local intelligence

can it run

Can the Tesla V100 (16GB, used) run qwen3 1.7B?

YES

Comfortably. 16GB of memory against a 4GB working set leaves headroom for context, the OS, and anything else you're running.

~300–490 tok/s

weights 1.4GB + KV cache 0.44GB at 4k context vs ~16GB usable → full. 1.8 GB needed of 16 GB usable — headroom for context

computed roofline: 900 GB/s × 0.46–0.76 efficiency window / 1.4GB (Q4_K_M) — bands, never points. Small models (under ~4.5B) run BELOW these bands — kernel-launch overhead keeps them from saturating bandwidth (measured against community medians, 09-06).

explore the full catalog84 machines indexed · live prices · what each one can run

Specs

model file1.4GB (GGUF Q4_K_M)
minimum memory4GB working set
this machine16GB HBM2, 900 GB/s
params1.7B
licenseapache-2.0
price$340

Run it

model files: hugging face ↗

easy run: ollama pull qwen3:1.7b

runs with: ollama · llama.cpp · koboldcpp · lm studio

Alternatives

every model the Tesla V100 (16GB, used) can run — full list

RTX 3090 (24GB, used) — upgrade path machine

Buy

eBay (used) ↗ · Amazon ↗

2026-09-17 · ← all models on the Tesla V100 (16GB, used) · ← full hardware catalog · prices verified at source, may drift