GLM-5.3 Flash (320B-A18B) on Ryzen AI Max+ 395 128GB (128GB) — VRAM, KV Cache & Throughput

GLM-5.3 Flash (320B-A18B) (320B total, 18B active, Multi-head Latent Attention (MLA) MoE) uses 180.93 GiB of 4-bit weights (Q4_K_M), requiring 181.84 GiB total at 8K context and 182.9 GiB at 32K on Ryzen AI Max+ 395 128GB (~8.5 tok/s decode).

Interactive Sizing Workbench

Full Compatibility Report →
128 GB · 256 GB/s
Exceeds Available GPU Memory
Config-derived formula HF config.json ↗
Memory Allocation Breakdown (GiB) 181.84 GiB (195.25 GB) / 128 GiB (142%)
Model Weights: 180.93 GiB KV Cache & State: 0.35 GiB Runtime & Activation Buffers: 0.56 GiB System RAM Offload: 0 GiB
Required GPU Memory
181.84 GiB
195.25 GB (decimal)
Usable Hardware Memory
99.8 GiB
128 GB (physical)
Safe Headroom
-82.04 GiB
142% utilization
Est. Decode Throughput
~8.5 tok/s
18B active params
Est. Prefill Throughput
~688 tok/s
4K Prompt TTFT: ~5951 ms
Est. Cost / 1M Tokens
$124.18
Multi-head Latent Attention (MLA) MoE · MIT

Recommended Hardware for Current Configuration

Best Single GPU
Instinct MI325X 256GB (256GB)
~$21,000
Best Value / Used GPU
2x H200 141GB SXM
282GB · ~$64,000
Apple Unified Memory
Mac Studio M4 Ultra 256GB
~$5,999
Cloud From
DigitalOcean · $3.80 / hr
1x Instinct MI325X 256GB

Production Launch Commands

llama.cpp (GGUF)
llama-server -hf unsloth/GLM-5.3-Flash-GGUF:Q4_K_M \
  --ctx-size 8192 -ngl 999 --flash-attn
vLLM
vllm serve zai-org/GLM-5.3-Flash \
  --max-model-len 8192 --gpu-memory-utilization 0.92
Live Token Speed Simulator (TTFT ~5951ms · ~8.5 tok/s)
[GLM-5.3 Flash (320B-A18B) · 181.84 GiB] allocated on target GPU. Prefill completed in TTFT window; streaming autoregressive tokens at memory-bandwidth-bound rate...

Cloud GPU Comparison & Rent-vs-Buy TCO

Verified public rates across RunPod, Vast.ai, Vultr, and DigitalOcean.

Verified: 2026-11-04
Purchase break-even
~25.5 months
Est. local power: $21.28 / mo
Provider Recommended Instance Total VRAM Hourly Rate Monthly at Selected Hours Billing Mode Deploy
RunPod 1x B300 288GB Blackwell Ultra (Community Cloud) 288 GB $6.94 / hr $843.90 / mo Per-second Deploy GPU ↗
Vast.ai 2x H200 141GB SXM (Verified Host · NVL) 282 GB $7.74 / hr $940.94 / mo Spot / On-demand Deploy GPU ↗
Vultr ($300 Free Credit*) 8x A100 80GB SXM (Dedicated Instance · $300 Credit*) 640 GB $19.18 / hr $2331.80 / mo Hourly Deploy GPU ↗
Vultr Cloud GPU 8x A100 80GB SXM (Dedicated Instance) 640 GB $19.18 / hr $2331.80 / mo Hourly Deploy GPU ↗
DigitalOcean 1x Instinct MI325X 256GB (Dedicated Instance) 256 GB $3.80 / hr $462.08 / mo Per-second Deploy GPU ↗

Rates reflect public listings on the verification date and fluctuate with regional inventory.

Fine-Tuning VRAM Requirements (QLoRA / LoRA / Full) — GLM-5.3 Flash (320B-A18B)

QLoRA (4b) Exceeds Available GPU Memory
184.53 GiB
Model Weights: 180.93 GiB · Gradients + Optimizer: 2.52 GiB · Act: 1.08 GiB
Recommended GPU: Instinct MI325X 256GB (256GB)
LoRA (16b) Exceeds Available GPU Memory
601.44 GiB
Model Weights: 596.05 GiB · Gradients + Optimizer: 3.96 GiB · Act: 1.43 GiB
Recommended GPU: 4x B200 180GB (720GB)
Full BF16 Exceeds Available GPU Memory
2446.32 GiB
Model Weights: 596.05 GiB · Gradients + Optimizer: 1847.75 GiB · Act: 2.52 GiB
Recommended GPU: Multi-GPU Required

Engineering Sizing Notes & Optimization Playbook

Quick Hardware Verdict

A single Ryzen AI Max+ 395 128GB (128GB) cannot hold 4-bit GLM-5.3 Flash (320B-A18B) (181.84 GiB at 8K) entirely in VRAM. Use multi-GPU tensor parallelism, offload layers to system RAM, or deploy on a larger cloud GPU.

