gemma-4-E4B-it-qat-heretic_decensored
prithivMLmods/gemma-4-E4B-it-qat-heretic_decensoredgemma-4-E4B-it-qat-heretic_decensored at Q4_K_M is exactly 5,302,272,800 bytes (4.94 GiB / 5.30 GB) — an effective 5.342 bits per weight, not the nominal 4. Its KV cache at 32K is 0.51 GiB, not the 2.63 GiB a flat formula predicts.
Shipped quantizations
| Quant | Size● | Exact bytes● | Effective bpw● | Tensors● | Publisher |
|---|---|---|---|---|---|
| I1-IQ1_S | 3.06 GiB | 3,289,757,248 | 3.314 | — | mradermacher |
| I1-IQ1_M | 3.14 GiB | 3,372,271,168 | 3.397 | — | mradermacher |
| I1-IQ2_XXS | 3.27 GiB | 3,509,794,368 | 3.536 | — | mradermacher |
| I1-IQ2_XS | 3.38 GiB | 3,627,841,088 | 3.655 | — | mradermacher |
| I1-IQ2_S | 3.42 GiB | 3,677,279,808 | 3.705 | — | mradermacher |
| I1-IQ2_M | 3.53 GiB | 3,787,298,368 | 3.815 | — | mradermacher |
| I1-IQ3_XXS | 3.71 GiB | 3,982,841,408 | 4.012 | — | mradermacher |
| I1-Q2_K_S | 3.98 GiB | 4,269,590,080 | 4.301 | — | mradermacher |
| Q2_K | 4.08 GiB | 4,376,781,600 | 4.409 | — | prithivMLmods |
| Q2_K | 4.08 GiB | 4,376,782,080 | 4.409 | — | mradermacher |
| I1-Q2_K | 4.08 GiB | 4,376,782,400 | 4.409 | — | mradermacher |
| I1-IQ3_XS | 4.23 GiB | 4,545,885,760 | 4.580 | — | mradermacher |
| Q3_K_S | 4.31 GiB | 4,630,958,880 | 4.665 | — | prithivMLmods |
| Q3_K_S | 4.31 GiB | 4,630,959,360 | 4.665 | — | mradermacher |
| I1-Q3_K_S | 4.31 GiB | 4,630,959,680 | 4.665 | — | mradermacher |
| I1-IQ3_S | 4.32 GiB | 4,635,833,920 | 4.670 | — | mradermacher |
| I1-IQ3_M | 4.37 GiB | 4,687,361,600 | 4.722 | — | mradermacher |
| Q3_K_M | 4.49 GiB | 4,823,061,280 | 4.859 | — | prithivMLmods |
| Q3_K_M | 4.49 GiB | 4,823,061,760 | 4.859 | — | mradermacher |
| I1-Q3_K_M | 4.49 GiB | 4,823,062,080 | 4.859 | — | mradermacher |
| Q3_K_L | 4.65 GiB | 4,990,505,760 | 5.027 | — | prithivMLmods |
| Q3_K_L | 4.65 GiB | 4,990,506,240 | 5.027 | — | mradermacher |
| I1-Q3_K_L | 4.65 GiB | 4,990,506,560 | 5.027 | — | mradermacher |
| I1-IQ4_XS | 4.69 GiB | 5,037,385,280 | 5.075 | — | mradermacher |
| IQ4_XS | 4.71 GiB | 5,057,864,960 | 5.095 | — | mradermacher |
| Q4_0 | 4.80 GiB | 5,154,939,680 | 5.193 | — | prithivMLmods |
| I1-IQ4_NL | 4.81 GiB | 5,159,528,000 | 5.198 | — | mradermacher |
| I1-Q4_0 | 4.81 GiB | 5,163,132,480 | 5.201 | — | mradermacher |
| Q4_K_S | 4.82 GiB | 5,171,979,040 | 5.210 | — | prithivMLmods |
| Q4_K_S | 4.82 GiB | 5,171,979,520 | 5.210 | — | mradermacher |
| I1-Q4_K_S | 4.82 GiB | 5,171,979,840 | 5.210 | — | mradermacher |
| Q4_K_M | 4.94 GiB | 5,302,272,800 | 5.342 | — | prithivMLmods |
| Q4_K_M | 4.94 GiB | 5,302,273,280 | 5.342 | — | mradermacher |
| I1-Q4_K_M | 4.94 GiB | 5,302,273,600 | 5.342 | — | mradermacher |
| I1-Q4_1 | 5.03 GiB | 5,401,519,680 | 5.442 | — | mradermacher |
| Q5_0 | 5.26 GiB | 5,648,098,080 | 5.690 | — | prithivMLmods |
| Q5_K_S | 5.26 GiB | 5,648,098,080 | 5.690 | — | prithivMLmods |
| Q5_K_S | 5.26 GiB | 5,648,098,560 | 5.690 | — | mradermacher |
| I1-Q5_K_S | 5.26 GiB | 5,648,098,880 | 5.690 | — | mradermacher |
| Q5_K_M | 5.33 GiB | 5,723,996,960 | 5.766 | — | prithivMLmods |
KV cache by context
| Context | KV cache (f16)● | Flat formula | Overstated by | Full / windowed / recurrent |
|---|---|---|---|---|
| 4,096 | 0.12 GiB | 0.33 GiB | 2.67× | 7 / 35 / 0 |
| 8,192 | 0.18 GiB | 0.66 GiB | 3.69× | 7 / 35 / 0 |
| 16,384 | 0.29 GiB | 1.31 GiB | 4.57× | 7 / 35 / 0 |
| 32,768 | 0.51 GiB | 2.63 GiB | 5.19× | 7 / 35 / 0 |
| 65,536 | 0.94 GiB | 5.25 GiB | 5.57× | 7 / 35 / 0 |
| 131,072 | 1.82 GiB | 10.50 GiB | 5.77× | 7 / 35 / 0 |
35 of 42 layers cache only a 512-token window rather than the full context, on a period of . 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 4.16 GiB. The real file is 4.94 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 2.63 GiB at 32K context where the real figure is 0.51 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-4-E4B-it-qat-heretic_decensored need?
- Q4_K_M is exactly 5,302,272,800 bytes (4.94 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-4-E4B-it-qat-heretic_decensored's KV cache?
- 0.51 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-4-E4B-it-qat-heretic_decensored 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.