Llama on Intel Battlemage

Can I run Llama 3.1 70B on an Arc B580?

Not at Q4_K_M — it needs 43.4 GB against 10.5 GB available. You would need 5 of these cards.

Won't fit

43.4 GB of 10.5 GB · 414%
045 GB
Weights 40.0 GB
KV cache 2.5 GB
Runtime overhead 0.9 GB
Over the limit 32.9 GB

Short by 32.9 GB. You can run it with 14 of 80 layers on the Arc B580 and the rest in system RAM, at roughly 0.92 tok/s — usable for batch work, painful for chat. A smaller quantisation or a shorter context is usually the better trade.

Generation0.92tok/s
Prompt processing137tok/s
Max context0tokens
KV per 1K tokens0GB

Every quantisation of Llama 3.1 70B on a Arc B580

Highlighted row is the highest quality that still fits at 8K context.

QuantisationbpwWeights TotalVerdictMax ctxtok/s
FP16 / BF16 16.00 131.4 GB 134.8 GB Won't fit — 0.26
INT8 / W8A8 8.50 69.3 GB 72.7 GB Won't fit — 0.50
Q8_0 (GGUF) 8.50 69.3 GB 72.7 GB Won't fit — 0.50
FP8 (E4M3) 8.00 65.7 GB 69.1 GB Won't fit — 0.53
Q6_K 6.56 53.9 GB 57.3 GB Won't fit — 0.66
Q5_K_M 5.67 46.6 GB 50.0 GB Won't fit — 0.78
Q5_K_S 5.52 45.3 GB 48.7 GB Won't fit — 0.80
Q4_K_M 4.85 40.0 GB 43.4 GB Won't fit — 0.92
Q4_K_S 4.58 37.8 GB 41.2 GB Won't fit — 0.98
AWQ 4-bit 4.25 37.8 GB 41.2 GB Won't fit — 0.99
GPTQ 4-bit 4.25 37.8 GB 41.2 GB Won't fit — 0.99
MXFP4 4.25 37.8 GB 41.2 GB Won't fit — 0.99
Q4_0 4.55 37.6 GB 41.0 GB Won't fit — 0.99
IQ4_XS 4.25 35.2 GB 38.6 GB Won't fit — 1.07
Q3_K_M 3.91 32.5 GB 35.9 GB Won't fit — 1.17
IQ3_M 3.70 30.8 GB 34.2 GB Won't fit — 1.25
IQ3_XXS 3.06 25.7 GB 29.1 GB Won't fit — 1.57
Q2_K 2.63 22.3 GB 25.7 GB Won't fit — 1.88
IQ2_XXS 2.06 17.8 GB 21.2 GB Won't fit — 2.55
IQ1_M 1.75 15.3 GB 18.7 GB Won't fit — 3.25

Also worth checking

Llama 3.1 70B on every GPU
Full hardware tableEverything that runs on a Arc B580
Full model tableWhy the KV cache is the part that bites
Guide