GLM-4-32B-0414 VRAM Requirements & GPU Benchmarks
GLM-4-32B-0414 (32B total, 32B active, 61L, 8 KV heads, vocab 151552) requires 20.77 GB in 4-bit Q4_K_M, 33.19 GB in FP8, and 62 GB in FP16 at 8K context.
CLOUD-GPU PREISVERGLEICH & MIETEN-VS-KAUFEN RECHNER
Nicht genug lokaler VRAM? Cloud-GPU in 60 Sekunden starten (GLM-4-32B-0414: 20.77 GB in 4-bit)
Recommended Cloud Tier: RTX 4090 (24GB) Β· Full FP16 Needs: 62 GB
Amortisationszeit (Kauf vs. Miete): ~32 months (vs $1,699 hardware)
| Cloud Provider | RTX 4090 (24GB) | A100 (80GB) | H100 (80GB) | Est. Monthly Cost (4h/day) | Free Credit / Trial | Deploy |
|---|---|---|---|---|---|---|
| RunPod | $0.44 / hr | $1.39 / hr | $2.39 / hr | $52.80 / mo | Instant PyTorch / vLLM Templates + Serverless GPU | Auf RunPod starten β |
| Vast.ai | $0.29 / hr | $0.95 / hr | $1.79 / hr | $34.80 / mo | Save 50β70% on RTX 4090 / 5090 / A100 rentals | Spot-GPU mieten β |
| Vultr Cloud GPU | β | $1.79 / hr | $2.69 / hr | $214.80 / mo (A100) | $300 Free Credit | $300 Guthaben sichern β |
| DigitalOcean GPU | β | β | $2.99 / hr | $358.80 / mo (H100) | $200 Free Credit (60d) | $200 Startguthaben β |
| GPU Hardware | VRAM | Bandwidth | FP16 (62GB) | Q4_K_M (20.77GB) | Decode / Prefill Speed | Report |
|---|---|---|---|---|---|---|
| NVIDIA RTX 5090 | 32 GB | 1792 GB/s | Nein | Ja (65%) | ~63.7 / 1702 tok/s | Exakten VRAM & Speed berechnen β |
| NVIDIA RTX 4090 | 24 GB | 1008 GB/s | Nein | Ja (87%) | ~35.9 / 1342 tok/s | Exakten VRAM & Speed berechnen β |
| NVIDIA RTX 5080 | 16 GB | 960 GB/s | Nein | Nein | ~10.2 / 916 tok/s | Exakten VRAM & Speed berechnen β |
| NVIDIA RTX 4080 Super | 16 GB | 736 GB/s | Nein | Nein | ~9.6 / 848 tok/s | Exakten VRAM & Speed berechnen β |
| NVIDIA RTX 4070 Ti Super | 16 GB | 672 GB/s | Nein | Nein | ~9.3 / 717 tok/s | Exakten VRAM & Speed berechnen β |
| NVIDIA RTX 3090 | 24 GB | 936 GB/s | Nein | Ja (87%) | ~33.3 / 577 tok/s | Exakten VRAM & Speed berechnen β |
| NVIDIA RTX 4060 Ti 16GB | 16 GB | 288 GB/s | Nein | Nein | ~6.7 / 358 tok/s | Exakten VRAM & Speed berechnen β |
| NVIDIA RTX 3060 12GB | 12 GB | 360 GB/s | Nein | Nein | ~5.5 / 206 tok/s | Exakten VRAM & Speed berechnen β |
| NVIDIA RTX 6000 Ada | 48 GB | 960 GB/s | Nein | Ja (43%) | ~34.1 / 1480 tok/s | Exakten VRAM & Speed berechnen β |
| NVIDIA RTX A6000 | 48 GB | 768 GB/s | Nein | Ja (43%) | ~27.3 / 629 tok/s | Exakten VRAM & Speed berechnen β |
| NVIDIA L40S 48GB | 48 GB | 864 GB/s | Nein | Ja (43%) | ~30.7 / 2941 tok/s | Exakten VRAM & Speed berechnen β |
| NVIDIA A100 80GB SXM | 80 GB | 2039 GB/s | Ja | Ja (26%) | ~72.5 / 2535 tok/s | Exakten VRAM & Speed berechnen β |
| NVIDIA H100 80GB SXM | 80 GB | 3350 GB/s | Ja | Ja (26%) | ~119.2 / 8036 tok/s | Exakten VRAM & Speed berechnen β |
| NVIDIA H200 141GB SXM | 141 GB | 4800 GB/s | Ja | Ja (15%) | ~170.7 / 8036 tok/s | Exakten VRAM & Speed berechnen β |
| NVIDIA Blackwell B200 192GB | 192 GB | 8000 GB/s | Ja | Ja (11%) | ~284.6 / 18000 tok/s | Exakten VRAM & Speed berechnen β |
| AMD Instinct MI300X 192GB | 192 GB | 5300 GB/s | Ja | Ja (11%) | ~188.5 / 10619 tok/s | Exakten VRAM & Speed berechnen β |
| 2x NVIDIA RTX 3090 (48GB) | 48 GB | 936 GB/s | Nein | Ja (43%) | ~33.3 / 1154 tok/s | Exakten VRAM & Speed berechnen β |
| 2x NVIDIA RTX 4090 (48GB) | 48 GB | 1008 GB/s | Nein | Ja (43%) | ~35.9 / 2685 tok/s | Exakten VRAM & Speed berechnen β |
| 4x NVIDIA A100 80GB (320GB) | 320 GB | 2039 GB/s | Ja | Ja (6%) | ~72.5 / 10140 tok/s | Exakten VRAM & Speed berechnen β |
| 8x NVIDIA H100 80GB (640GB) | 640 GB | 3350 GB/s | Ja | Ja (3%) | ~119.2 / 18000 tok/s | Exakten VRAM & Speed berechnen β |
| Apple M4 Max (128GB Unified) | 128 GB | 546 GB/s | Ja | Ja (16%) | ~21.2 / 299 tok/s | Exakten VRAM & Speed berechnen β |
| Apple M3 Ultra Mac Studio (512GB) | 512 GB | 819 GB/s | Ja | Ja (4%) | ~31.9 / 440 tok/s | Exakten VRAM & Speed berechnen β |
| Apple M4 Pro Mac Mini (64GB) | 64 GB | 273 GB/s | Ja | Ja (32%) | ~10.6 / 150 tok/s | Exakten VRAM & Speed berechnen β |