Bloom 1b1 — Hardware Requirements & GPU Compatibility
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Bloom 1b1 is a 1.1B-parameter open language model from BigScience. At Q4_K_M it needs about 0.70 GB of VRAM — see which GPUs and Macs can run it below.
Runs great on a 24 GB GPU
Runs from 8 GB (Q4_K_M · 32K)Best on 24 GB (Q4_K_M · ~936 tok/s · 32K)Macs from 8 GB (Q4_K_M · ~102 tok/s)
bigscience-bloom-rail-1.0
Reference GPU · RTX 4090 24 GB
Estimates, ±20% · how we estimate
Run Bloom 1b1
One recommended way. Every other method, OS and quant is in the step-by-step guide.Each way opens a step-by-step guide for your OS and quant.
Recommended
vllm serve bigscience/bloom-1b1 --max-model-len 16384vLLM repo with its own quantisation
Download: Weights on Hugging Face
Ways to runOther ways
each opens step-by-stepRun in cloud
Runs on RTX 3060 12GB (9 GB headroom) · Q4_K_M
- Generation speed
- ~334 tok/s
- generation speed
- Cost per 1M output tokens
- $0.051
- per 1M output tokens
How Much VRAM Does Bloom 1b1 Need?
Select a quantization level; the listed hardware adheres to it.
| Quantization | VRAM | +32K | On RTX 4090 (reference) | |
|---|---|---|---|---|
| 0.5 GB | 3.6 GB | 2-bit · K-quant — 2-bit quantization with K-quant improvements | Fits: 32K context · ~1310 tok/s | |
| 0.6 GB | 3.7 GB | 3-bit medium — 3-bit medium quantization | Fits: 32K context · ~1150 tok/s | |
| 0.7 GB | 3.8 GB | 4-bit medium — 4-bit medium quantization — most popular sweet spot | Fits: 32K context · ~936 tok/s | |
| 0.8 GB | 4 GB | 5-bit medium — 5-bit medium quantization — good quality/size tradeoff | Fits: 32K context · ~789 tok/s | |
| 1.0 GB | 4.1 GB | 6-bit, very good — 6-bit quantization, very good quality | Fits: 32K context · ~676 tok/s | |
| 1.2 GB | 4.3 GB | 8-bit, near-lossless — 8-bit quantization, near-lossless | Fits: 32K context · ~560 tok/s | |
| 2.3 GB | 5.5 GB | 16-bit · bfloat — Brain floating point 16 — preferred for training | Fits: 32K context · ~280 tok/s |
Selected Q4_K_M
4-bit medium quantization2.2GBat 16K context
- Weights
- 0.2 GB
- KV cache
- 1.7 GB
- Overhead
- 0.3 GB
Fits RTX 4090 (reference) · 21.8 GB free · ~936 tok/s
≥50 tok/s needs ≥54 GB/s · RTX 5090 ~1664, RTX 3090 Ti ~936
Which Hardware Can Run Bloom 1b1?
Q4_K_M · 0.7 GBBloom 1b1 (Q4_K_M) requires 0.7 GB of VRAM to load the model weights. For comfortable inference with headroom for KV cache and system overhead, 1+ GB is recommended. 52 GPUs can run it, including NVIDIA GeForce RTX 5090, NVIDIA GeForce RTX 3090 Ti. 163 devices with unified memory can run Bloom 1b1, including Mac Studio (M3 Ultra, 256GB), Mac Studio (M3 Ultra, 512GB).
