Can I Run Cosmos 3 on RTX 3090 Desktop (24 GB VRAM, 64 GB RAM)?
Written by Jakub Rusinowski · Last updated July 21, 2026
Yes
Yes — Cosmos 3 Nano at Q8_0 needs about 19.2 GB of the 24 GB usable on RTX 3090 Desktop (24 GB VRAM, 64 GB RAM) (~4.8 GB spare), at ~65 tok/s (estimated), with room for about 16,384 tokens of context.
Confidence: medium · Recommended quantization: Q8_0 · Estimated speed: ~65 tok/s
RTX 3090 Desktop (24 GB VRAM, 64 GB RAM) — what it gives a model
| Usable memory for models | 24 GB |
| Memory bandwidth | 936 GB/s |
| Form factor | Desktop |
| Operating system | Windows or Linux |
| Memory upgradeable | Yes |
Cosmos 3 on RTX 3090 Desktop (24 GB VRAM, 64 GB RAM): memory by quantization
| Quant | Memory needed | Fits 24 GB? | Max context | Est. speed | Download |
|---|
| F16 | 34.2 GB | ✗ No | — | — | 32 GB |
| Q8_0 | 19.2 GB | ✓ Yes | 16K | ~65 tok/s | 17 GB |
| Q6_K | 15.4 GB | ✓ Yes | 16K | ~79.2 tok/s | 13.1 GB |
| Q5_K_M | 13.6 GB | ✓ Yes | 16K | ~88.1 tok/s | 11.3 GB |
| Q4_K_M | 11.9 GB | ✓ Yes | 16K | ~98.5 tok/s | 9.7 GB |
| Q3_K_M | 9.1 GB | ✓ Yes | 16K | ~123 tok/s | 6.8 GB |
| Q2_K | 7.5 GB | ✓ Yes | 16K | ~142.4 tok/s | 5.3 GB |
Which Cosmos 3 sizes fit
| Variant | Needs at Q4_K_M | Fits? | Est. speed |
|---|
| Cosmos 3 Super | 41.8 GB | ✗ Too large | — |
| Cosmos 3 Nano | 11.9 GB | ✓ Fits | ~98.5 tok/s |
| Cosmos 3 Edge | 4.1 GB | ✓ Fits | ~216.9 tok/s |
What to watch out for
- 1 larger variant of Cosmos 3 does not fit and would need CPU offload or different hardware.
- This model does not publish its full attention configuration, so the KV-cache share of these figures is inferred from its parameter count rather than computed exactly.
RTX 3090 desktop limitations
- The cheapest route to 24 GB of VRAM, and the standard used-market recommendation for local LLMs.
- Older architecture: no FP8 acceleration, and higher idle power than a current card.
Recommended setup
Ollama or llama.cpp (CUDA/ROCm) — vLLM if you need concurrent serving
How these numbers are calculated
- Memory need = quantized weights + KV cache at 8,192 tokens (f16) + 0.8 GB runtime overhead.
- 24 GB of VRAM on the NVIDIA GeForce RTX 3090 at 936 GB/s.
- 64 GB of system RAM available for CPU offload when a model exceeds VRAM.
- Throughput is a memory-bandwidth roofline estimate, not a measurement. It is labelled "estimated" everywhere it appears.
- KV cache is inferred from the parameter count because this model does not publish its full attention configuration.
FAQ
Can I run Cosmos 3 on RTX 3090 Desktop (24 GB VRAM, 64 GB RAM)?
Yes — Cosmos 3 Nano at Q8_0 needs about 19.2 GB of the 24 GB usable on RTX 3090 Desktop (24 GB VRAM, 64 GB RAM) (~4.8 GB spare), at ~65 tok/s (estimated), with room for about 16,384 tokens of context.
Which quantization of Cosmos 3 should I use on RTX 3090 Desktop (24 GB VRAM, 64 GB RAM)?
Q8_0 — it needs about 19.2 GB of the 24 GB available, downloads as roughly 17 GB, and runs at an estimated 65 tokens/sec with up to 16K of context.
What limits Cosmos 3 on RTX 3090 Desktop (24 GB VRAM, 64 GB RAM)?
Nothing binding — the model fits with headroom and generates at a usable speed on this hardware.
Which runtime should I use?
Ollama or llama.cpp (CUDA/ROCm) — vLLM if you need concurrent serving
Other Computers
Other Models on RTX 3090 Desktop (24 GB VRAM, 64 GB RAM)
Cosmos 3 on GPUs
What This Model Is Good At
Model & Tools
← Can I Run It? | Cosmos 3 model page | Check your hardware