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llama.cpp · homogeneous 2–4 GPUs · not a PC builder
Can this model run across multiple GPUs?
Phase 8 answers memory feasibility for identical cards under llama.cpp. Default split is layer (pipeline parallel: each GPU owns a slice of layers; KV stays with those layers). This is not 2 × VRAM = pool, and it is not a complete PC build.
2× NVIDIA RTX 3060 Ti 8 GB
Does not fit on this configuration
- Model
- DeepSeek Coder 33B Instruct · Q4 · 8K
- Runtime / split
- llama.cpp ·
layer· calculator 1.0.0 - Single-GPU status
- DOES_NOT_FIT · required 23.8 GB vs usable 7.2 GB
- Per card advertised / usable
- 8 GB / 7.2 GB
- Aggregate advertised
- 16.0 GB — capacity, not effective model capacity
- Nominal aggregate usable
- 14.4 GB (N × advertised × 0.90)
- Effective per-GPU peak
- 12.3 GB vs usable 7.2 GB
- Per-GPU split (approx.)
- weights 9.8 GB · KV 1.0 GB · runtime 1.0 GB · safety 0.5 GB
- Why
- Even a 2K context exceeds per-GPU usable VRAM after partition and per-device reserves.
- Topology
- Requires space for 2 discrete GPUs. Exact cooler slot width is not in the RigForAI graph. layer split is pipeline parallel and can run over PCIe. KV stays with the layers on each GPU. NVLink is not treated as a 1× aggregate VRAM pool.
- Performance
- Phase 5 predictions are single-GPU. Multi-GPU tok/s is not published.
- GPU-only current cost
- $566.44 = 2 × $283.22 at the current per-card matched price. This does not mean 2 units are in stock, and it is not a complete build cost.MSI VENTUS RTX 3060 TI 3X 8G OC LHR graphics card NVIDIA GeForce RTX 3060 Ti 8 GB GDDR6 · ASIN B09BK9X9K9
- Formula
- per_gpu_peak = ceil(weight_bytes/N) + ceil(kv_bytes/N) + runtime_base + safety_base + weight_fractions×ceil(weight_bytes/N). Compare to usable = advertised×0.90. Not (single_gpu_required × N) and not advertised_vram × N as effective capacity.
NVIDIA RTX 3060 Ti 8 GB · Single-GPU can-run · Find a single GPU · Build a machine for this GPU setup
Query combinations are not indexed. Source: llama.cpp multi-GPU documentation.