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No. Llama 3.3 70B does not fit on RTX 4090 24GB: Q4_K_M needs 47.1 GB and 23.5 GB is usable.
Hardware: RTX 4090 24GB · Model: Llama 3.3 70B
RTX 4090 24GB has 24 GB of VRAM and 1008 GB/s of memory bandwidth. The checker holds back 0.5 GB of VRAM for the driver and assumes 16 GB of system RAM, so fast memory usable by Ollama is 23.5 GB. Partial offload may also use 60% of that system RAM. Llama 3.3 70B (70.6B, Meta) at Q4_K_M is a 43 GB download and needs 47.1 GB with headroom for about 8k tokens.
| Best quant | Q4_K_M |
|---|---|
| Download size | 43 GB |
| Memory needed | 47.1 GB |
| Usable fast memory | 23.5 GB |
| Fit | does not fit |
| Estimated speed | no estimate, it does not fit |
| Command | ollama run llama3.3:70b |
Smallest hardware that runs it: M1 Max (32c GPU) 64GB at Q4_K_M (fits in fast memory, 47.1 GB needed, 48.0 GB usable, about 7 tok/s (estimate)). Can a M1 Max (32c GPU) 64GB run Llama 3.3 70B?
A smaller Meta model that fits this hardware: Llama 3.2 Vision 11B at Q8_0 (fits in fast memory, 13.5 GB). Can a RTX 4090 24GB run Llama 3.2 Vision 11B?
Open RTX 4090 24GB in the checkerEstimates, not benchmarks. Model sizes are ollama.com download sizes; memory needed adds headroom for ~8k tokens of context; speeds are rough figures from memory bandwidth. Data updated 2026-10-23.
A project by OnDevice Labs · llms.txt