Step-3.7 Flash (198B-A11B) on Ryzen AI Max+ 395 128GB (128GB) — VRAM, KV Cache & Throughput

Step-3.7 Flash (198B-A11B) (198B total, 11B active, Sparse MoE + GQA) uses 112 GiB of 4-bit weights (Q4_K_M), requiring 112.91 GiB total at 8K context and 113.76 GiB at 32K on Ryzen AI Max+ 395 128GB (~20.5 tok/s decode).

Interactive Sizing Workbench

Full Compatibility Report →
128 GB · 256 GB/s
Tight Fit (<8% Headroom)
Config-derived formula HF config.json ↗
Memory Allocation Breakdown (GiB) 112.91 GiB (121.24 GB) / 128 GiB (88%)
Model Weights: 112 GiB KV Cache & State: 0.35 GiB Runtime & Activation Buffers: 0.56 GiB System RAM Offload: 0 GiB
Required GPU Memory
112.91 GiB
121.24 GB (decimal)
Usable Hardware Memory
99.8 GiB
128 GB (physical)
Safe Headroom
-13.11 GiB
88% utilization
Est. Decode Throughput
~20.5 tok/s
11B active params
Est. Prefill Throughput
~1126 tok/s
4K Prompt TTFT: ~3636 ms
Est. Cost / 1M Tokens
$35.09
Sparse MoE + GQA · Apache-2.0

Recommended Hardware for Current Configuration

Best Single GPU
Instinct MI300X 192GB (192GB)
~$15,000
Best Value / Used GPU
2x A100 80GB SXM
160GB · ~$24,000
Apple Unified Memory
Mac Studio M4 Ultra 256GB
~$5,999
Cloud From
DigitalOcean · $2.59 / hr
1x Instinct MI300X 192GB

Production Launch Commands

llama.cpp (GGUF)
llama-server -hf stepfun-ai/Step-3.7-Flash-GGUF:Q4_K_M \
  --ctx-size 8192 -ngl 999 --flash-attn
vLLM
vllm serve stepfun-ai/Step-3.7-Flash \
  --max-model-len 8192 --gpu-memory-utilization 0.92
Live Token Speed Simulator (TTFT ~3636ms · ~20.5 tok/s)
[Step-3.7 Flash (198B-A11B) · 112.91 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
~35.7 months
Est. local power: $15.96 / mo
Provider Recommended Instance Total VRAM Hourly Rate Monthly at Selected Hours Billing Mode Deploy
RunPod 1x H200 141GB SXM (Community Cloud) 141 GB $3.59 / hr $436.54 / mo Per-second Deploy GPU ↗
Vast.ai 1x H200 141GB SXM (Verified Host · NVL) 141 GB $3.87 / hr $470.47 / mo Spot / On-demand Deploy GPU ↗
Vultr ($300 Free Credit*) 4x L40S 48GB (Dedicated Instance · $300 Credit*) 192 GB $6.68 / hr $812.77 / mo Hourly Deploy GPU ↗
Vultr Cloud GPU 4x L40S 48GB (Dedicated Instance) 192 GB $6.68 / hr $812.77 / mo Hourly Deploy GPU ↗
DigitalOcean 1x Instinct MI300X 192GB (Dedicated Instance) 192 GB $2.59 / hr $314.94 / 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) — Step-3.7 Flash (198B-A11B)

QLoRA (4b) Tight Fit (<8% Headroom)
114.62 GiB
Model Weights: 112 GiB · Gradients + Optimizer: 1.54 GiB · Act: 1.08 GiB
Recommended GPU: Instinct MI300X 192GB (192GB)
LoRA (16b) Exceeds Available GPU Memory
372.65 GiB
Model Weights: 368.8 GiB · Gradients + Optimizer: 2.42 GiB · Act: 1.43 GiB
Recommended GPU: 4x H200 141GB SXM (564GB)
Full BF16 Exceeds Available GPU Memory
1514.6 GiB
Model Weights: 368.8 GiB · Gradients + Optimizer: 1143.28 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 Step-3.7 Flash (198B-A11B) (112.91 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

Step-3.7 Flash (198B-A11B) uses Sparse MoE + GQA (198B total, 11B active per token). Moving from 8K to 32K context expands FP16 KV cache from 0.35 GiB to 1.2 GiB; enabling 8-bit KV cache (llama.cpp -ctk q8_0 -ctv q8_0 or vLLM --kv-cache-dtype fp8) saves 0.6 GiB at 32K (reducing total VRAM to 113.16 GiB).

