Gemmasutra-Mini-2B-v1
TheDrummer/Gemmasutra-Mini-2B-v1Gemmasutra-Mini-2B-v1 at Q4_K_M is exactly 1,708,582,720 bytes (1.59 GiB / 1.71 GB) — an effective 5.228 bits per weight, not the nominal 4. Its KV cache at 32K is 1.85 GiB, not the 3.25 GiB a flat formula predicts.
Shipped quantizations
| Quant | Size● | Exact bytes● | Effective bpw● | Tensors● | Publisher |
|---|---|---|---|---|---|
| I1-IQ1_S | 0.78 GiB | 832,159,968 | 2.546 | — | mradermacher |
| I1-IQ1_M | 0.81 GiB | 873,797,856 | 2.674 | — | mradermacher |
| I1-IQ2_XXS | 0.88 GiB | 943,194,336 | 2.886 | — | mradermacher |
| I1-IQ2_XS | 0.93 GiB | 1,002,545,376 | 3.068 | — | mradermacher |
| I1-IQ2_S | 0.96 GiB | 1,032,497,376 | 3.159 | — | mradermacher |
| I1-IQ2_M | 1.01 GiB | 1,088,014,560 | 3.329 | — | mradermacher |
| I1-IQ3_XXS | 1.10 GiB | 1,181,685,984 | 3.616 | — | mradermacher |
| I1-Q2_K | 1.15 GiB | 1,229,830,368 | 3.763 | — | mradermacher |
| I1-IQ3_XS | 1.22 GiB | 1,314,212,064 | 4.021 | — | mradermacher |
| I1-IQ3_S | 1.27 GiB | 1,360,660,704 | 4.164 | — | mradermacher |
| I1-Q3_K_S | 1.27 GiB | 1,360,660,704 | 4.164 | — | mradermacher |
| IQ3_M | 1.30 GiB | 1,393,561,408 | 4.264 | — | bartowski |
| I1-IQ3_M | 1.30 GiB | 1,393,561,824 | 4.264 | — | mradermacher |
| I1-Q3_K_M | 1.36 GiB | 1,461,668,064 | 4.473 | — | mradermacher |
| Q3_K_L | 1.44 GiB | 1,550,436,160 | 4.744 | — | bartowski |
| I1-Q3_K_L | 1.44 GiB | 1,550,436,576 | 4.744 | — | mradermacher |
| IQ4_XS | 1.46 GiB | 1,566,250,816 | 4.793 | — | bartowski |
| I1-IQ4_XS | 1.46 GiB | 1,566,251,232 | 4.793 | — | mradermacher |
| I1-Q4_0 | 1.52 GiB | 1,633,491,168 | 4.999 | — | mradermacher |
| Q4_K_S | 1.53 GiB | 1,638,651,712 | 5.014 | — | bartowski |
| I1-Q4_K_S | 1.53 GiB | 1,638,652,128 | 5.014 | — | mradermacher |
| Q4_K_M | 1.59 GiB | 1,708,582,720 | 5.228 | — | bartowski |
| I1-Q4_K_M | 1.59 GiB | 1,708,583,136 | 5.228 | — | mradermacher |
| Q4_K_L | 1.72 GiB | 1,851,430,720 | 5.665 | — | bartowski |
| Q5_K_S | 1.75 GiB | 1,882,543,936 | 5.761 | — | bartowski |
| I1-Q5_K_S | 1.75 GiB | 1,882,544,352 | 5.761 | — | mradermacher |
| Q5_K_M | 1.79 GiB | 1,923,278,656 | 5.885 | — | bartowski |
| I1-Q5_K_M | 1.79 GiB | 1,923,279,072 | 5.885 | — | mradermacher |
| Q5_K_L | 1.92 GiB | 2,066,126,656 | 6.322 | — | bartowski |
| Q6_K | 2.00 GiB | 2,151,393,088 | 6.583 | — | bartowski |
| I1-Q6_K | 2.00 GiB | 2,151,393,504 | 6.583 | — | mradermacher |
| Q6_K_L | 2.14 GiB | 2,294,241,088 | 7.021 | — | bartowski |
| Q8_0 | 2.59 GiB | 2,784,495,424 | 8.521 | — | bartowski |
| F32 | 9.74 GiB | 10,463,413,792 | 32.019 | — | bartowski |
KV cache by context
| Context | KV cache (f16)● | Flat formula | Overstated by | Full / windowed / recurrent |
|---|---|---|---|---|
| 4,096 | 0.41 GiB | 0.41 GiB | — | 13 / 13 / 0 |
| 8,192 | 0.63 GiB | 0.81 GiB | 1.28× | 13 / 13 / 0 |
| 16,384 | 1.04 GiB | 1.63 GiB | 1.56× | 13 / 13 / 0 |
| 32,768 | 1.85 GiB | 3.25 GiB | 1.75× | 13 / 13 / 0 |
| 65,536 | 3.48 GiB | 6.50 GiB | 1.87× | 13 / 13 / 0 |
| 131,072 | 6.73 GiB | 13.00 GiB | 1.93× | 13 / 13 / 0 |
13 of 26 layers cache only a 4,096-token window rather than the full context, on a period of 2. 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 1.37 GiB. The real file is 1.59 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 3.25 GiB at 32K context where the real figure is 1.85 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 Gemmasutra-Mini-2B-v1 need?
- Q4_K_M is exactly 1,708,582,720 bytes (1.59 GiB) in weights. Add the KV cache, which depends on your context length, plus roughly half a gigabyte of runtime overhead.
- How large is Gemmasutra-Mini-2B-v1's KV cache?
- 1.85 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 Gemmasutra-Mini-2B-v1 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.