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NVIDIA GeForce RTX 2050
Runs downloadable LLMs up to ~7B at Q4, ~18.3-21.8 tok/s on an 8B model.
What you can run
At 8k context, FP16 KV. Full-speed tok/s holds up to "max ctx"; beyond it the context spills to SSD swap and drops to the degraded figure.
| Model size | FP16 | Q8 | Q4 |
|---|---|---|---|
| 3B | won't run |
27.3-32.5 t/s ≤31k ctx · then ~2.4-2.9 (slow) |
48.7-58 t/s ≤51k ctx · then ~4.3-5.2 (slow) |
| 7-8B | won't run | won't run |
18.3-21.8 t/s ≤4k ctx · then ~1.6-1.9 (slow) |
| 13B | won't run | won't run | won't run |
| 32B | won't run | won't run | won't run |
| 70B | won't run | won't run | won't run |
| 120B | won't run | won't run | won't run |
| 400B | won't run | won't run | won't run |
Estimate: tok/s ≈ bandwidth ÷ (params × bytes/param) × efficiency (NVIDIA). Cyan = fits ~6.5 GB usable. Beyond "ctx", KV spills to SSD swap (rough degraded speed shown).
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About the NVIDIA GeForce RTX 2050
NVIDIA GeForce RTX 2050 is a unified-memory system from NVIDIA, 2021. For local genAI the numbers that matter are its 8 GB (how big a model + context fits) and 112 GB/s bandwidth (generation speed).
Frequently asked questions
What size LLM can the NVIDIA GeForce RTX 2050 run?â–¶
With ~6.5 GB usable it runs up to ~7B at Q4 (~2B at FP16) at 8k context. Bigger spills into SSD swap and slows sharply.
How many tokens/sec does the NVIDIA GeForce RTX 2050 generate?â–¶
Generation is bandwidth-bound. At 112 GB/s an 8B model at Q4 runs ~18.3-21.8 tok/s (estimate).
Why does long context slow it down?â–¶
The KV cache for the context must also fit fast memory; once weights+KV exceed 6.5 GB it spills to SSD swap and throughput collapses. Each row shows the max usable context.