local intelligence

will it local

Best local LLMs for the NVIDIA GeForce GTX 1650 Super

4GB · Turing

No direct 7B-class benchmark found on localmaxxing or r/LocalLLaMA for this exact SKU; single localmaxxing row is tagged 'GTX 1650 4GB' and may be misattributed — treat toks as TU116-class indicative, spec unverified for 7B No tensor cores (GTX 16-series) — dp4a INT8 path only 4GB VRAM caps you at 3-4B models fully on-GPU; 7B needs partial offload TU116 die (same as GTX 1660) with 50% more memory bandwidth than the non-Super 1650 (192 vs 128 GB/s) — decode should scale near-GTX-1660 for same-size models Requires 1x 6-pin PCIe power (100W TDP) — unlike the 75W non-Super GDDR6 only — no GDDR5 variant confusion like the base 1650

explore the full catalogupgrade paths with live prices · what fits on each machine

Speed

computed band 18.0-27.0 tok/s for 8B Q4_K_M (roofline, 192.0 GB/s VRAM); community: 30.6 tok/s Qwen3.5-4B IQ4_NL (https://localmaxxing.com/en/hardware/DISCRETE_GPU:nvidia+geforce+gtx+1650+super (run labeled 'GTX 1650 4GB' hardware — likely misattributed; treat as indicative of TU116-class 4GB))

Effective decode window: 0.48–0.72 of 192 GB/s nominal → ~92–138 GB/s effective (llama.cpp decode, Q4_K_M basis; arch window, community-calibrated)

What fits (computed)

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

Cited community benches (1 rows)

→ 30.6 tok/s · Qwen3.5-4B IQ4_NL · source

Runs fully in memory (machine alternatives)

Nominal bandwidth: 192.0 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)

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)

Borderline — runs, but offloads

→ 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

Gotchas

⚠ No direct 7B-class benchmark found on localmaxxing or r/LocalLLaMA for this exact SKU; single localmaxxing row is tagged 'GTX 1650 4GB' and may be misattributed — treat toks as TU116-class indicative, spec unverified for 7B

⚠ No tensor cores (GTX 16-series) — dp4a INT8 path only

⚠ 4GB VRAM caps you at 3-4B models fully on-GPU; 7B needs partial offload

⚠ TU116 die (same as GTX 1660) with 50% more memory bandwidth than the non-Super 1650 (192 vs 128 GB/s) — decode should scale near-GTX-1660 for same-size models

⚠ Requires 1x 6-pin PCIe power (100W TDP) — unlike the 75W non-Super

⚠ GDDR6 only — no GDDR5 variant confusion like the base 1650

Where to go next

gtx-1660-super

+80 GB/s, same 6GB class

→ its best-models page

rtx-3060-ti

8GB + 448 GB/s — first 8B-full tier

→ its best-models page

2026-09-18 · ← full hardware catalog · fit = working set vs VRAM · speeds are community-reported, cited in our knowledge base