Qwen2.5 32B Instruct Abliterated vs Qwen2.5 14B Instruct

Side-by-side comparison of VRAM requirements, quantization, context length, and hardware compatibility.

Qwen2.5 14B Instruct

Alibaba · 14.8B

Chat

Specifications

Qwen2.5 32B Instruct AbliteratedQwen2.5 14B Instruct
Parameters32B14.8B
Context33K33K
ArchitectureQwen2ForCausalLMQwen2ForCausalLM
LicenseApache 2.0Apache 2.0
Downloads2.4K2.2M
ReleasedApr 2025Sep 2024

VRAM by Quantization: Qwen2.5 32B Instruct Abliterated vs Qwen2.5 14B Instruct

QuantizationBitsQwen2.5 32B Instruct Abliterated VRAMQwen2.5 14B Instruct VRAM
Q2_K3.4014.4 GB7.0 GB
Q3_K_M3.9016.4 GB7.9 GB
Q3_K_S3.5014.8 GB7.2 GB
Q4_04.0016.8 GB8.1 GB
Q4_K_M4.8020.0 GB9.6 GB
Q5_K_M5.7023.6 GB11.2 GB
Q6_K6.6027.2 GB12.9 GB
Q8_08.0032.8 GB15.5 GB

Verdict

Qwen2.5 14B Instruct needs less VRAM at Q4_K_M (9.6 GB vs 20.0 GB), so it fits on smaller GPUs. Qwen2.5 14B Instruct is the more widely downloaded of the two.

Frequently Asked Questions

Which needs less VRAM, Qwen2.5 32B Instruct Abliterated or Qwen2.5 14B Instruct?

At Q4_K_M, Qwen2.5 32B Instruct Abliterated needs 20.0 GB and Qwen2.5 14B Instruct needs 9.6 GB, so Qwen2.5 14B Instruct is the lighter option to run locally.

Which has a longer context window, Qwen2.5 32B Instruct Abliterated or Qwen2.5 14B Instruct?

Qwen2.5 32B Instruct Abliterated supports 32,768 tokens and Qwen2.5 14B Instruct supports 32,768 tokens.

What is the difference between Qwen2.5 32B Instruct Abliterated and Qwen2.5 14B Instruct?

Qwen2.5 32B Instruct Abliterated is a 32B model from huihui-ai (Qwen 2.5 family), while Qwen2.5 14B Instruct is a 14.8B model from Alibaba (Qwen 2.5 family). Compare their VRAM requirements above to see which fits your GPU or Mac.