Can the Arc B580 run Llama 3.3 70B Instruct?
Does not fit at Q4_K_M.
Llama 3.3 70B Instruct is 70.6B parameters. At Q4_K_M the weights are about 39.5 GiB; with the 1.5 GiB runtime reserve that is 41.0 GiB against the card's 12GB, about 29.0 GiB more than the card has.
All three quants
12GB card| Quant | Weights | With reserve | Verdict | Headroom |
|---|---|---|---|---|
| Q4_K_Mthe everyday quant | 39.5 GiB | 41.0 GiB | Does not fit | short 29.0 GiB |
| Q8_0near-lossless | 69.7 GiB | 71.2 GiB | Does not fit | short 59.2 GiB |
| FP16full weights | 131.5 GiB | 133.0 GiB | Does not fit | short 121.0 GiB |
Verdict rules: fits comfortably when weights plus reserve sit within 85% of VRAM; tight when they fit with little left for context; CPU offload when they exceed VRAM by up to 2x (runs, slowly, with layers in system RAM); no beyond that. The KV cache per token depends on the model's architecture and is not modelled here.
The numbers for this pairing
At Q4_K_M the weights take about 39.5 GiB, so with the 1.5 GiB runtime reserve it needs 41.0 GB: 29.0 GB more than the card's 12 GB.
No version of it fits entirely in this card's memory, so it would lean on system RAM and run far slower.
At about $330, this card costs roughly $27 per GB of VRAM.
Running it at its full 190 W board power for 4 hours a day would use about 23 kWh a month, about $4.20 at the US average residential rate of 18.4 cents per kWh (2026-05); real use sits below that ceiling.
Prices are the lowest current listings our tracker saw on Oct 7, 2026, since averages include premium variants; launch prices are marked where we have no listing.
Not this card. These fit it comfortably at Q4.
Nothing in the consumer catalog fits Llama 3.3 70B Instruct at Q4 on a single card; this is multi-GPU or datacenter territory, or a job for hosted inference (see PicksByModel for per-token pricing).
What the Arc B580 does run well → · Llama 3.3 70B Instruct on every card →
About the model
Llama 3.3 70B Instruct by Meta: 131,072-token native context, text, released 2024 under the Llama 3.3 Community License. Model card → · Hosted pricing on PicksByModel →