GigaChat Lightning 10B on NVIDIA RTX 4070 Laptop (80-115W)
RTX 4070 Laptop (80-115W) runs GigaChat Lightning 10B at Q4_K_M — 56 tok/s. Usable on 8 GB VRAM — see full quantization options below.
Model Size
10B
Device VRAM
8 GB
Bandwidth
256 GB/s
Quantization
Q4_K_M
Performance by Quantization
OwnRig currently has one published compatibility entry for GigaChat Lightning 10B on NVIDIA RTX 4070 Laptop (80-115W) at Q4_K_M. This is the best supported pairing we can stand behind today.
| Quantization | Speed | TTFT | Fits in VRAM | Rating | Confidence |
|---|---|---|---|---|---|
| Q4_K_M | 56 tok/s | 107ms | ✓ Yes | Acceptable | estimated |
Notes
Q4_K_M
Q4_K_M fits in 8GB with 2GB headroom. Small MoE model; 1.8B active per token keeps decode speed high once loaded.
About GigaChat Lightning 10B
GigaChat Lightning 10B (10B) is a chat, multi-purpose model. Compact MoE model with 10B total parameters and around 1.8B active per token. Interesting efficiency play for chat workloads that want MoE-style speed without the memory cost of larger expert models.
View all GigaChat Lightning 10B hardware options →About NVIDIA RTX 4070 Laptop (80-115W)
NVIDIA RTX 4070 Laptop (80-115W) has 8 GB at 256 GB/s. Street price: $0.
See all models NVIDIA RTX 4070 Laptop (80-115W) can run →Estimate method: Estimated from small-model MoE benchmarks and bandwidth scaling. Reference hardware source: github.com (2026-03-24)
Performance varies by driver version, inference engine, quantization method, context length, and system configuration. Figures shown are estimates based on community benchmarks and may not reflect your exact setup. Product names are trademarks of their respective owners. OwnRig is independent and not affiliated with any hardware or AI model provider.