MirilAI · text

Miril-Drone-2B-1

MirilAI/Miril-Drone-2B-1

Miril-Drone-2B-1 at Q4_K_M is exactly 3,416,119,840 bytes (3.18 GiB / 3.42 GB) — an effective 5.354 bits per weight, not the nominal 4. Its KV cache at 32K is 0.25 GiB, not the 1.09 GiB a flat formula predicts.

From the file· summed from 1 file(s)From the file· KV per layer
Parameters
5.1B
Architecture
gemma4
35 layers
Context
131,072
native (config.json)
License
apache-2.0

Shipped quantizations

exact bytes, summed from published files
QuantSizeExact bytesEffective bpwTensorsPublisher
IQ2_M2.43 GiB2,608,439,6804.088bartowski
IQ3_XXS2.50 GiB2,684,308,8644.207bartowski
Q2_K2.78 GiB2,980,654,6244.672mradermacher
Q2_K2.80 GiB3,011,620,2244.720bartowski
IQ3_XS2.88 GiB3,091,320,1924.845bartowski
Q3_K_S2.89 GiB3,102,078,4964.862mradermacher
Q3_K_S2.91 GiB3,126,654,3364.900bartowski
IQ3_M2.93 GiB3,151,039,8724.939bartowski
Q3_K_M2.97 GiB3,191,959,0725.003mradermacher
Q3_K_M3.00 GiB3,216,878,9765.042bartowski
Q3_K_L3.05 GiB3,271,781,9205.128mradermacher
Q3_K_L3.05 GiB3,279,842,6885.141bartowski
IQ4_XS3.07 GiB3,298,299,4245.169mradermacher
IQ4_XS3.08 GiB3,311,527,2965.190bartowski
Q4_K_S3.12 GiB3,354,431,0085.257mradermacher
IQ4_NL3.14 GiB3,367,560,5765.278bartowski
Q4_03.14 GiB3,368,095,1045.279bartowski
Q4_K_S3.14 GiB3,370,896,7685.283bartowski
Q4_K_M3.18 GiB3,416,119,8405.354mradermacher
Q4_K_M3.21 GiB3,449,739,6485.407bartowski
Q4_13.24 GiB3,478,244,7365.452bartowski
Q5_K_S3.34 GiB3,582,397,9845.615mradermacher
Q5_K_S3.34 GiB3,590,753,6645.628bartowski
Q5_K_M3.37 GiB3,616,709,1525.668mradermacher
Q5_K_M3.39 GiB3,643,552,1285.711bartowski
Q2_K_L3.43 GiB3,677,990,2725.764bartowski
Q6_K3.57 GiB3,829,835,2966.003mradermacher
Q6_K3.61 GiB3,879,641,4726.081bartowski
Q4_K_L3.83 GiB4,116,109,6966.451bartowski
Q5_K_L4.01 GiB4,309,922,1766.755bartowski
Q6_K_L4.23 GiB4,546,011,5207.125bartowski
Q8_04.61 GiB4,947,414,4007.754bartowski
Q8_04.61 GiB4,947,414,5607.754mradermacher
BF168.64 GiB9,273,527,39214.534bartowski
F168.64 GiB9,273,527,84014.534mradermacher

KV cache by context

computed per layer — this model uses sliding-window attention
ContextKV cache (f16)Flat formulaOverstated byFull / windowed / recurrent
4,0960.05 GiB0.14 GiB2.50×7 / 28 / 0
8,1920.08 GiB0.27 GiB3.33×7 / 28 / 0
16,3840.14 GiB0.55 GiB4.00×7 / 28 / 0
32,7680.25 GiB1.09 GiB4.44×7 / 28 / 0
65,5360.46 GiB2.19 GiB4.71×7 / 28 / 0
131,0720.90 GiB4.38 GiB4.85×7 / 28 / 0

28 of 35 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

same modality, comparable size

Will it run on your card?

full quant x context sweep

Why other calculators give a different number

A parameters × bits ÷ 8 estimate puts Q4_K_M at roughly 2.67 GiB. The real file is 3.18 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 1.09 GiB at 32K context where the real figure is 0.25 GiB, because most of this model's layers cache a fixed window rather than the whole context.

Architecture

from config.json
Layers
35
Attention heads
8
KV heads
1
Head dim
256
Hidden size
1536
Vocab
262,144
Sliding window
512
SWA period
MLA
no
Experts
Experts per token
use_sliding_window

Questions people ask

How much VRAM does Miril-Drone-2B-1 need?
Q4_K_M is exactly 3,416,119,840 bytes (3.18 GiB) in weights. Add the KV cache, which depends on your context length, plus roughly half a gigabyte of runtime overhead.
How large is Miril-Drone-2B-1's KV cache?
0.25 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 Miril-Drone-2B-1 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.
Miril-Drone-2B-1 — VRAM requirements, exact quant sizes — ossmodeldb