KV Cache & Runtime Tuning

GLM-5.3 Flash (320B-A18B) uses Multi-head Latent Attention (MLA) MoE (320B total, 18B active per token). Moving from 8K to 32K context expands FP16 KV cache from 0.35 GiB to 1.41 GiB; enabling 8-bit KV cache (llama.cpp -ctk q8_0 -ctv q8_0 or vLLM --kv-cache-dtype fp8) saves 0.71 GiB at 32K (reducing total VRAM to 182.19 GiB).

VRAM Scaling Across Context Windows (4K to 128K, 4-bit Weights)

GLM-5.3 Flash (320B-A18B) VRAM scaling from 4K to 128K context (4K: 181.67 GiB, 8K: 181.84 GiB, 32K: 182.9 GiB, 128K: 187.12 GiB) 4K 181.67 GiB (KV 0.18 GiB) 8K 181.84 GiB (KV 0.35 GiB) 32K 182.9 GiB (KV 1.41 GiB) 128K 187.12 GiB (KV 5.63 GiB) Ryzen AI Max+ 395 128GB (128GB)
Model weights remain constant while attention KV cache grows with context length and batch size.

Quantization Precision & Memory Matrix — GLM-5.3 Flash (320B-A18B) @ 8K

Quantization Format Weights (GiB) KV Cache Total VRAM (GiB) Decode Speed Compatibility (Ryzen AI Max+ 395 128GB) Recommended GPU Data Source
Native Weights (BF16 / FP8 / MXFP4 — Lossless) (BF16) 596.05 GiB 0.35 GiB 596.96 GiB (640.98 GB) ~1.7 tok/s Exceeds Available GPU Memory Multi-GPU Required Official checkpoint size
FP8 / GGUF Q8_0 (8-bit — Near-Lossless) (Q8_0) 316.65 GiB 0.35 GiB 317.56 GiB (340.98 GB) ~3.7 tok/s Exceeds Available GPU Memory Multi-GPU Required Config-derived formula
GGUF Q6_K (6-bit — High Precision) (Q6_K) 244.38 GiB 0.35 GiB 245.29 GiB (263.38 GB) ~5.3 tok/s Exceeds Available GPU Memory Instinct MI355X 288GB (288GB) Config-derived formula
GGUF Q5_K_M (5-bit — Balanced) (Q5_K_M) 212.1 GiB 0.35 GiB 213.01 GiB (228.72 GB) ~6.6 tok/s Exceeds Available GPU Memory Instinct MI325X 256GB (256GB) Config-derived formula
Q4_K_M / UD-Q4_K_XL / AWQ (4-bit — Recommended) (Q4_K_M) 180.93 GiB 0.35 GiB 181.84 GiB (195.25 GB) ~8.5 tok/s Exceeds Available GPU Memory Instinct MI325X 256GB (256GB) Config-derived formula
GGUF IQ4_XS (4.25-bit — Compact) (IQ4_XS) 158.51 GiB 0.35 GiB 159.42 GiB (171.18 GB) ~10.9 tok/s Exceeds Available GPU Memory Instinct MI300X 192GB (192GB) Config-derived formula
GGUF Q3_K_M (3-bit — Low VRAM) (Q3_K_M) 145.82 GiB 0.35 GiB 146.73 GiB (157.55 GB) ~12.9 tok/s Exceeds Available GPU Memory Instinct MI300X 192GB (192GB) Config-derived formula
GGUF UD-Q2_K_XL (2-bit — Extreme MoE) (UD-Q2_K_XL) 102.7 GiB 0.35 GiB 103.61 GiB (111.25 GB) ~22 tok/s Tight Fit (<8% Headroom) Instinct MI300X 192GB (192GB) Config-derived formula

Technical Specifications & FAQ

Does GLM-5.3 Flash (320B-A18B) fit on Ryzen AI Max+ 395 128GB (128GB)?

In 4-bit (Q4_K_M) at 8,192 context, GLM-5.3 Flash (320B-A18B) requires 181.84 GiB total GPU memory (180.93 GiB weights + 0.35 GiB KV cache + 0.56 GiB runtime buffers) against 99.8 GiB usable on Ryzen AI Max+ 395 128GB, delivering ~8.5 tok/s decode.

How much VRAM does GLM-5.3 Flash (320B-A18B) need at 32K context?

At 32,768 context tokens, GLM-5.3 Flash (320B-A18B) (Multi-head Latent Attention (MLA) MoE) allocates 1.41 GiB for KV cache and state, bringing total 4-bit VRAM to 182.9 GiB (196.39 GB decimal).

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