Gemma-3-27B-MeditronFO
EPFLiGHT/Gemma-3-27B-MeditronFOGemma-3-27B-MeditronFO at Q4_K_M is exactly 17,339,606,784 bytes (16.15 GiB / 17.34 GB) — an effective 4.809 bits per weight, not the nominal 4. Its KV cache at 32K is 3.11 GiB, not the 15.50 GiB a flat formula predicts.
Shipped quantizations
| Quant | Size● | Exact bytes● | Effective bpw● | Tensors● | Publisher |
|---|---|---|---|---|---|
| I1-IQ1_S | 6.26 GiB | 6,726,783,648 | 1.866 | — | mradermacher |
| I1-IQ1_M | 6.76 GiB | 7,259,781,792 | 2.014 | — | mradermacher |
| I1-IQ2_XXS | 7.59 GiB | 8,148,112,032 | 2.260 | — | mradermacher |
| I1-IQ2_XS | 8.29 GiB | 8,901,440,160 | 2.469 | — | mradermacher |
| I1-IQ2_S | 8.74 GiB | 9,388,110,624 | 2.604 | — | mradermacher |
| I1-IQ2_M | 9.41 GiB | 10,098,774,816 | 2.801 | — | mradermacher |
| I1-Q2_K_S | 9.52 GiB | 10,219,982,112 | 2.835 | — | mradermacher |
| Q2_K | 10.21 GiB | 10,966,256,640 | 3.042 | — | mradermacher |
| I1-Q2_K | 10.21 GiB | 10,966,256,928 | 3.042 | — | mradermacher |
| I1-IQ3_XXS | 10.54 GiB | 11,322,180,384 | 3.140 | — | mradermacher |
| I1-IQ3_XS | 11.33 GiB | 12,167,935,392 | 3.375 | — | mradermacher |
| Q3_K_S | 11.90 GiB | 12,773,315,712 | 3.543 | — | mradermacher |
| I1-IQ3_S | 11.90 GiB | 12,773,316,000 | 3.543 | — | mradermacher |
| I1-Q3_K_S | 11.90 GiB | 12,773,316,000 | 3.543 | — | mradermacher |
| I1-IQ3_M | 12.25 GiB | 13,152,775,584 | 3.648 | — | mradermacher |
| Q3_K_M | 13.08 GiB | 14,043,341,952 | 3.895 | — | mradermacher |
| I1-Q3_K_M | 13.08 GiB | 14,043,342,240 | 3.895 | — | mradermacher |
| Q3_K_L | 14.11 GiB | 15,149,163,648 | 4.202 | — | mradermacher |
| I1-Q3_K_L | 14.11 GiB | 15,149,163,936 | 4.202 | — | mradermacher |
| I1-IQ4_XS | 14.45 GiB | 15,516,315,168 | 4.304 | — | mradermacher |
| IQ4_XS | 14.57 GiB | 15,642,758,400 | 4.339 | — | mradermacher |
| I1-Q4_0 | 15.28 GiB | 16,410,892,320 | 4.552 | — | mradermacher |
| Q4_K_S | 15.34 GiB | 16,466,974,464 | 4.567 | — | mradermacher |
| I1-Q4_K_S | 15.34 GiB | 16,466,974,752 | 4.567 | — | mradermacher |
| Q4_K_M | 16.15 GiB | 17,339,606,784 | 4.809 | — | mradermacher |
| I1-Q4_K_M | 16.15 GiB | 17,339,607,072 | 4.809 | — | mradermacher |
| I1-Q4_1 | 16.81 GiB | 18,048,314,400 | 5.006 | — | mradermacher |
| Q5_K_S | 18.38 GiB | 19,736,313,600 | 5.474 | — | mradermacher |
| I1-Q5_K_S | 18.38 GiB | 19,736,313,888 | 5.474 | — | mradermacher |
| Q5_K_M | 18.85 GiB | 20,240,797,440 | 5.614 | — | mradermacher |
| I1-Q5_K_M | 18.85 GiB | 20,240,797,728 | 5.614 | — | mradermacher |
| Q6_K | 21.72 GiB | 23,323,312,512 | 6.469 | — | mradermacher |
| I1-Q6_K | 21.72 GiB | 23,323,312,800 | 6.469 | — | mradermacher |
| Q8_0 | 28.13 GiB | 30,205,705,344 | 8.378 | — | mradermacher |
KV cache by context
| Context | KV cache (f16)● | Flat formula | Overstated by | Full / windowed / recurrent |
|---|---|---|---|---|
| 4,096 | 0.92 GiB | 1.94 GiB | 2.10× | 10 / 52 / 0 |
| 8,192 | 1.23 GiB | 3.88 GiB | 3.14× | 10 / 52 / 0 |
| 16,384 | 1.86 GiB | 7.75 GiB | 4.17× | 10 / 52 / 0 |
| 32,768 | 3.11 GiB | 15.50 GiB | 4.98× | 10 / 52 / 0 |
| 65,536 | 5.61 GiB | 31.00 GiB | 5.53× | 10 / 52 / 0 |
| 131,072 | 10.61 GiB | 62.00 GiB | 5.84× | 10 / 52 / 0 |
52 of 62 layers cache only a 1,024-token window rather than the full context, on a period of 6. Figures assume the default configuration; --swa-full disables the saving entirely.
Compare with
Will it run on your card?
Why other calculators give a different number
A parameters × bits ÷ 8 estimate puts Q4_K_M at roughly 15.11 GiB. The real file is 16.15 GiB, because a quantization is a mixture and some tensors are always kept at higher precision. The larger discrepancy is the cache: a flat formula gives 15.50 GiB at 32K context where the real figure is 3.11 GiB, because most of this model's layers cache a fixed window rather than the whole context.
Architecture
Questions people ask
- How much VRAM does Gemma-3-27B-MeditronFO need?
- Q4_K_M is exactly 17,339,606,784 bytes (16.15 GiB) in weights. Add the KV cache, which depends on your context length, plus roughly half a gigabyte of runtime overhead.
- How large is Gemma-3-27B-MeditronFO's KV cache?
- 3.11 GiB at 32K context with an f16 cache, computed per layer. Quantizing the cache to q8_0 roughly halves it, which is often the difference between a context length fitting and not.
- Which quantization of Gemma-3-27B-MeditronFO should I use?
- Q4_K_M is the usual default. Pick the largest quantization that fits your card at the context you actually need — the table above gives exact sizes for every one published.