local intelligence

will it local

Best local LLMs for the RTX A2000 Laptop

4GB · Ampere (laptop)

Variant trap: base card is 4 GB @ 12 Gbps = 192 GB/s (TPU RTX A2000 Mobile); an 8 GB refresh runs 14 Gbps = 224 GB/s (TPU RTX A2000 Mobile 8 GB) — verify which laptop you have Coverage hint of 6 GB / 240 GB/s is the desktop A2000's config family — desktop A2000 is GA106 192-bit 288 GB/s, a different card entirely; never inherit its numbers Alias RTX A1000 Laptop is a lower card (fewer cores, less bandwidth) — don't treat as equal 4 GB config holds nothing beyond ~1B-class quants fully in VRAM; 80 3rd-gen Tensor cores are the only upside

⚠ Laptop part — mobile clocks and thermals run below desktop sibling speeds; treat the band as optimistic for sustained load.

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

Speed

computed band 21.0-33.0 tok/s for 8B Q4_K_M (roofline, 192 GB/s VRAM)

Effective decode window: 0.55–0.88 of 192 GB/s nominal → ~106–169 GB/s effective (llama.cpp decode, Q4_K_M basis; arch window, community-calibrated)

What fits (computed)

13b-q4 no 14.6 GB vs 4 GB usable — does not fit

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

no single-card bench published — band is computed (see notes)

Runs fully in memory (machine alternatives)

Nominal bandwidth: 192 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

⚠ Variant trap: base card is 4 GB @ 12 Gbps = 192 GB/s (TPU RTX A2000 Mobile); an 8 GB refresh runs 14 Gbps = 224 GB/s (TPU RTX A2000 Mobile 8 GB) — verify which laptop you have

⚠ Coverage hint of 6 GB / 240 GB/s is the desktop A2000's config family — desktop A2000 is GA106 192-bit 288 GB/s, a different card entirely; never inherit its numbers

⚠ Alias RTX A1000 Laptop is a lower card (fewer cores, less bandwidth) — don't treat as equal

⚠ 4 GB config holds nothing beyond ~1B-class quants fully in VRAM; 80 3rd-gen Tensor cores are the only upside

Where to go next

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