Gemma3-4B-CodeCenturion
sillykiwi/Gemma3-4B-CodeCenturionGemma3-4B-CodeCenturion at Q4_K_M is exactly 2,489,761,152 bytes (2.32 GiB / 2.49 GB) — an effective 4.632 bits per weight, not the nominal 4. Its KV cache at 32K is 0.79 GiB, not the 4.25 GiB a flat formula predicts.
Shipped quantizations
| Quant | Size● | Exact bytes● | Effective bpw● | Tensors● | Publisher |
|---|---|---|---|---|---|
| I1-IQ1_S | 1.06 GiB | 1,132,981,568 | 2.108 | — | mradermacher |
| I1-IQ1_M | 1.12 GiB | 1,199,459,648 | 2.232 | — | mradermacher |
| I1-IQ2_XXS | 1.22 GiB | 1,310,256,448 | 2.438 | — | mradermacher |
| I1-IQ2_XS | 1.31 GiB | 1,404,464,448 | 2.613 | — | mradermacher |
| I1-IQ2_S | 1.35 GiB | 1,449,233,728 | 2.696 | — | mradermacher |
| I1-IQ2_M | 1.43 GiB | 1,537,871,168 | 2.861 | — | mradermacher |
| I1-Q2_K_S | 1.52 GiB | 1,635,929,760 | 3.044 | — | mradermacher |
| I1-IQ3_XXS | 1.57 GiB | 1,689,341,248 | 3.143 | — | mradermacher |
| Q2_K | 1.61 GiB | 1,729,031,552 | 3.217 | — | mradermacher |
| I1-Q2_K | 1.61 GiB | 1,729,031,840 | 3.217 | — | mradermacher |
| I1-IQ3_XS | 1.74 GiB | 1,863,257,760 | 3.467 | — | mradermacher |
| Q3_K_S | 1.80 GiB | 1,937,231,232 | 3.604 | — | mradermacher |
| I1-IQ3_S | 1.80 GiB | 1,937,231,520 | 3.604 | — | mradermacher |
| I1-Q3_K_S | 1.80 GiB | 1,937,231,520 | 3.604 | — | mradermacher |
| I1-IQ3_M | 1.85 GiB | 1,986,670,240 | 3.696 | — | mradermacher |
| Q3_K_M | 1.95 GiB | 2,098,326,912 | 3.904 | — | mradermacher |
| I1-Q3_K_M | 1.95 GiB | 2,098,327,200 | 3.904 | — | mradermacher |
| Q3_K_L | 2.08 GiB | 2,235,952,512 | 4.160 | — | mradermacher |
| I1-Q3_K_L | 2.08 GiB | 2,235,952,800 | 4.160 | — | mradermacher |
| I1-IQ4_XS | 2.11 GiB | 2,263,109,280 | 4.210 | — | mradermacher |
| IQ4_XS | 2.12 GiB | 2,279,492,992 | 4.241 | — | mradermacher |
| I1-IQ4_NL | 2.20 GiB | 2,363,379,360 | 4.397 | — | mradermacher |
| I1-Q4_0 | 2.21 GiB | 2,369,932,960 | 4.409 | — | mradermacher |
| Q4_K_S | 2.21 GiB | 2,377,796,992 | 4.424 | — | mradermacher |
| I1-Q4_K_S | 2.21 GiB | 2,377,797,280 | 4.424 | — | mradermacher |
| Q4_K_M | 2.32 GiB | 2,489,761,152 | 4.632 | — | mradermacher |
| I1-Q4_K_M | 2.32 GiB | 2,489,761,440 | 4.632 | — | mradermacher |
| I1-Q4_1 | 2.39 GiB | 2,563,919,520 | 4.770 | — | mradermacher |
| Q5_K_S | 2.57 GiB | 2,764,459,392 | 5.143 | — | mradermacher |
| I1-Q5_K_S | 2.57 GiB | 2,764,459,680 | 5.143 | — | mradermacher |
| Q5_K_M | 2.64 GiB | 2,829,565,312 | 5.264 | — | mradermacher |
| I1-Q5_K_M | 2.64 GiB | 2,829,565,600 | 5.264 | — | mradermacher |
| Q6_K | 2.97 GiB | 3,190,607,232 | 5.936 | — | mradermacher |
| I1-Q6_K | 2.97 GiB | 3,190,607,520 | 5.936 | — | mradermacher |
| Q8_0 | 3.85 GiB | 4,130,230,240 | 7.684 | — | mradermacher |
| F16 | 7.23 GiB | 7,767,480,640 | 14.451 | — | mradermacher |
KV cache by context
| Context | KV cache (f16)● | Flat formula | Overstated by | Full / windowed / recurrent |
|---|---|---|---|---|
| 4,096 | 0.25 GiB | 0.53 GiB | 2.14× | 5 / 29 / 0 |
| 8,192 | 0.33 GiB | 1.06 GiB | 3.26× | 5 / 29 / 0 |
| 16,384 | 0.48 GiB | 2.13 GiB | 4.40× | 5 / 29 / 0 |
| 32,768 | 0.79 GiB | 4.25 GiB | 5.35× | 5 / 29 / 0 |
| 65,536 | 1.42 GiB | 8.50 GiB | 5.99× | 5 / 29 / 0 |
| 131,072 | 2.67 GiB | 17.00 GiB | 6.37× | 5 / 29 / 0 |
29 of 34 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 2.25 GiB. The real file is 2.32 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 4.25 GiB at 32K context where the real figure is 0.79 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 Gemma3-4B-CodeCenturion need?
- Q4_K_M is exactly 2,489,761,152 bytes (2.32 GiB) in weights. Add the KV cache, which depends on your context length, plus roughly half a gigabyte of runtime overhead.
- How large is Gemma3-4B-CodeCenturion's KV cache?
- 0.79 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 Gemma3-4B-CodeCenturion 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.