RTP-LLM · text · mixture of experts

Qwen3-Coder-30B-A3B-Instruct-RTPurbo

RTP-LLM/Qwen3-Coder-30B-A3B-Instruct-RTPurbo

Qwen3-Coder-30B-A3B-Instruct-RTPurbo at I1-IQ1_S is exactly 6,416,505,440 bytes (5.98 GiB / 6.42 GB) — an effective 1.681 bits per weight, not the nominal 1. Its KV cache at 32K is 3.00 GiB.

From the file· summed from 1 file(s)From the file· KV per layer
Parameters
30.5B
total, not active
Architecture
qwen3moe
48 layers
Context
262,144
native (config.json)
License

Shipped quantizations

exact bytes, summed from published files
QuantSizeExact bytesEffective bpwTensorsPublisher
I1-IQ1_S5.98 GiB6,416,505,4401.681mradermacher
I1-IQ1_M6.59 GiB7,078,287,9681.855mradermacher
I1-IQ2_XXS7.62 GiB8,181,258,8482.144mradermacher
I1-IQ2_XS8.45 GiB9,076,218,4642.378mradermacher
I1-IQ2_S8.65 GiB9,287,127,6482.433mradermacher
I1-IQ2_M9.47 GiB10,169,504,3522.665mradermacher
I1-Q2_K_S9.80 GiB10,519,360,0962.756mradermacher
I1-Q2_K10.49 GiB11,258,606,1762.950mradermacher
I1-IQ3_XXS11.04 GiB11,849,323,1043.105mradermacher
I1-IQ3_XS11.73 GiB12,598,438,4963.301mradermacher
I1-Q3_K_S12.38 GiB13,292,464,7363.483mradermacher
I1-IQ3_S12.39 GiB13,299,149,4083.485mradermacher
I1-IQ3_M12.59 GiB13,513,058,9123.541mradermacher
I1-Q3_K_M13.70 GiB14,711,843,4243.855mradermacher
I1-Q3_K_L14.81 GiB15,900,666,4644.166mradermacher
I1-IQ4_XS15.24 GiB16,368,345,6964.289mradermacher
I1-Q4_016.19 GiB17,379,983,9684.554mradermacher
I1-Q4_K_S16.26 GiB17,456,005,7284.574mradermacher
I1-Q4_K_M17.28 GiB18,556,682,8484.862mradermacher
I1-Q4_117.87 GiB19,192,496,7365.029mradermacher
I1-Q5_K_S19.63 GiB21,080,506,9765.524mradermacher
I1-Q5_K_M20.23 GiB21,725,577,8245.692mradermacher
I1-Q6_K23.37 GiB25,092,528,7366.575mradermacher

KV cache by context

computed per layer
ContextKV cache (f16)Flat formulaOverstated byFull / windowed / recurrent
4,0960.38 GiB0.38 GiB48 / 0 / 0
8,1920.75 GiB0.75 GiB48 / 0 / 0
16,3841.50 GiB1.50 GiB48 / 0 / 0
32,7683.00 GiB3.00 GiB48 / 0 / 0
65,5366.00 GiB6.00 GiB48 / 0 / 0
131,07212.00 GiB12.00 GiB48 / 0 / 0

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 I1-IQ1_S at roughly 15.99 GiB. The real file is 5.98 GiB, because a quantization is a mixture and some tensors are always kept at higher precision.

Architecture

from config.json
Layers
48
Attention heads
32
KV heads
4
Head dim
128
Hidden size
2048
Vocab
151,936
Sliding window
none
SWA period
MLA
no
Experts
128
Experts per token
8
use_sliding_window
false

Questions people ask

How much VRAM does Qwen3-Coder-30B-A3B-Instruct-RTPurbo need?
I1-IQ1_S is exactly 6,416,505,440 bytes (5.98 GiB) in weights. Add the KV cache, which depends on your context length, plus roughly half a gigabyte of runtime overhead.
How large is Qwen3-Coder-30B-A3B-Instruct-RTPurbo's KV cache?
3.00 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.
Is Qwen3-Coder-30B-A3B-Instruct-RTPurbo a mixture-of-experts model?
Yes — 128 experts, 8 routed per token. Every expert must be resident, but only the routed ones are read per token, which is why its memory requirement and its speed behave very differently.
Which quantization of Qwen3-Coder-30B-A3B-Instruct-RTPurbo 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.