▲ local intelligence

will it local

Best local LLMs for the GTX 980M

4GB · Maxwell (laptop)

Maxwell dropped from current CUDA toolkits — Vulkan backend or pinned old builds 8GB variant exists (rare); 4GB base means 7B Q4 tight via q8-KV-style tricks at best High TGP for a laptop part — many units throttle; used units often ex-gaming wear

⚠ 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 8.7-16.0 tok/s for 8B Q4_K_M (roofline, 160.4 GB/s VRAM)

Effective decode window: 0.28–0.50 of 160.4 GB/s nominal → ~45–80 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: 160.4 GB/s — see the effective decode window above

→ qwen3:0.6b on Tesla M60 (16GB, used) ($35) 0.6B · 0.6GB · needs ~1GB (4k ctx)

→ qwen3:1.7b on Tesla M60 (16GB, used) ($35) 1.7B · 1.4GB · needs ~1.8GB (4k ctx)

→ qwen3:4b on Tesla M60 (16GB, used) ($35) 4B · 2.6GB · needs ~3.2GB (4k ctx)

→ llama3.2:1b on Tesla M60 (16GB, used) ($35) 1B · 1.3GB · needs ~1.4GB (4k ctx)

→ llama3.2:3b on Tesla M60 (16GB, used) ($35) 3B · 2.0GB · needs ~2.4GB (4k ctx)

→ gemma3:1b on Tesla M60 (16GB, used) ($35) 1B · 1.0GB · needs ~1.1GB (4k ctx)

→ phi4:mini on Tesla M60 (16GB, used) ($35) mini 3.8B · 2.5GB · needs ~3GB (4k ctx)

→ moondream:2b on Tesla M60 (16GB, used) ($35) 2B · 1.7GB · needs ~3.7GB (4k ctx)

→ whisper:tiny on Tesla M60 (16GB, used) ($35) tiny · 0.1GB · needs ~2.1GB (4k ctx)

→ whisper on Tesla M60 (16GB, used) ($35) base · 0.3GB · needs ~2.3GB (4k ctx)

→ whisper:small on Tesla M60 (16GB, used) ($35) small · 0.9GB · needs ~2.9GB (4k ctx)

→ kokoro:82m on Tesla M60 (16GB, used) ($35) 82M · 0.3GB · needs ~2.3GB (4k ctx)

→ gemma3:4b on Tesla M60 (16GB, used) ($35) 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

⚠ Maxwell dropped from current CUDA toolkits — Vulkan backend or pinned old builds

⚠ 8GB variant exists (rare); 4GB base means 7B Q4 tight via q8-KV-style tricks at best

⚠ High TGP for a laptop part — many units throttle; used units often ex-gaming wear

Where to go next

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2026-10-01 · ← full hardware catalog · fit = working set vs VRAM · speeds are community-reported, cited in our knowledge base