 1/28/2027
Sources
Related Entities
Related Claims
Verifiedllama.cpp通过GGUF格式对模型权重进行4-bit、8-bit等量化压缩，大幅降低显存和内存占用72% similarUnverifiedFor users with limited VRAM, it is recommended to prioritize GGUF versions with 4-bit or 5-bit quantization to achieve a balance between performance and quality.70% similarUnverifiedQuantization formats such as GGUF and AWQ can compress models with tens of billions of parameters to a size runnable on consumer-grade GPUs while maintaining near-original performance.66% similarUnverifiedWith Unsloth's 1-bit GGUF quantization, GLM-5.3-Flash can run on a combined 102 GB of RAM and VRAM, with a context length of 1M tokens.66% similarVerifiedThe GGUF format supports multiple precision levels such as 4-bit and 8-bit, and can compress the memory footprint of a 7-billion-parameter model from approximately 14 GB (FP16) to approximately 4 GB (Q4_K_M quantization), with inference accuracy loss typically within 1–3%.66% similar
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