Local LLM model fit

Can my GPU run Qwen3.8 27B?

Qwen3.8 27B is a 27B Qwen3.8 model. This page estimates Q4 VRAM fit, Ollama command, context planning, and fallback choices for common local AI GPUs.

Check Qwen3.8 27B in the calculator

Q4 runtime estimate22 GB
Ollama commandollama run qwen3.8:27b-q4_K_M
Recommended GPURTX 3090/4090 24GB as tight/offload target, RTX 5090 32GB or larger preferred for long context

Best use

Current 27B-class local coding, multimodal analysis, and long-running tool agents on 24GB-class GPUs. Weakness: The 18GB Q4 weights require RAM offload on a 24GB GPU once runtime reserve and long multimodal context are included.

GPU fit table

HardwareExamplesClean capacityQ4 needStatusCalculator
6 GB VRAM entry GPUGTX 1660, RTX 2060 6GB4.5 GB usable VRAM22 GBToo largeOpen calculator
8 GB VRAM mainstream GPURTX 3060 Ti, RTX 4060, RTX 30706.5 GB usable VRAM22 GBRAM offloadOpen calculator
10 GB VRAM older high-end GPURTX 3080 10GB8.5 GB usable VRAM22 GBRAM offloadOpen calculator
12 GB VRAM local agent GPURTX 3060 12GB, RTX 4070, RTX 507010.5 GB usable VRAM22 GBRAM offloadOpen calculator
16 GB VRAM creator GPURTX 4060 Ti 16GB, RTX 4080, RTX 5070 Ti, RTX 508014.5 GB usable VRAM22 GBRAM offloadOpen calculator
24 GB VRAM homelab workstationRTX 3090, RTX 409022.5 GB usable VRAM22 GBRAM offloadOpen calculator
32 GB VRAM Blackwell workstationRTX 509030.5 GB usable VRAM22 GBRuns locallyOpen calculator
48 GB VRAM workstationRTX A6000, L40S 48GB46.5 GB usable VRAM22 GBRuns locallyOpen calculator
Apple Silicon 32 GB unified memoryM2 Max 32GB, M3 Max 36GB26 GB unified22 GBRAM offloadOpen calculator
Apple Silicon 256 GB unified memoryMac Studio M3 Ultra 256GB, Mac Studio M4 Ultra 256GB250 GB unified22 GBRuns locallyOpen calculator

Quantization memory estimate on a 12GB GPU preset

QuantizationEstimated memoryUse case
Q4 / 4-bit22 GBDefault local inference balance

Data sources and confidence

This is a practical planning estimate, not a benchmark. Real memory use changes with backend, context length, KV cache, quantization file, drivers, and offloading settings.

Verified

2026-08-24

Confidence

high

Cloud fallback

Compare API costs on apiroute.dev

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