TinyLlama
TinyLlama 1.1B Chat v0.6 (1.100000023841858B parameters) requires approximately 2.6 GB of VRAM with Q4_K_M quantization. For the best balance of quality and speed, we recommend hardware with at least 3 GB of VRAM.
Quick specs
Related models
Quick picks
Best hardware
Run this model
Quantization options
No hardware detected — fit column shows raw VRAM estimates
| Quant | Bits | VRAM | Quality | Fit |
|---|---|---|---|---|
Q2_K | 2 | 0.4 GB | Low | — |
Q3_K_S | 3 | 0.5 GB | Low | — |
NVFP4 | 4 | 0.6 GB | Medium | — |
Q4_K_M | 4 | 0.7 GB | Medium | — |
Q5_K_M | 5 | 0.8 GB | High | — |
Q6_K | 6 | 0.9 GB | High | — |
Q8_0 | 8 | 1.2 GB | Very High | — |
F16 | 16 | 2.3 GB | Maximum | — |
Hardware compatibility
Computing compatibility...
Memory breakdown
Frequently asked questions
TinyLlama 1.1B Chat v0.6 (1.100000023841858B parameters) requires approximately 2.6 GB of VRAM with Q4_K_M quantization. Lower quantizations like Q4_K_M use less memory but may reduce quality.
Yes, Intel Arc A380 6GB can run TinyLlama 1.1B Chat v0.6 with a compatibility score of 44/100. It provides 6 GB of memory and achieves approximately 15.4 tokens per second.
The recommended quantization for TinyLlama 1.1B Chat v0.6 is Q4_K_M, which offers the best balance between model quality and memory efficiency. Higher quantizations preserve more quality but require more VRAM.
The top recommended hardware for TinyLlama 1.1B Chat v0.6: GTX 1650 4GB (score: 49/100), RTX 3050 Ti Laptop 4GB (score: 49/100), Intel Arc A370M 4GB (score: 47/100). These provide the best combination of memory, bandwidth, and compute for running this model locally.
Yes, TinyLlama 1.1B Chat v0.6 is well-suited for chat. It was designed with these use cases in mind.
See also
