Compatibility check
Can you run Mistral Small 24B Instruct on the RTX 4070 Ti?
Not on a single RTX 4070 Ti. Even at 4-bit, Mistral Small 24B Instruct needs about 14.2 GB, which exceeds the card's 12 GB. You would need roughly 2× RTX 4070 Ti with tensor parallelism, a larger GPU, or a smaller model.
Memory breakdown
Weights plus a 0.6 GB KV cache at 4,096tokens, against the card's 12 GB. Verdicts leave ~10% headroom for activations and fragmentation.
| Precision | Weights | KV cache | Total | % of 12 GB | Fit |
|---|---|---|---|---|---|
| FP16 / BF16full quality | 54.2 GB | 0.6 GB | 54.8 GB | 457% | No |
| INT8 (8-bit)near-full quality | 27.1 GB | 0.6 GB | 27.7 GB | 231% | No |
| INT4 (4-bit)GPTQ / AWQ / GGUF Q4 | 13.6 GB | 0.6 GB | 14.2 GB | 118% | No |
Planning estimates, not a substitute for profiling. Real usage varies with the inference runtime, batch size, and how much context you actually use — the KV cache grows linearly with prompt length.
GPUs that run Mistral Small 24B Instruct
Cards where this model fits (at its best precision):
Models that fit the RTX 4070 Ti
Other popular models that run on this card:
Go deeper
Frequently asked questions
Can the RTX 4070 Ti run Mistral Small 24B Instruct?
No. Even 4-bit needs about 14.2 GB, more than the 12 GB available.
How much VRAM does Mistral Small 24B Instruct need?
Approximately 54.2 GB in FP16, 27.1 GB in INT8, and 13.6 GB in 4-bit for the weights, plus a KV cache of about 0.6 GB at 4,096 tokens.
Does quantization let Mistral Small 24B Instruct fit on the RTX 4070 Ti?
Not on a single RTX 4070 Ti — even 4-bit exceeds 12 GB. You would need multiple GPUs or a larger card.
What happens to memory with longer context?
The KV cache grows linearly with prompt length. At 4,096 tokens it is about 0.6 GB here; doubling the context roughly doubles that term, so long-context use can push a tight fit over the edge.