Expired60% confidenceFactExact time
The tests used Q4KM quantized versions of both models, both in Unsloth's GGUF format, running on llama.cpp.
2
Sources
60%
Confidence
Medium-term (~90 days)
Relevance
7/9/2026
First Seen
Valid until: 10/7/2026(expired)
Sources
16GB VRAM Showdown: Ornith 35B vs Qwen 35B — Full Benchmark Comparison
bilibili程序员-智能译站7/7/2026
Related Claims
UnverifiedGGUF is a quantized model format introduced by the llama.cpp project; Q4_K_M denotes 4-bit quantization, which can reduce VRAM usage by approximately 75% compared to F16.72% similarUnverifiedThe local deployment uses llama.cpp as the inference backend with Unsloth's 4-bit quantized model.69% similarVerifiedOllama natively supports the GGUF format, and most models have been pre-quantized to specifications such as Q4_K_M or Q8_0.69% similarUnverifiedThe Qwen3.8-27B model is available in multiple formats including Safetensors, GGUF, NVFP4, NVFP4 GGUF variants, and GPTQ-Int4 quantized versions.69% similarVerifiedThe Unsloth team released a new Qwen3.8-27B GGUF model based on the Dynamic v3 quantization scheme, achieving an additional 10% improvement in top-1% accuracy while maintaining the same model size.68% similar
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