W7900+R9700 llama.cpp AMDVLK Vulkan: Qwen3.5-35B-A3B decode at 215917 context (u/neuromacmd)
34.3 tok/s (single-request decode, batch 1, two GPUs combined, 215917-token context)
Fields
id
benchmarks/nm-1s4bggo-w7900-r9700-35b-amdvlk-ctx215917-tgMetric
decode_tok_s
Value
34.3
Unit
tok/s (single-request decode, batch 1, two GPUs combined, 215917-token context)
Model
Qwen3.5-35B-A3B (unsloth UD-Q4_K_M, 21 GB)
Methodology
r/LocalLLaMA post 1s4bggo, EDIT 2. llama.cpp long-context sweep of Qwen3.5-35B-A3B UD-Q4_K_M on Fedora 43. One request, batch size 1. The context column is the allocated context in tokens and both the PP and Gen columns are measured at that depth; the post does not separately print the generated-token count. NOT aggregate across concurrent requests. ROCm rows at 65K and above on the dual-GPU config required -np 1 after a KV-cache checkpoint memory-access fault. Dual GPU, W7900 + R9700, tensor split across the two cards (the post does not print the split ratio). Backend: AMDVLK Vulkan. Context depth: 215917 tokens.
Measured by
third_party
Reproducible
yes
notes
EDIT 2 dual-GPU context sweep. The figure covers BOTH cards together, so it is not a per-GPU rate. ROCm at 65K+ needed -np 1 after a memory-access fault on the R9700.
Notes
EDIT 2 dual-GPU context sweep. The figure covers BOTH cards together, so it is not a per-GPU rate. ROCm at 65K+ needed -np 1 after a memory-access fault on the R9700.