stepfun-ai · text

step-3.5-flash

stepfun-ai/step-3.5-flash

step-3.5-flash at Q4_K_M is exactly 119,937,953,440 bytes (111.70 GiB / 119.94 GB) — an effective 4.812 bits per weight, not the nominal 4. Its KV cache at 32K is 13.03 GiB, not the 45.00 GiB a flat formula predicts.

From the file· summed from 4 file(s)From the file· KV per layer
Parameters
199B
Architecture
step35
45 layers
Context
262,144
native (config.json)
License
apache-2.0

Shipped quantizations

exact bytes, summed from published files
QuantSizeExact bytesEffective bpwTensorsPublisher
IQ1_S38.47 GiB41,301,534,9441.657bartowski
IQ1_M40.17 GiB43,127,491,8081.730bartowski
IQ2_XXS44.74 GiB48,034,597,0881.927bartowski
IQ2_XS2 shards51.40 GiB55,187,798,4322.214bartowski
IQ2_S2 shards51.70 GiB55,513,426,3682.227bartowski
IQ2_M2 shards58.63 GiB62,949,743,0402.526bartowski
IQ2_M59.59 GiB63,980,443,5842.567Ex0bit
Q2_K2 shards64.78 GiB69,553,669,5682.791bartowski
Q2_K_L2 shards65.26 GiB70,069,253,5682.811bartowski
IQ3_XXS2 shards72.82 GiB78,190,672,3203.137bartowski
IQ3_XS3 shards75.46 GiB81,028,805,1843.251bartowski
Q3_K_S3 shards80.06 GiB85,965,042,2403.449bartowski
IQ3_M3 shards83.98 GiB90,168,226,3363.618bartowski
Q3_K_M3 shards84.04 GiB90,232,418,8483.620bartowski
Q3_K_L3 shards87.26 GiB93,692,326,4643.759bartowski
Q3_K_L95.03 GiB102,042,463,9364.094Ex0bit
IQ4_XS3 shards98.34 GiB105,591,741,9844.237bartowski
IQ4_NL103.86 GiB111,520,582,3364.475Ex0bit
IQ4_NL3 shards103.97 GiB111,641,955,9044.479bartowski
Q4_03 shards105.60 GiB113,392,160,3204.550bartowski
Q4_K_S3 shards107.70 GiB115,642,666,5604.640bartowski
Q4_K110.56 GiB118,710,303,7124.763ggml-org
Q4_K_M4 shards111.70 GiB119,937,953,4404.812bartowski
Q4_K_L4 shards112.07 GiB120,329,797,2804.828bartowski
Q4_14 shards115.15 GiB123,642,900,1604.961bartowski
Q5_K_S4 shards126.55 GiB135,886,679,7125.452bartowski
Q5_K_M4 shards130.58 GiB140,208,656,0645.626bartowski
Q5_K_L4 shards130.88 GiB140,534,505,1525.639bartowski
Q6_K5 shards150.81 GiB161,935,354,6886.497bartowski
Q8_06 shards195.04 GiB209,417,870,9768.403bartowski

KV cache by context

computed per layer — this model uses sliding-window attention
ContextKV cache (f16)Flat formulaOverstated byFull / windowed / recurrent
4,0962.53 GiB5.63 GiB2.22×12 / 33 / 0
8,1924.03 GiB11.25 GiB2.79×12 / 33 / 0
16,3847.03 GiB22.50 GiB3.20×12 / 33 / 0
32,76813.03 GiB45.00 GiB3.45×12 / 33 / 0
65,53625.03 GiB90.00 GiB3.60×12 / 33 / 0
131,07249.03 GiB180.00 GiB3.67×12 / 33 / 0

33 of 45 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 104.45 GiB. The real file is 111.70 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 45.00 GiB at 32K context where the real figure is 13.03 GiB, because most of this model's layers cache a fixed window rather than the whole context.

Architecture

from config.json
Layers
45
Attention heads
64
KV heads
64
Head dim
128
Hidden size
4096
Vocab
128,896
Sliding window
512
SWA period
MLA
no
Experts
Experts per token
use_sliding_window

Questions people ask

How much VRAM does step-3.5-flash need?
Q4_K_M is exactly 119,937,953,440 bytes (111.70 GiB) in weights. Add the KV cache, which depends on your context length, plus roughly half a gigabyte of runtime overhead.
How large is step-3.5-flash's KV cache?
13.03 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 step-3.5-flash 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.