Bloom — Hardware Requirements & GPU Compatibility
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Bloom is a 176.2B-parameter open language model from BigScience. At Q4_K_M it needs about 116.32 GB of VRAM — see which GPUs and Macs can run it below.
6.8K downloads
5.0K likesSpecifications
- Publisher
- BigScience
- Parameters
- 176.2B
- Architecture
- BloomForCausalLM
- Vocabulary Size
- 250,880
- Release Date
- 2023-07-28
- License
- bigscience-bloom-rail-1.0
Get Started
HuggingFace
How Much VRAM Does Bloom Need?
Select a quantization to see compatible GPUs below.
| Quantization | Bits | VRAM | + Context | File Size | Quality |
|---|---|---|---|---|---|
| Q2_K | 3.40 | 82.4 GB | — | 74.91 GB | 2-bit quantization with K-quant improvements |
| Q3_K_S | 3.50 | 84.8 GB | — | 77.11 GB | 3-bit small quantization |
| Q3_K_M | 3.90 | 94.5 GB | — | 85.92 GB | 3-bit medium quantization |
| Q4_K_M | 4.80 | 116.3 GB | — | 105.75 GB | 4-bit medium quantization — most popular sweet spot |
| Q5_K_M | 5.70 | 138.1 GB | — | 125.58 GB | 5-bit medium quantization — good quality/size tradeoff |
| Q6_K | 6.60 | 159.9 GB | — | 145.40 GB | 6-bit quantization, very good quality |
| Q8_0 | 8.00 | 193.9 GB | — | 176.25 GB | 8-bit quantization, near-lossless |
Which GPUs Can Run Bloom?
Q4_K_M · 116.3 GBBloom (Q4_K_M) requires 116.3 GB of VRAM to load the model weights. For comfortable inference with headroom for KV cache and system overhead, 152+ GB is recommended. No single GPU has enough memory — multi-GPU or cluster setups are needed.
Which Devices Can Run Bloom?
Q4_K_M · 116.3 GB5 devices with unified memory can run Bloom, including NVIDIA DGX H100, NVIDIA DGX A100 640GB, Mac Studio M4 Max (128 GB).
Runs great
— Plenty of headroom
Decent
— Enough memory, may be tightBenchmarks
View all 2 →Related Models
Frequently Asked Questions
- How much VRAM does Bloom need?
Bloom requires 116.3 GB of VRAM at Q4_K_M, or 193.9 GB at Q8_0.
VRAM = Weights + KV Cache + Overhead
Weights = 176.2B × 4.8 bits ÷ 8 = 105.7 GB
KV Cache + Overhead ≈ 10.6 GB (at 2K context + ~0.3 GB framework)
VRAM usage by quantization
Q4_K_M116.3 GB- Can NVIDIA GeForce RTX 5090 run Bloom?
No — Bloom requires at least 82.4 GB at Q2_K, which exceeds the NVIDIA GeForce RTX 5090's 32 GB of VRAM.
- What's the best quantization for Bloom?
For Bloom, Q4_K_M (116.3 GB) offers the best balance of quality and VRAM usage. Q5_K_S (133.3 GB) provides better quality if you have the VRAM. The smallest option is Q2_K at 82.4 GB.
VRAM requirement by quantization
Q2_K82.4 GBQ3_K_L99.4 GBQ4_K_S109.0 GBQ4_K_M ★116.3 GBQ5_K_M138.1 GBQ8_0193.9 GB★ Recommended — best balance of quality and VRAM usage.
- Can I run Bloom on a Mac?
Bloom requires at least 82.4 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 locally?
Yes — Bloom can run locally on consumer hardware. At Q4_K_M quantization it needs 116.3 GB of VRAM. Popular tools include Ollama, LM Studio, and llama.cpp.
- How fast is Bloom?
At Q4_K_M, Bloom can reach ~25 tok/s on AMD Instinct MI300X. 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 ÷ 116.3 × 0.55 = ~25 tok/s
Estimated speed at Q4_K_M (116.3 GB)
~25 tok/s~16 tok/sReal-world results typically within ±20%. Speed depends on batch size, quantization kernel, and software stack.
- What's the download size of Bloom?
At Q4_K_M, the download is about 105.75 GB. The full-precision Q8_0 version is 176.25 GB. The smallest option (Q2_K) is 74.91 GB.
- Which GPUs can run Bloom?
No single consumer GPU has enough VRAM to run Bloom at Q4_K_M (116.3 GB). Multi-GPU or professional hardware is required.
- Which devices can run Bloom?
5 devices with unified memory can run Bloom at Q4_K_M (116.3 GB), including Mac Pro M2 Ultra (192 GB), Mac Studio M2 Ultra (192 GB), Mac Studio M4 Max (128 GB), NVIDIA DGX A100 640GB. Apple Silicon Macs use unified memory shared between CPU and GPU, making them well-suited for local LLM inference.