Compatibility check
Can you run OLMo 2 7B Instruct on the RTX 4060 Ti 8GB?
Yes, with quantization. OLMo 2 7B Instruct does not fit the RTX 4060 Ti 8GB (8 GB) in FP16, but it runs at INT4 (4-bit) using about 6.2 GB (78% of VRAM). Use a GPTQ, AWQ, or GGUF build to get there, and keep prompts moderate to leave room for the KV cache.
Memory breakdown
Weights plus a 2 GB KV cache at 4,096tokens, against the card's 8 GB. Verdicts leave ~10% headroom for activations and fragmentation.
| Precision | Weights | KV cache | Total | % of 8 GB | Fit |
|---|---|---|---|---|---|
| FP16 / BF16full quality | 16.8 GB | 2 GB | 18.8 GB | 235% | No |
| INT8 (8-bit)near-full quality | 8.4 GB | 2 GB | 10.4 GB | 130% | No |
| INT4 (4-bit)GPTQ / AWQ / GGUF Q4 | 4.2 GB | 2 GB | 6.2 GB | 78% | Fits |
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 OLMo 2 7B Instruct
Cards where this model fits (at its best precision):
Models that fit the RTX 4060 Ti 8GB
Other popular models that run on this card:
Go deeper
Frequently asked questions
Can the RTX 4060 Ti 8GB run OLMo 2 7B Instruct?
Not in FP16, but yes at INT4 (4-bit), where it uses about 6.2 GB versus the card's 8 GB.
How much VRAM does OLMo 2 7B Instruct need?
Approximately 16.8 GB in FP16, 8.4 GB in INT8, and 4.2 GB in 4-bit for the weights, plus a KV cache of about 2 GB at 4,096 tokens.
Does quantization let OLMo 2 7B Instruct fit on the RTX 4060 Ti 8GB?
Yes. Dropping to INT4 (4-bit) brings total usage to about 6.2 GB, which fits the 8 GB card with headroom for the KV cache.
What happens to memory with longer context?
The KV cache grows linearly with prompt length. At 4,096 tokens it is about 2 GB here; doubling the context roughly doubles that term, so long-context use can push a tight fit over the edge.