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

Step-3.7 Flash (198B-A11B) VRAM scaling from 4K to 128K context (4K: 112.77 GiB, 8K: 112.91 GiB, 32K: 113.76 GiB, 128K: 117.13 GiB) 4K 112.77 GiB (KV 0.21 GiB) 8K 112.91 GiB (KV 0.35 GiB) 32K 113.76 GiB (KV 1.2 GiB) 128K 117.13 GiB (KV 4.57 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 — Step-3.7 Flash (198B-A11B) @ 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) 368.8 GiB 0.35 GiB 369.71 GiB (396.97 GB) ~3.1 tok/s Exceeds Available GPU Memory Multi-GPU Required Official checkpoint size
FP8 / GGUF Q8_0 (8-bit — Near-Lossless) (Q8_0) 195.93 GiB 0.35 GiB 196.84 GiB (211.36 GB) ~7.5 tok/s Exceeds Available GPU Memory Instinct MI325X 256GB (256GB) Config-derived formula
GGUF Q6_K (6-bit — High Precision) (Q6_K) 151.21 GiB 0.35 GiB 152.12 GiB (163.34 GB) ~12.1 tok/s Exceeds Available GPU Memory Instinct MI300X 192GB (192GB) Config-derived formula
GGUF Q5_K_M (5-bit — Balanced) (Q5_K_M) 131.26 GiB 0.35 GiB 132.17 GiB (141.92 GB) ~16.8 tok/s Exceeds Available GPU Memory Instinct MI300X 192GB (192GB) Config-derived formula
Q4_K_M / UD-Q4_K_XL / AWQ (4-bit — Recommended) (Q4_K_M) 112 GiB 0.35 GiB 112.91 GiB (121.24 GB) ~20.5 tok/s Tight Fit (<8% Headroom) Instinct MI300X 192GB (192GB) Config-derived formula
GGUF IQ4_XS (4.25-bit — Compact) (IQ4_XS) 98.12 GiB 0.35 GiB 99.03 GiB (106.33 GB) ~23.3 tok/s Fits with Safe Headroom Instinct MI300X 192GB (192GB) Config-derived formula
GGUF Q3_K_M (3-bit — Low VRAM) (Q3_K_M) 90.26 GiB 0.35 GiB 91.17 GiB (97.89 GB) ~25.1 tok/s Fits with Safe Headroom Instinct MI300X 192GB (192GB) Config-derived formula
GGUF UD-Q2_K_XL (2-bit — Extreme MoE) (UD-Q2_K_XL) 63.6 GiB 0.35 GiB 64.51 GiB (69.27 GB) ~34.6 tok/s Fits with Safe Headroom RTX PRO 6000 Blackwell (96GB) Config-derived formula

Technical Specifications & FAQ

Does Step-3.7 Flash (198B-A11B) fit on Ryzen AI Max+ 395 128GB (128GB)?

In 4-bit (Q4_K_M) at 8,192 context, Step-3.7 Flash (198B-A11B) requires 112.91 GiB total GPU memory (112 GiB weights + 0.35 GiB KV cache + 0.56 GiB runtime buffers) against 99.8 GiB usable on Ryzen AI Max+ 395 128GB, delivering ~20.5 tok/s decode.

How much VRAM does Step-3.7 Flash (198B-A11B) need at 32K context?

At 32,768 context tokens, Step-3.7 Flash (198B-A11B) (Sparse MoE + GQA) allocates 1.2 GiB for KV cache and state, bringing total 4-bit VRAM to 113.76 GiB (122.15 GB decimal).

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