Local LLM beginner questions Qwen 3.5 benchmarks and pricing

Parameter count is no longer a reliable proxy for intelligence, leading to understandable confusion for newcomers navigating open-weight model benchmarks and pricing.

• –The 27B model's superior benchmark performance over the 35B likely stems from architectural differences, better training data mixtures, or more rigorous fine-tuning.
• –Higher API costs for smaller models can result from lower inference optimization, lower batching efficiency, or lack of provider caching compared to widely used larger models.
• –Running a 27B model locally with acceptable speeds requires significant VRAM, pushing users toward 24GB GPUs (like the RTX 3090/4090) or Apple Silicon with large unified memory.