Qwen2.5 72B Instruct Abliterated vs Qwen2.5 1.5B Quantized.w8a8

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

Qwen2.5 72B Instruct Abliterated

huihui-ai · 72.7B

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Qwen2.5 1.5B Quantized.w8a8

RedHatAI · 1.8B

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Specifications

Qwen2.5 72B Instruct AbliteratedQwen2.5 1.5B Quantized.w8a8
Parameters72.7B1.8B
Context33K33K
ArchitectureQwen2ForCausalLMQwen2ForCausalLM
LicenseOtherApache 2.0
Downloads360.8K1.3M
ReleasedJun 2025Dec 2024

VRAM by Quantization: Qwen2.5 72B Instruct Abliterated vs Qwen2.5 1.5B Quantized.w8a8

QuantizationBitsQwen2.5 72B Instruct Abliterated VRAMQwen2.5 1.5B Quantized.w8a8 VRAM
Q2_K3.4031.9 GB1.1 GB
Q3_K_M3.9036.4 GB1.2 GB
Q3_K_S3.501.1 GB
Q4_04.001.3 GB
Q4_K_M4.8044.6 GB1.4 GB
Q5_K_M5.7052.8 GB1.6 GB
Q6_K6.6061.0 GB1.8 GB
Q8_08.0073.7 GB2.1 GB

Verdict

Qwen2.5 1.5B Quantized.w8a8 needs less VRAM at Q4_K_M (1.4 GB vs 44.6 GB), so it fits on smaller GPUs. Qwen2.5 1.5B Quantized.w8a8 is the more widely downloaded of the two.

Frequently Asked Questions

Which needs less VRAM, Qwen2.5 72B Instruct Abliterated or Qwen2.5 1.5B Quantized.w8a8?

At Q4_K_M, Qwen2.5 72B Instruct Abliterated needs 44.6 GB and Qwen2.5 1.5B Quantized.w8a8 needs 1.4 GB, so Qwen2.5 1.5B Quantized.w8a8 is the lighter option to run locally.

Which has a longer context window, Qwen2.5 72B Instruct Abliterated or Qwen2.5 1.5B Quantized.w8a8?

Qwen2.5 72B Instruct Abliterated supports 32,768 tokens and Qwen2.5 1.5B Quantized.w8a8 supports 32,768 tokens.

What is the difference between Qwen2.5 72B Instruct Abliterated and Qwen2.5 1.5B Quantized.w8a8?

Qwen2.5 72B Instruct Abliterated is a 72.7B model from huihui-ai (Qwen 2.5 family), while Qwen2.5 1.5B Quantized.w8a8 is a 1.8B model from RedHatAI (Qwen 2.5 family). Compare their VRAM requirements above to see which fits your GPU or Mac.