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How much VRAM does Qwen3.8 2.4T A95B need?

Qwen3.8 2.4T A95B needs 1,381 GB for its weights at 4-bit, 1,384 GB with an 8K context and 1,386 GB with 32K. At 8-bit, 2,423 GB.

Parameters
2.4T
Active per token
95B
Longest context
256K
Released
Aug 2026
License
Qwen3.8-Max License
Strongest at
Chat, Coding, Agents

Memory at each precision

Memory Qwen3.8 2.4T A95B needs at each precision and context length
PrecisionWeightsWith 8KWith 32KWith 128K
16-bit4,556 GB4,559 GB4,561 GB4,570 GB
8-bit2,421 GB2,423 GB2,425 GB2,434 GB
6-bit1,868 GB1,871 GB1,873 GB1,881 GB
5-bit1,620 GB1,623 GB1,625 GB1,634 GB
4-bit1,381 GB1,384 GB1,386 GB1,394 GB
3-bit1,113 GB1,116 GB1,118 GB1,127 GB
2-bit854 GB857 GB859 GB868 GB
1.6-bit470 GB472 GB474 GB483 GB

One conversation, 16-bit context cache, runtime overhead included.

What runs it

The best way Qwen3.8 2.4T A95B runs on common GPUs, Macs and AI boxes
MachineBest fitContextSpeedFirst reply
RTX 3060 12 GBToo big
RTX 4060 Ti 16 GBToo big
RTX 3090Too big
RTX 4090Too big
RTX 5090Too big
2× RTX 3090Too big
RTX PRO 6000 BlackwellToo big
M4 Max 128 GBToo big
M5 Max 128 GBToo big
Ryzen AI Max+ 395 128 GBToo big
DGX Spark 128 GBToo big
M3 Ultra 256 GBToo big
M5 Ultra 512 GBToo big
H100 SXMToo big
DGX Station GB3001.6-bit, spills256K35 tok/s4.5 s
8× H200 NVL2-bit256K61 tok/s0.8 s

Best fit is the highest quality, up to 8-bit, that leaves 16K of context. First reply is the wait for a 2K prompt. Speeds are rough, plus or minus 25%.

How to run it

llama.cpp
llama-server -hf unsloth/Qwen3.8-2.4T-A95B-GGUF
vLLM
vllm serve Qwen/Qwen3.8-2.4T-A95B

Questions

How much VRAM does Qwen3.8 2.4T A95B need?

Qwen3.8 2.4T A95B needs 1,381 GB for its weights at 4-bit, 1,384 GB with an 8K context and 1,386 GB with 32K. At 8-bit, 2,423 GB.

Can Qwen3.8 2.4T A95B run on an RTX 4090?

Not on one card. The smallest machine here that runs it is the 8× H200 NVL.

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