Smol Llama 101M GQA vs Llama 68M

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

Smol Llama 101M GQA

BEE-spoke-data · 101M

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Llama 68M

JackFram · 68M

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Specifications

Smol Llama 101M GQALlama 68M
Parameters101M68M
Context1K2K
ArchitectureLlamaForCausalLMLlamaForCausalLM
LicenseApache 2.0Apache 2.0
Downloads1.9K203.4K
ReleasedDec 2025Jun 2026

VRAM by Quantization: Smol Llama 101M GQA vs Llama 68M

QuantizationBitsSmol Llama 101M GQA VRAMLlama 68M VRAM
Q2_K3.400.0 GB
Q3_K_M3.900.0 GB
Q3_K_S3.500.0 GB
Q4_K_M4.800.0 GB
Q5_K_M5.700.1 GB
Q6_K6.600.1 GB
Q8_08.000.1 GB

Verdict

Llama 68M supports a longer context window (2K tokens). Llama 68M is the more widely downloaded of the two.

Frequently Asked Questions

Which has a longer context window, Smol Llama 101M GQA or Llama 68M?

Smol Llama 101M GQA supports 1,024 tokens and Llama 68M supports 2,048 tokens.

What is the difference between Smol Llama 101M GQA and Llama 68M?

Smol Llama 101M GQA is a 101M model from BEE-spoke-data (Llama family), while Llama 68M is a 68M model from JackFram (Llama family). Compare their VRAM requirements above to see which fits your GPU or Mac.