Floppa-12B-Gemma3-Uncensored
Ryex/Floppa-12B-Gemma3-UncensoredFloppa-12B-Gemma3-Uncensored at Q4_K_M is exactly 7,300,779,040 bytes (6.80 GiB / 7.30 GB) — an effective 4.792 bits per weight, not the nominal 4. Its KV cache at 32K is 2.47 GiB, not the 12.00 GiB a flat formula predicts.
Shipped quantizations
| Quant | Size● | Exact bytes● | Effective bpw● | Tensors● | Publisher |
|---|---|---|---|---|---|
| I1-IQ1_S | 2.74 GiB | 2,947,415,488 | 1.935 | — | mradermacher |
| I1-IQ1_M | 2.95 GiB | 3,164,728,768 | 2.077 | — | mradermacher |
| I1-IQ2_XXS | 3.28 GiB | 3,526,917,568 | 2.315 | — | mradermacher |
| I1-IQ2_XS | 3.58 GiB | 3,840,261,568 | 2.521 | — | mradermacher |
| I1-IQ2_S | 3.74 GiB | 4,020,710,848 | 2.639 | — | mradermacher |
| I1-IQ2_M | 4.01 GiB | 4,310,461,888 | 2.829 | — | mradermacher |
| I1-Q2_K_S | 4.14 GiB | 4,448,611,648 | 2.920 | — | mradermacher |
| Q2_K | 4.44 GiB | 4,768,222,240 | 3.130 | — | mradermacher |
| I1-Q2_K | 4.44 GiB | 4,768,222,528 | 3.130 | — | mradermacher |
| I1-IQ3_XXS | 4.46 GiB | 4,784,901,568 | 3.141 | — | mradermacher |
| I1-IQ3_XS | 4.85 GiB | 5,206,166,848 | 3.417 | — | mradermacher |
| Q3_K_S | 5.08 GiB | 5,458,316,320 | 3.583 | — | mradermacher |
| I1-Q3_K_S | 5.08 GiB | 5,458,316,608 | 3.583 | — | mradermacher |
| I1-IQ3_S | 5.08 GiB | 5,458,316,608 | 3.583 | — | mradermacher |
| I1-IQ3_M | 5.27 GiB | 5,655,723,328 | 3.712 | — | mradermacher |
| Q3_K_M | 5.60 GiB | 6,008,818,720 | 3.944 | — | mradermacher |
| I1-Q3_K_M | 5.60 GiB | 6,008,819,008 | 3.944 | — | mradermacher |
| Q3_K_L | 6.04 GiB | 6,480,186,400 | 4.254 | — | mradermacher |
| I1-Q3_K_L | 6.04 GiB | 6,480,186,688 | 4.254 | — | mradermacher |
| I1-IQ4_XS | 6.10 GiB | 6,550,965,568 | 4.300 | — | mradermacher |
| IQ4_XS | 6.15 GiB | 6,606,261,280 | 4.337 | — | mradermacher |
| I1-IQ4_NL | 6.41 GiB | 6,887,165,248 | 4.521 | — | mradermacher |
| I1-Q4_0 | 6.43 GiB | 6,909,283,648 | 4.535 | — | mradermacher |
| Q4_K_S | 6.46 GiB | 6,935,333,920 | 4.553 | — | mradermacher |
| I1-Q4_K_S | 6.46 GiB | 6,935,334,208 | 4.553 | — | mradermacher |
| Q4_K_M | 6.80 GiB | 7,300,779,040 | 4.792 | — | mradermacher |
| I1-Q4_K_M | 6.80 GiB | 7,300,779,328 | 4.792 | — | mradermacher |
| I1-Q4_1 | 7.04 GiB | 7,559,564,608 | 4.962 | — | mradermacher |
| Q5_K_S | 7.67 GiB | 8,231,963,680 | 5.404 | — | mradermacher |
| I1-Q5_K_S | 7.67 GiB | 8,231,963,968 | 5.404 | — | mradermacher |
| Q5_K_M | 7.87 GiB | 8,445,037,120 | 5.543 | — | Ryex |
| Q5_K_M | 7.87 GiB | 8,445,037,600 | 5.543 | — | mradermacher |
| I1-Q5_K_M | 7.87 GiB | 8,445,037,888 | 5.543 | — | mradermacher |
| Q6_K | 9.00 GiB | 9,660,812,320 | 6.341 | — | mradermacher |
| I1-Q6_K | 9.00 GiB | 9,660,812,608 | 6.341 | — | mradermacher |
| Q8_0 | 11.65 GiB | 12,510,213,280 | 8.212 | — | mradermacher |
KV cache by context
| Context | KV cache (f16)● | Flat formula | Overstated by | Full / windowed / recurrent |
|---|---|---|---|---|
| 4,096 | 0.72 GiB | 1.50 GiB | 2.09× | 8 / 40 / 0 |
| 8,192 | 0.97 GiB | 3.00 GiB | 3.10× | 8 / 40 / 0 |
| 16,384 | 1.47 GiB | 6.00 GiB | 4.09× | 8 / 40 / 0 |
| 32,768 | 2.47 GiB | 12.00 GiB | 4.86× | 8 / 40 / 0 |
| 65,536 | 4.47 GiB | 24.00 GiB | 5.37× | 8 / 40 / 0 |
| 131,072 | 8.47 GiB | 48.00 GiB | 5.67× | 8 / 40 / 0 |
40 of 48 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 6.38 GiB. The real file is 6.80 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 12.00 GiB at 32K context where the real figure is 2.47 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 Floppa-12B-Gemma3-Uncensored need?
- Q4_K_M is exactly 7,300,779,040 bytes (6.80 GiB) in weights. Add the KV cache, which depends on your context length, plus roughly half a gigabyte of runtime overhead.
- How large is Floppa-12B-Gemma3-Uncensored's KV cache?
- 2.47 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 Floppa-12B-Gemma3-Uncensored 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.