Can I run it?
Can I run Tiel Coder 35B A3B on GeForce RTX 3080 10GB?
Expert offload
Expert offload on your GeForce RTX 3080 10GB: UD-Q4_K_XL keeps shared weights on the GPU and about 17.2 GB of experts in system RAM. About 196–267 tok/s. Active-parameter speed is approximate.
Best quantUD-Q4_K_XL
Working context8K
Max that fits8K
Speed196–267 tok/s
Weights20.8 GB
KV cache0.19 GB
Total4.30 GB
Usable9.03 GB
Tiel Coder 35B A3B details · GeForce RTX 3080 10GB page · How this estimate is made
Run commands
llama.cpp
# Expert offload is approximate. llama.cpp can pin experts to CPU: # -ot "\\.ffn_.*_exps\\.=CPU" llama-server -hf peculiar-ragdoll/Tiel-Coder-35B-A3B-GGUF:UD-Q4_K_XL -c 8192 -ngl 99
No matching name in the Ollama library snapshot.
LM Studio
lms get peculiar-ragdoll/Tiel-Coder-35B-A3B-GGUF # Then load quant UD-Q4_K_XL
Assumptions
- Estimate, not a benchmark. Decode speed uses a memory-bandwidth model at 55–75% of peak.
- KV cache is FP16. Engine overhead assumes llama.cpp (0.3 GB + 1% of the weights). Ollama is closer to 0.9 GB + 3%, LM Studio closer to 1 GB + 3%.
- UD-Q4_K_XL size is the real GGUF file size from Hugging Face.
- 0.5 GB is reserved because this GPU also drives a display, then 5% of the rest is left free.
- Speed is quoted at 8K context, not at the maximum context that still fits.
- Mixture-of-experts split is approximate: shared layers on the GPU, expert tensors in system RAM. Speed uses active parameters.
Models that fit this machine more comfortably
- Can I run Qwen3 VL 32B Instruct on GeForce RTX 3080 10GB? — Tight fit, UD-IQ1_S, 47–65 tok/s
- Can I run Qwen3 Coder 30B A3B Instruct on GeForce RTX 3080 10GB? — Tight fit, UD-IQ1_S, 428–584 tok/s
- Can I run Qwen3.8 27B on GeForce RTX 3080 10GB? — Tight fit, UD-IQ2_S, 47–64 tok/s
Updated 2026-10-24. Profile on this page is the device default plus 32 GB of DDR5-5600 system RAM.