Bielik 1.5B V3.0 Instruct GGUF — Hardware Requirements & GPU Compatibility
Chat
Bielik 1.5B V3.0 Instruct GGUF is a 1.5B-parameter open language model from speakleash. At Q8_0 it needs about 1.65 GB of VRAM — see which GPUs and Macs can run it below.
703 downloads
7 likesSpecifications
- Publisher
- speakleash
- Parameters
- 1.5B
- Release Date
- 2026-01-28
- License
- Apache 2.0
Get Started
HuggingFace
How Much VRAM Does Bielik 1.5B V3.0 Instruct GGUF Need?
Select a quantization to see compatible GPUs below.
| Quantization | Bits | VRAM | + Context | File Size | Quality |
|---|---|---|---|---|---|
| Q8_0 | 8.00 | 1.6 GB | — | 1.50 GB | 8-bit quantization, near-lossless |
Which GPUs Can Run Bielik 1.5B V3.0 Instruct GGUF?
Q8_0 · 1.6 GBBielik 1.5B V3.0 Instruct GGUF (Q8_0) requires 1.6 GB of VRAM to load the model weights. For comfortable inference with headroom for KV cache and system overhead, 3+ GB is recommended. 35 GPUs can run it, including NVIDIA GeForce RTX 5090, NVIDIA GeForce RTX 3090 Ti.
Runs great
— Plenty of headroomWhich Devices Can Run Bielik 1.5B V3.0 Instruct GGUF?
Q8_0 · 1.6 GB33 devices with unified memory can run Bielik 1.5B V3.0 Instruct GGUF, including NVIDIA DGX H100, NVIDIA DGX A100 640GB.
Runs great
— Plenty of headroomRelated Models
Frequently Asked Questions
- How much VRAM does Bielik 1.5B V3.0 Instruct GGUF need?
Bielik 1.5B V3.0 Instruct GGUF requires 1.6 GB of VRAM at Q8_0.
VRAM = Weights + KV Cache + Overhead
Weights = 1.5B × 8 bits ÷ 8 = 1.5 GB
KV Cache + Overhead ≈ 0.1 GB (at 2K context + ~0.3 GB framework)
VRAM usage by quantization
Q8_01.6 GB- Can I run Bielik 1.5B V3.0 Instruct GGUF on a Mac?
Bielik 1.5B V3.0 Instruct GGUF requires at least 1.6 GB at Q8_0, which exceeds the unified memory of most consumer Macs. You would need a Mac Studio or Mac Pro with a high-memory configuration.
- Can I run Bielik 1.5B V3.0 Instruct GGUF locally?
Yes — Bielik 1.5B V3.0 Instruct GGUF can run locally on consumer hardware. At Q8_0 quantization it needs 1.6 GB of VRAM. Popular tools include Ollama, LM Studio, and llama.cpp.
- How fast is Bielik 1.5B V3.0 Instruct GGUF?
At Q8_0, Bielik 1.5B V3.0 Instruct GGUF can reach ~1767 tok/s on AMD Instinct MI300X. On NVIDIA GeForce RTX 4090: ~397 tok/s. Speed depends mainly on GPU memory bandwidth. Real-world results typically within ±20%.
tok/s = (bandwidth GB/s ÷ model GB) × efficiency
Example: AMD Instinct MI300X → 5300 ÷ 1.6 × 0.55 = ~1767 tok/s
Estimated speed at Q8_0 (1.6 GB)
~1767 tok/s~397 tok/s~1321 tok/s~1092 tok/sReal-world results typically within ±20%. Speed depends on batch size, quantization kernel, and software stack.
- What's the download size of Bielik 1.5B V3.0 Instruct GGUF?
At Q8_0, the download is about 1.50 GB.
- Which GPUs can run Bielik 1.5B V3.0 Instruct GGUF?
35 consumer GPUs can run Bielik 1.5B V3.0 Instruct GGUF at Q8_0 (1.6 GB). Top options include AMD Radeon RX 6700 XT, AMD Radeon RX 6800, AMD Radeon RX 6800 XT. 35 GPUs have plenty of headroom for comfortable inference.
- Which devices can run Bielik 1.5B V3.0 Instruct GGUF?
33 devices with unified memory can run Bielik 1.5B V3.0 Instruct GGUF at Q8_0 (1.6 GB), including Mac Mini M4 (16 GB), Mac Mini M4 (32 GB), Mac Mini M4 Pro (24 GB), Mac Mini M4 Pro (48 GB). Apple Silicon Macs use unified memory shared between CPU and GPU, making them well-suited for local LLM inference.