will it local
No localmaxxing.com approved runs for this exact card; bench evidence is r/LocalLLaMA community reports only 4GB VRAM means 7B Q4_K_M does not fit on-GPU — requires partial CPU offload, which tanks speed to single digits No tensor cores; llama.cpp CUDA path uses slow fp32/fp16 CUDA-core kernels Pascal (CC 6.1) support is being deprecated in newer CUDA releases — future llama.cpp builds may drop it 75W TDP, most models have no 6-pin PCIe power connector — good for OEM/SFF retrofits Lowest memory bandwidth in this class (112 GB/s) — decode is bandwidth-bound
computed band 6.1-11.0 tok/s for 8B Q4_K_M (roofline, 112.1 GB/s VRAM); community: single-digit (interactive at best) tok/s Qwen2.5-7B (partial offload, 4GB VRAM) Q4-class GGUF with CPU offload (https://www.reddit.com/r/LocalLLaMA/comments/1po97ad/finally_managed_to_run_qwen257b_on_a_4gb_gtx_1050)
Effective decode window: 0.28–0.50 of 112.1 GB/s nominal → ~31–56 GB/s effective (llama.cpp decode, Q4_K_M basis; arch window, community-calibrated)
→ 3b-q4 full 2.8 GB needed of 4 GB usable — headroom for context
→ 4b-q4 tight 3.7 of 4 GB usable — keep context modest
→ 8b-q4 no 6.1 GB vs 4 GB usable — does not fit
→ single-digit (interactive at best) tok/s · Qwen2.5-7B (partial offload, 4GB VRAM) Q4-class GGUF with CPU offload · source
Nominal bandwidth: 112.1 GB/s — see the effective decode window above
→ qwen3:0.6b on Raspberry Pi 5 + AI Kit (Hailo-8L) ($110) 0.6B · 0.6GB · needs ~1GB (4k ctx)
→ qwen3:1.7b on Raspberry Pi 5 + AI Kit (Hailo-8L) ($110) 1.7B · 1.4GB · needs ~1.8GB (4k ctx)
→ qwen3:4b on Raspberry Pi 5 + AI Kit (Hailo-8L) ($110) 4B · 2.6GB · needs ~3.2GB (4k ctx)
→ llama3.2:1b on Raspberry Pi 5 + AI Kit (Hailo-8L) ($110) 1B · 1.3GB · needs ~1.4GB (4k ctx)
→ llama3.2:3b on Raspberry Pi 5 + AI Kit (Hailo-8L) ($110) 3B · 2.0GB · needs ~2.4GB (4k ctx)
→ gemma3:1b on Raspberry Pi 5 + AI Kit (Hailo-8L) ($110) 1B · 1.0GB · needs ~1.1GB (4k ctx)
→ phi4:mini on Raspberry Pi 5 + AI Kit (Hailo-8L) ($110) mini 3.8B · 2.5GB · needs ~3GB (4k ctx)
→ moondream:2b on Raspberry Pi 5 + AI Kit (Hailo-8L) ($110) 2B · 1.7GB · needs ~3.7GB (4k ctx)
→ whisper:tiny on Raspberry Pi 5 + AI Kit (Hailo-8L) ($110) tiny · 0.1GB · needs ~2.1GB (4k ctx)
→ whisper on Raspberry Pi 5 + AI Kit (Hailo-8L) ($110) base · 0.3GB · needs ~2.3GB (4k ctx)
→ whisper:small on Raspberry Pi 5 + AI Kit (Hailo-8L) ($110) small · 0.9GB · needs ~2.9GB (4k ctx)
→ kokoro:82m on Raspberry Pi 5 + AI Kit (Hailo-8L) ($110) 82M · 0.3GB · needs ~2.3GB (4k ctx)
→ gemma3:4b on Raspberry Pi 5 + AI Kit (Hailo-8L) ($110) 4B · 3.3GB · needs ~3.8GB (4k ctx)
→ deepseek-r1:7b distill 7B — 4.9 GB vs 4 GB usable — partial CPU offload, expect large speed loss
→ mistral:7b 7B — 4.6 GB vs 4 GB usable — partial CPU offload, expect large speed loss
⚠ No localmaxxing.com approved runs for this exact card; bench evidence is r/LocalLLaMA community reports only
⚠ 4GB VRAM means 7B Q4_K_M does not fit on-GPU — requires partial CPU offload, which tanks speed to single digits
⚠ No tensor cores; llama.cpp CUDA path uses slow fp32/fp16 CUDA-core kernels
⚠ Pascal (CC 6.1) support is being deprecated in newer CUDA releases — future llama.cpp builds may drop it
⚠ 75W TDP, most models have no 6-pin PCIe power connector — good for OEM/SFF retrofits
⚠ Lowest memory bandwidth in this class (112 GB/s) — decode is bandwidth-bound