What GPU do I need to run microsoft/kosmos-2-patch14-224?
1.7B parameters, published in F32. View on Hugging Face
Set up kosmos-2-patch14-224kosmos-2-patch14-224 is published by microsoft on Hugging Face, with 187,274 downloads and 183 likes to date. It's a Kosmos2ForConditionalGeneration model built for image-to-text, published natively in F32.
VRAM required & cheapest live GPU fit
Required VRAM = weight size at each precision times a flat 1.2 overhead for activations and fragmentation. The KV-cache grows with context and is not in that factor; it is listed per model below where the architecture is published. Full formula and assumptions: methodology.
| Precision | Weight size | Required VRAM | Cheapest live fit | GPUs needed | Est. $/hr (full fit) |
|---|---|---|---|---|---|
| FP32 | 6.2 GB | 7.4 GB | P4 | 1 | $0.069/hr |
| FP8 (quantized) | 1.6 GB | 1.9 GB | RTX 4000 SFF Ada | 1 | $0.198/hr |
| INT4 (quantized) | 0.8 GB | 0.9 GB | RTX 3070 | 1 | $0.143/hr |
A GPU is only matched to a row if its hardware supports that precision, and the primary recommendation is always a single-GPU fit when one exists.
INT4 requires a quantized checkpoint actually published for this model, check its Hugging Face page before relying on this row.
Cheapest way to run kosmos-2-patch14-224 at its published (F32) precision: 1× P4, at $0.069/hr per GPU ($0.069/hr total). Quantizing to FP8 or INT4 (rows above) can cost less, but requires a compatible quantized checkpoint to exist for this model.
kosmos-2-patch14-224: common questions
Does kosmos-2-patch14-224 fit on a 8 GB GPU?
Yes. At FP32 it needs 7.4 GB of VRAM, so an 8 GB card holds it with 0.6 GB to spare. A 6 GB card is not enough for it at FP32.
Can kosmos-2-patch14-224 run in 16-bit instead of FP32?
Yes. Its published weights are FP32, 6.2 GB, or 7.4 GB once inference overhead is added. Loading the same weights in 16 bits halves that to 3.1 GB, or 3.7 GB with overhead. That moves it onto a 6 GB card instead of an 8 GB one. How much accuracy the cast costs is model-specific and is not measured here.
What is the least VRAM kosmos-2-patch14-224 can run in?
0.9 GB, at INT4 (quantized), which fits a 6 GB card, against 7.4 GB at FP32. That row assumes an INT4 checkpoint has actually been published for this model, so check its Hugging Face page before planning around it.
Weight-to-VRAM math, the fit rules, and how live prices are normalized: full methodology.
More microsoft models
- FrogNano-4B-2609 (4.7B, BF16)
- Mage-VL (4.7B, BF16)
- trocr-base-printed (333M, F32)
- trocr-base-handwritten (333M, F32)
- DialoGPT-small (176M, F16)
Alternatives at this size
Other models for image-to-text within about a third of kosmos-2-patch14-224's 1.7B parameters, from other model lines.
- LightOnOCR-1B-1025 (1.2B, BF16)
More on kosmos-2-patch14-224
Fits on an 8 GB GPU at FP32: every model that fits in 8 GB.
Related reading: H100 pricing and specs, How much VRAM you need for LLMs, and What AI inference is.
