Bloom 560M — Hardware Requirements & GPU Compatibility
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Bloom 560M is a 559M-parameter open language model from BigScience. At Q4_K_M it needs about 0.37 GB of VRAM — see which GPUs and Macs can run it below.
497.7K downloads
374 likesSpecifications
- Publisher
- BigScience
- Parameters
- 559M
- Architecture
- BloomForCausalLM
- Vocabulary Size
- 250,880
- Release Date
- 2023-09-26
- License
- bigscience-bloom-rail-1.0
Get Started
HuggingFace
How Much VRAM Does Bloom 560M Need?
Select a quantization to see compatible GPUs below.
| Quantization | Bits | VRAM | + Context | File Size | Quality |
|---|---|---|---|---|---|
| Q2_K | 3.40 | 0.3 GB | — | 0.24 GB | 2-bit quantization with K-quant improvements |
| Q3_K_S | 3.50 | 0.3 GB | — | 0.24 GB | 3-bit small quantization |
| Q3_K_M | 3.90 | 0.3 GB | — | 0.27 GB | 3-bit medium quantization |
| Q4_K_M | 4.80 | 0.4 GB | — | 0.34 GB | 4-bit medium quantization — most popular sweet spot |
| Q5_K_M | 5.70 | 0.4 GB | — | 0.40 GB | 5-bit medium quantization — good quality/size tradeoff |
| Q6_K | 6.60 | 0.5 GB | — | 0.46 GB | 6-bit quantization, very good quality |
| Q8_0 | 8.00 | 0.6 GB | — | 0.56 GB | 8-bit quantization, near-lossless |
Which GPUs Can Run Bloom 560M?
Q4_K_M · 0.4 GBBloom 560M (Q4_K_M) requires 0.4 GB of VRAM to load the model weights. For comfortable inference with headroom for KV cache and system overhead, 1+ 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 Bloom 560M?
Q4_K_M · 0.4 GB33 devices with unified memory can run Bloom 560M, including NVIDIA DGX H100, NVIDIA DGX A100 640GB.
Runs great
— Plenty of headroomRelated Models
Derivatives (2)
Frequently Asked Questions
- How much VRAM does Bloom 560M need?
Bloom 560M requires 0.4 GB of VRAM at Q4_K_M, or 0.6 GB at Q8_0.
VRAM = Weights + KV Cache + Overhead
Weights = 559M × 4.8 bits ÷ 8 = 0.3 GB
KV Cache + Overhead ≈ 0.1 GB (at 2K context + ~0.3 GB framework)
VRAM usage by quantization
Q4_K_M0.4 GB- What's the best quantization for Bloom 560M?
For Bloom 560M, Q4_K_M (0.4 GB) offers the best balance of quality and VRAM usage. Q5_K_S (0.4 GB) provides better quality if you have the VRAM. The smallest option is Q2_K at 0.3 GB.
VRAM requirement by quantization
Q2_K0.3 GBQ3_K_L0.3 GBQ4_K_S0.3 GBQ4_K_M ★0.4 GBQ5_K_M0.4 GBQ8_00.6 GB★ Recommended — best balance of quality and VRAM usage.
- Can I run Bloom 560M on a Mac?
Bloom 560M requires at least 0.3 GB at Q2_K, 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 Bloom 560M locally?
Yes — Bloom 560M can run locally on consumer hardware. At Q4_K_M quantization it needs 0.4 GB of VRAM. Popular tools include Ollama, LM Studio, and llama.cpp.
- How fast is Bloom 560M?
At Q4_K_M, Bloom 560M can reach ~7878 tok/s on AMD Instinct MI300X. On NVIDIA GeForce RTX 4090: ~1771 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 ÷ 0.4 × 0.55 = ~7878 tok/s
Estimated speed at Q4_K_M (0.4 GB)
~7878 tok/s~1771 tok/s~5889 tok/s~4871 tok/sReal-world results typically within ±20%. Speed depends on batch size, quantization kernel, and software stack.
- What's the download size of Bloom 560M?
At Q4_K_M, the download is about 0.34 GB. The full-precision Q8_0 version is 0.56 GB. The smallest option (Q2_K) is 0.24 GB.
- Which GPUs can run Bloom 560M?
35 consumer GPUs can run Bloom 560M at Q4_K_M (0.4 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 Bloom 560M?
33 devices with unified memory can run Bloom 560M at Q4_K_M (0.4 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.