Compare

DeepSeek-Coder-V2-Lite Instruct 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-Coder-V2-Lite Instruct	Llama 3.1 8B Instruct
Organization	DeepSeek	Meta
Parameters	15.7B	8B
Architecture	DeepSeek-V2 · moe	Llama · dense
Context	128k	128k
Layers	27	32
Hidden size	2,048	4,096
KV heads	16 of 16	8 of 32
Licence	DeepSeek License	Llama 3.1 Community License
Commercial use	Yes	Yes
Modalities	text	text
Released	2024-06-17	2024-07-23
Recommended quantization	Q5_K_M	Q8_0
Memory needed	13 GB	9.5 GB
Estimated tok/s	458	92
Fit	Excellent 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