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Can I run clef-flash on a Mac with 24 GB?

Yes, with a GGUF version

The published weights are too big, but the Q8_0 file from bartowski/Cloudflare_clef-flash-GGUF (9.68 GB) fits, with room for ≈ 187K tokens of context.

Full analysis of clef-flash Everything that runs on Mac with 24 GB Get the Q8_0 file on Hugging Face
ollama run hf.co/bartowski/Cloudflare_clef-flash-GGUF:Q8_0

Files and context on Mac with 24 GB

Each file of clef-flash (and of GGUF versions the site has analyzed), and how much context fits next to it, with the context cache in 16-bit or 8-bit.

FileSizeOn Mac with 24 GB Context (16-bit)Context (8-bit)
As published18.8 GBDoesn't fit——
BF16ggml-org/Clef-Flash-GGUF18.2 GBDoesn't fit——
Q8_0ggml-org/Clef-Flash-GGUF9.66 GBFits187K256K
Q4_K_Mggml-org/Clef-Flash-GGUF6.49 GBFits256K256K
BF16bartowski/Cloudflare_clef-flash-GGUF18.2 GBDoesn't fit——
Q8_0bartowski/Cloudflare_clef-flash-GGUF9.68 GBFits187K256K
Q6_K_Lbartowski/Cloudflare_clef-flash-GGUF8.32 GBFits227K256K
Q6_Kbartowski/Cloudflare_clef-flash-GGUF7.83 GBFits242K256K
Q5_K_Mbartowski/Cloudflare_clef-flash-GGUF6.98 GBFits256K256K
Q4_K_Lbartowski/Cloudflare_clef-flash-GGUF6.80 GBFits256K256K
Q5_K_Sbartowski/Cloudflare_clef-flash-GGUF6.66 GBFits256K256K
Q4_1bartowski/Cloudflare_clef-flash-GGUF6.07 GBFits256K256K
Q4_K_Mbartowski/Cloudflare_clef-flash-GGUF6.04 GBFits256K256K
Q4_K_Sbartowski/Cloudflare_clef-flash-GGUF5.73 GBFits256K256K
IQ4_NLbartowski/Cloudflare_clef-flash-GGUF5.63 GBFits256K256K
Q4_0bartowski/Cloudflare_clef-flash-GGUF5.60 GBFits256K256K
IQ4_XSbartowski/Cloudflare_clef-flash-GGUF5.40 GBFits256K256K
Q3_K_Lbartowski/Cloudflare_clef-flash-GGUF5.24 GBFits256K256K
Q3_K_Mbartowski/Cloudflare_clef-flash-GGUF5.05 GBFits256K256K
IQ3_Mbartowski/Cloudflare_clef-flash-GGUF4.85 GBFits256K256K
Q3_K_Sbartowski/Cloudflare_clef-flash-GGUF4.80 GBFits256K256K
Q2_Kbartowski/Cloudflare_clef-flash-GGUF4.19 GBFits256K256K

clef-flash on other hardware

Popular models that run on Mac with 24 GB

Assumes 67% of the Mac's memory is usable (macOS's default limit for the GPU; it can be raised) and at least 4K tokens of context for one conversation, with the context cache in 16-bit unless noted. Fits leaves at least 20% of that memory for context; Tight leaves less.