Alibaba Cloud35B (3B active)Q4_K_M 下约 22 GB 显存

Qwen 3.5 35B-A3B — 显存、速度与本地部署

作者: Jakub Rusinowski · 最后更新:

MoE variant with ~36B total parameters but only 3B active per token — best MoE efficiency in the family. Fits on an RTX 4090/3090 at Q4 (~21.4 GB) while outperforming most 70B dense models. Note: third-party GGUF imports can fail in Ollama due to a separate mmproj vision file; use the official `qwen3.5:35b` library tag, which bundles vision support.

Qwen 3.5 35B-A3B 在 Q4_K_M 下约需 22 GB 显存——量化权重加框架开销,不含 KV 缓存。在 Apple Silicon 上,这部分来自统一内存。

逻辑91
创意89
编程92

按量化级别的显存与速度

计算基准:NVIDIA RTX 4090 (24 GB)。仅含权重与开销:该模型架构未公开,因此未计入 KV 缓存。

量化显存速度(估算)适配
Q2_K
2.63 bpw
12.3 GB~209 tok/s可运行
Q3_K_M
3.41 bpw
15.7 GB~193 tok/s可运行
Q4_K_M
4.83 bpw
21.9 GB~170 tok/s勉强
Q5_K_M
5.67 bpw
25.6 GB~24 tok/s需卸载
Q6_K
6.56 bpw
29.5 GB~22 tok/s需卸载
Q8_0
8.50 bpw
38 GB~19 tok/s需卸载
F16
16.00 bpw
70.8 GB—放不下

黑色标记 = NVIDIA RTX 4090 (24 GB) 上的可用显存。 估算来自内存带宽屋顶线模型,详见 方法说明页. Qwen 3.5 35B-A3B 显存计算器 →

运行 Qwen 3.5 35B-A3B

目录中能运行 Qwen 3.5 35B-A3B 的最便宜 GPU 是 AMD Radeon RX 7900 XTX (24 GB).

购买此硬件 AMD Radeon RX 7900 XTX 24GB — 24 GB VRAM · 355 W board power立即云端部署 RunPod 上的 RTX 4090 — 低至 $0.34/小时 · 价格核实于 2026-07

或在 Vast.ai 比较,低至 $0.35/小时 (typical low · varies)

作为亚马逊联盟成员,我们从符合条件的购买中获得收入。云 GPU 链接为推荐链接——我们可能获得佣金,您无需额外付费。

联盟营销声明: 本页部分链接为联盟推广链接——如果你通过它们购买,LLM Configurator 可能会获得佣金,而你无需支付任何额外费用。作为亚马逊联盟成员(Amazon Associate),LLM Configurator 会从符合条件的购买中获得收益。
AMD Radeon RX 7900 XTX 24GB
24 GB VRAM · 355 W board power
2026年价格波动较大——请以当前商品页价格为准。

如何运行 Qwen 3.5 35B-A3B

安装 Ollama,然后运行:

ollama run qwen3.5:35b-a3b
Hugging Face 上的权重: Qwen/Qwen3.5-35B-A3B-Instruct ↗

规格

Curated — A hand-written entry from before this catalogue recorded its sources. The figures are long-standing but their provenance is not on file.

参数量
~36 Billion (3B active)
上下文窗口
262,144
架构
Hybrid Gated DeltaNet + MoE
提供商
Alibaba Cloud
许可证
Apache 2.0
规格量化
Q4_K_M
系统内存
32 GB
记录更新于
2026-02-24
许可证Apache-2.0允许商业使用

Commercial use permitted. No usage restrictions beyond attribution.

质量与使用场景

评分由模型作者或独立评测方发布——衡量质量而非吞吐量,并非我们实测。

最适合reasoningcodinggeneral useconsumer gpu

我的 GPU 能运行 Qwen 3.5 35B-A3B 吗?

Qwen 3.5 的其他尺寸

Qwen 3.5 35B-A3B — 常见问题

How much VRAM does Qwen 3.5 35B-A3B need?

About 22 GB at Q4_K_M — quantized weights plus framework overhead, before any KV cache. The cache grows with context length and is added on top; the table above folds it in. Apple Silicon counts unified memory toward the same figure.

Does Qwen 3.5 35B-A3B run on an RTX 4090 (24 GB)?

Yes. Qwen 3.5 35B-A3B needs about 22 GB at Q4_K_M, inside a 24 GB card, at an estimated 170 tokens/sec.

How do I run Qwen 3.5 35B-A3B locally?

Install Ollama and run `ollama run qwen3.5:35b-a3b`. That pulls the weights and starts a local OpenAI-compatible endpoint; after the download nothing leaves the machine.

What other sizes does Qwen 3.5 come in?

Qwen 3.5 0.8B (1 GB), Qwen 3.5 2B (2 GB), Qwen 3.5 4B (3 GB), Qwen 3.5 9B (6 GB), Qwen 3.5 27B (17 GB), Qwen 3.5 35B-A3B (22 GB), Qwen 3.5 122B-A10B (74 GB), Qwen 3.5 397B-A17B (240 GB). Every size shares the family's training and licence; the larger ones score higher and need proportionally more memory.