Compare

DeepSeek-R1-Distill-Qwen-32B vs Llama 3.1 8B Instruct

Same hardware, same arithmetic, side by side. Every memory figure is calculated from published model geometry rather than quoted from a marketing page.

Estimated

Model AModel B

Hardware

Side by side

On GeForce RTX 4090

Property	DeepSeek-R1-Distill-Qwen-32B	Llama 3.1 8B Instruct
Organization	DeepSeek	Meta
Parameters	32.8B	8B
Architecture	Qwen2.5 · dense	Llama · dense
Context	128k	128k
Layers	64	32
Hidden size	5,120	4,096
KV heads	8 of 40	8 of 32
Licence	MIT	Llama 3.1 Community License
Commercial use	Yes	Yes
Modalities	text	text
Released	2025-01-20	2024-07-23
Recommended quantization	Q4_K_M	Q8_0
Memory needed	21 GB	9.5 GB
Estimated tok/s	39	92
Fit	Tight fit	Excellent fit
Fine-tune here	Yes	Yes
MMLU (reported)	—	69.4%
HUMANEVAL (reported)	—	72.6%

Benchmark rows are figures the model's authors published, not ModelLM measurements, and the two models may not have been evaluated under identical conditions.

Trade-offs