⚠️ KNAPP (<12% RESERVE) (GGUF Q3_K_M (3.91 bpw))
Mixtral-8x7B-Instruct (MoE) on NVIDIA RTX 3090 (24GB VRAM)
Standard Q4_K_M (27.8 GB) exceeds 24 GB by 3.80 GB. Use GGUF Q3_K_M (3.91 bpw), offload layers to system RAM, or use 2x GPUs.
🎛️ Interaktiver VRAM-, Kontext- & Offload-Konfigurator
📊 Echtzeit-Speicher- & Performance-Telemetrie
27.8 GB / 24 GB
🟦 Modellgewichte: 26.31 GB
🟪 KV-Cache: 1 GB
🟨 Engine-Puffer: 0.49 GB
Benötigter GPU-VRAM27.8 GB
Benötigter System-RAM (CPU)0.00 GB
Verfügbarer Hardware-VRAM24 GB (1x NVIDIA RTX 3090)
VRAM-Reserve / Defizit-3.80 GB
Geschätzte Decode-Geschwindigkeit~35.1 tokens/sec
Geschätzte Prefill-Geschwindigkeit~1431 tokens/sec
Time-to-First-Token (4K Prompt)~2862 ms
Transformer-TopologieMoE-GQA (32L, 8/32 KV/Q heads)
🚀 Startbefehl (vLLM / llama.cpp / Ollama)
ollama run mixtral:8x7b # Or llama.cpp server (8K context, Flash Attention): llama-server -hf mistralai/Mixtral-8x7B-Instruct-v0.1-GGUF -c 8192 -ngl 99 -fa
CLOUD-GPU PREISVERGLEICH & MIETEN-VS-KAUFEN RECHNER
Nicht genug lokaler VRAM? Cloud-GPU in 60 Sekunden starten (Mixtral-8x7B-Instruct (MoE): 27.8 GB in 4-bit)
Recommended Cloud Tier: L40S / RTX 6000 Ada (48GB) · Full FP16 Needs: 88.92 GB
Amortisationszeit (Kauf vs. Miete): ~32 months (vs $750 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 → |
| Vast.ai | $0.29 / hr | $0.95 / hr | $1.79 / hr | $34.80 / mo | Save 50–70% on RTX 4090 / 5090 / A100 rentals | Spot-GPU mieten → |
| Vultr Cloud GPU | — | $1.79 / hr | $2.69 / hr | $214.80 / mo (A100) | $300 Free Credit | $300 Guthaben sichern → |
| DigitalOcean GPU | — | — | $2.99 / hr | $358.80 / mo (H100) | $200 Free Credit (60d) | $200 Startguthaben → |
Alle Quantisierungsstufen im Detail: Mixtral-8x7B-Instruct (MoE) × NVIDIA RTX 3090
| Quantization Format | Core / Emb BPW | Weights (GiB) | KV Cache (8K) | Total VRAM | 1x NVIDIA RTX 3090 (24GB) | Decode / Prefill | Min GPUs |
|---|---|---|---|---|---|---|---|
| FP16 / BF16 (Unquantized) | 16 / 16 | 86.99 GB | 1 GB | 88.47 GB | Nein (+64.5GB) | ~3 / 1431 tok/s | 4x |
| FP8 (W8A8 / E4M3) | 8.25 / 8.5 | 44.86 GB | 1 GB | 46.35 GB | Nein (+22.4GB) | ~8.4 / 1431 tok/s | 2x |
| GGUF Q8_0 (8.50 bpw) | 8.5 / 8.5 | 46.21 GB | 1 GB | 47.7 GB | Nein (+23.7GB) | ~7.9 / 1431 tok/s | 2x |
| GGUF Q6_K (6.56 bpw) | 6.56 / 6.56 | 35.66 GB | 1 GB | 37.15 GB | Nein (+13.1GB) | ~13.5 / 1431 tok/s | 2x |
| GGUF Q5_K_M (5.69 bpw) | 5.69 / 6.56 | 30.96 GB | 1 GB | 32.45 GB | Nein (+8.5GB) | ~19.6 / 1431 tok/s | 2x |
| GGUF Q4_K_M / AWQ (4.83 bpw) | 4.83 / 6.56 | 26.31 GB | 1 GB | 27.8 GB | Nein (+3.8GB) | ~35.1 / 1431 tok/s | 2x |
| GGUF IQ4_XS (4.25 bpw) | 4.25 / 5.5 | 23.14 GB | 1 GB | 24.63 GB | Nein (+0.6GB) | ~74.9 / 1431 tok/s | 2x |
| GGUF Q3_K_M (3.91 bpw) | 3.91 / 5 | 21.29 GB | 1 GB | 22.78 GB | KNAPP (<12% RESERVE) | ~102 / 1431 tok/s | 1x |
Dieses Modell auf anderen GPUs testen
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