Bielik 11B V2.0 Instruct — Hardware Requirements & GPU Compatibility
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13 downloads
5 likesSpecifications
- Publisher
- speakleash
- Parameters
- 11.2B
- Architecture
- MistralForCausalLM
- Context Length
- 32,768 tokens
- Vocabulary Size
- 32,128
- Release Date
- 2025-06-06
- License
- Apache 2.0
Get Started
HuggingFace
How Much VRAM Does Bielik 11B V2.0 Instruct Need?
Select a quantization to see compatible GPUs below.
| Quantization | Bits | VRAM | + Context | File Size | Quality |
|---|---|---|---|---|---|
| BF16 | 16.00 | 23.1 GB | 29.4 GB | 22.34 GB | Brain floating point 16 — preferred for training |
Which GPUs Can Run Bielik 11B V2.0 Instruct?
BF16 · 23.1 GBBielik 11B V2.0 Instruct (BF16) requires 23.1 GB of VRAM to load the model weights. For comfortable inference with headroom for KV cache and system overhead, 30+ GB is recommended. Using the full 33K context window can add up to 6.3 GB, bringing total usage to 29.4 GB. 5 GPUs can run it, including NVIDIA GeForce RTX 5090.
All compatible consumer-level GPUs are running near their VRAM limit. You may also want to consider professional GPUs (e.g., NVIDIA A100, H100) which offer significantly more VRAM. For more headroom and better throughput, consider a multi-GPU configuration with tensor parallelism (supported by tools like vLLM, llama.cpp, or text-generation-inference).
Which Devices Can Run Bielik 11B V2.0 Instruct?
BF16 · 23.1 GB21 devices with unified memory can run Bielik 11B V2.0 Instruct, including NVIDIA DGX H100, NVIDIA DGX A100 640GB, Mac Mini M4 Pro (24 GB).
Runs great
— Plenty of headroomDecent
— Enough memory, may be tightRelated Models
Frequently Asked Questions
- How much VRAM does Bielik 11B V2.0 Instruct need?
Bielik 11B V2.0 Instruct requires 23.1 GB of VRAM at BF16. Full 33K context adds up to 6.3 GB (29.4 GB total).
VRAM = Weights + KV Cache + Overhead
Weights = 11.2B × 16 bits ÷ 8 = 22.3 GB
KV Cache + Overhead ≈ 0.8 GB (at 2K context + ~0.3 GB framework)
KV Cache + Overhead ≈ 7.1 GB (at full 33K context)
VRAM usage by quantization
BF1623.1 GBBF16 + full context29.4 GB- Can I run Bielik 11B V2.0 Instruct on a Mac?
Bielik 11B V2.0 Instruct requires at least 23.1 GB at BF16, 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 11B V2.0 Instruct locally?
Yes — Bielik 11B V2.0 Instruct can run locally on consumer hardware. At BF16 quantization it needs 23.1 GB of VRAM. Popular tools include Ollama, LM Studio, and llama.cpp.
- How fast is Bielik 11B V2.0 Instruct?
At BF16, Bielik 11B V2.0 Instruct can reach ~126 tok/s on AMD Instinct MI300X. On NVIDIA GeForce RTX 4090: ~28 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 ÷ 23.1 × 0.55 = ~126 tok/s
Estimated speed at BF16 (23.1 GB)
AMD Instinct MI300X~126 tok/sNVIDIA GeForce RTX 4090~28 tok/sNVIDIA H100 SXM~95 tok/sAMD Instinct MI250X~78 tok/sReal-world results typically within ±20%. Speed depends on batch size, quantization kernel, and software stack.
- What's the download size of Bielik 11B V2.0 Instruct?
At BF16, the download is about 22.34 GB.
- Which GPUs can run Bielik 11B V2.0 Instruct?
5 consumer GPUs can run Bielik 11B V2.0 Instruct at BF16 (23.1 GB). Top options include AMD Radeon RX 7900 XTX, NVIDIA GeForce RTX 3090.
- Which devices can run Bielik 11B V2.0 Instruct?
21 devices with unified memory can run Bielik 11B V2.0 Instruct at BF16 (23.1 GB), including Mac Mini M4 (32 GB), Mac Mini M4 Pro (24 GB), Mac Mini M4 Pro (48 GB), Mac Pro M2 Ultra (192 GB). Apple Silicon Macs use unified memory shared between CPU and GPU, making them well-suited for local LLM inference.