will it local

Best local LLMs for the NVIDIA GeForce RTX 3060 8GB

Speed

computed band 26.0-41.0 tok/s for 8B Q4_K_M (roofline, 240.0 GB/s VRAM); community: 37.0 tok/s Meta Llama 3.1 8B Instruct Q4_K_M (https://www.localscore.ai/accelerator/4053)

Effective decode window: 0.55–0.88 of 240 GB/s nominal → ~132–211 GB/s effective (llama.cpp decode, Q4_K_M basis; arch window, community-calibrated)

What fits (computed)

→ 14b-q4 no 10.5 GB vs 8 GB usable — does not fit

→ 3b-q4 full 2.8 GB needed of 8 GB usable — headroom for context

→ 4b-q4 full 3.7 GB needed of 8 GB usable — headroom for context

→ 8b-q4 full 6.1 GB needed of 8 GB usable — headroom for context

Cited community benches (1 rows)

→ 37.0 tok/s · Meta Llama 3.1 8B Instruct Q4_K_M LocalScore median · source

Runs fully in memory (machine alternatives)

Nominal bandwidth: 240.0 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)

→ whisper:medium on Raspberry Pi 5 + AI Kit (Hailo-8L) ($110) medium · 3.1GB · needs ~5.1GB (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 on Raspberry Pi 5 + AI Kit (Hailo-8L) ($110) distill 7B · 4.7GB · needs ~4.9GB (4k ctx)

→ mistral:7b on Raspberry Pi 5 + AI Kit (Hailo-8L) ($110) 7B · 4.1GB · needs ~4.6GB (4k ctx)

→ llava:7b on Raspberry Pi 5 + AI Kit (Hailo-8L) ($110) 7B · 4.7GB · needs ~6.7GB (4k ctx)

→ qwen3:8b on Tesla P100 (16GB, used) ($135) 8B · 5.2GB · needs ~5.8GB (4k ctx)

→ qwen2.5vl:7b on Tesla P100 (16GB, used) ($135) 7B · 5.6GB · needs ~5.8GB (4k ctx)

→ llama3.1:8b on Tesla P100 (16GB, used) ($135) 8B · 4.9GB · needs ~5.4GB (4k ctx)

→ deepseek-r1:8b on Tesla P100 (16GB, used) ($135) distill 8B · 4.9GB · needs ~5.4GB (4k ctx)

→ mistral-nemo:12b on Tesla P100 (16GB, used) ($135) 12B · 7.1GB · needs ~7.7GB (4k ctx)

Borderline — runs, but offloads

→ qwen3:14b 14B — 9.9 GB vs 8 GB usable — partial CPU offload, expect large speed loss

→ gemma3:12b 12B — 9.6 GB vs 8 GB usable — partial CPU offload, expect large speed loss

→ deepseek-r1:14b distill 14B — 9.8 GB vs 8 GB usable — partial CPU offload, expect large speed loss

→ phi4:14b 14B — 9.9 GB vs 8 GB usable — partial CPU offload, expect large speed loss

→ whisper:large-v3 large-v3 — 8.2 of 8 GB usable — barely over; real with q8 KV cache (halves KV) or shorter context

→ sdxl SDXL base — 8.9 GB vs 8 GB usable — partial CPU offload, expect large speed loss

Gotchas

⚠ The confusing sibling of the famous RTX 3060 12GB: 8GB cut-down (GA106, 3584 cores) — VERIFIED 0904: keeps the 192-bit/15Gbps memory subsystem at 240 GB/s (not 360); only VRAM is cut

⚠ At equal price ALWAYS buy the 12GB (rtx-3060-12): +50% VRAM and +50% bandwidth for 14B-class fits

⚠ Alias disambiguation matters: most "3060" listings mean the 12GB

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