≤ 11 GB
≤ 11 GB tier →fits · 5.8 GB free · up to 32K ctx
16 GPUs · 1 Mac class · 2 device families
RTX 3080~706Simulate output on RTX 3080RTX 2080 Ti~572Simulate output on RTX 2080 TiRTX 3070 Ti~565Simulate output on RTX 3070 TiM3*8 GB~102Simulate output on iMac 24" M3 (8 GB)Orin Nano~95Simulate output on NVIDIA Jetson Orin Nano 8GB (Super)iPhone~68Simulate output on iPhone 1720 GB
fits · 17.8 GB free · up to 32K ctx
1 GPU
RX 7900 XT~686Simulate output on RX 7900 XT32–40 GB
fits · 29.8 GB free · up to 32K ctx
1 GPU · 3 Mac classes · 4 device families
RTX 5090~1664Simulate output on RTX 5090M5 Max36 GB~460Simulate output on Mac Studio M5 Max (36 GB)M532 GB~154Simulate output on MacBook Air 13" M5 (32 GB)Orin~190Simulate output on NVIDIA Jetson AGX Orin 32GBSnapdragon X Elite (X1E-80-100)~125Simulate output on Snapdragon X Elite Copilot+ PC
By VRAM tier · typical GPUs and Macs at Q4_K_M
Similar models
6| Model | Score | VRAM | tok/s | Why it is similar |
|---|---|---|---|---|
| MiniCPM5 1BOpenBMB | — | 1.3 GB | ~662 | same size |
| Gemma 3 1B ITGoogle | — | 2.1 GB | ~993 | same size |
| TinyLlama 1.1B Chat v1.0TinyLlama | — | 1 GB | ~649 | same size |
| LLaMA3.1 8B Instruct DFlash UltraChatz-lab | — | 2.7 GB | ~269 | same size |
| Vaultgemma 1BGoogle | — | 3.7 GB | ~286 | same size |
| TinyDolphin 2.8 1.1BQuixiAI | — | 1.1 GB | ~649 | same size |
Specifications
- Publisher
- BigScience
- Parameters
- 1.1B
- Architecture
- BloomForCausalLM
- Vocabulary Size
- 250,880
- Release Date
- 2022-05-19
- License
- bigscience-bloom-rail-1.0
Frequently Asked Questions
How much VRAM does Bloom 1b1 need?
Bloom 1b1 requires 0.7 GB of VRAM at Q4_K_M, or 2.3 GB at BF16.
VRAM = Weights + KV Cache + Overhead
Weights = 1.1B × 4.8 bits ÷ 8 = 0.6 GB
KV Cache + Overhead ≈ 0.1 GB (at 2K context + ~0.3 GB framework)
Fit ratings and hardware model lists check this model with room for a 16K-token context, which needs a little more memory.
VRAM usage by quantization
What's the best quantization for Bloom 1b1?
For Bloom 1b1, Q4_K_M (0.7 GB) offers the best balance of quality and VRAM usage. Q5_K_M (0.8 GB) provides better quality if you have the VRAM. The smallest option is Q2_K at 0.5 GB.
VRAM requirement by quantization
★ Recommended — best balance of quality and VRAM usage.
Can I run Bloom 1b1 on a Mac?
Yes — MacBook Air 13" M3 (8 GB) and 145 other Macs can run Bloom 1b1. Apple Silicon uses unified memory, so the model shares RAM with the system. At Q4_K_M you need at least 0.7 GB of usable unified memory (RAM minus macOS overhead).
Can I run Bloom 1b1 locally?
Yes — Bloom 1b1 can run locally on consumer hardware. Popular tools include Ollama, LM Studio, and llama.cpp.
How fast is Bloom 1b1?
At Q4_K_M, Bloom 1b1 can reach ~6857 tok/s on AMD Instinct MI350X. On NVIDIA GeForce RTX 4090: ~936 tok/s. Speed depends mainly on GPU memory bandwidth. Real-world results typically within ±20%.
tok/s = (bandwidth GB/s ÷ model GB) × efficiency
Example: NVIDIA B200 → 8000 ÷ 0.7 × 0.65 = ~7429 tok/s
Estimated speed at Q4_K_M (0.7 GB)
Real-world results typically within ±20%. Speed depends on batch size, quantization kernel, and software stack.
What's the download size of Bloom 1b1?
At Q4_K_M, the download is about 0.64 GB. The full-precision BF16 version is 2.13 GB. The smallest option (Q2_K) is 0.45 GB.
Which GPUs can run Bloom 1b1?
52 consumer GPUs can run Bloom 1b1 at Q4_K_M. Top options include AMD Radeon RX 6700 XT, AMD Radeon RX 6800, AMD Radeon RX 6800 XT. 52 GPUs have plenty of headroom for comfortable inference.
Which devices can run Bloom 1b1?
163 devices with unified memory can run Bloom 1b1 at Q4_K_M (0.7 GB), including AMD Ryzen AI 9 HX 370 (Strix Point) Laptop, ASUS Ascent GX10, Beelink GTR9 Pro (Ryzen AI Max+ 395, 128 GB), Framework Desktop (Ryzen AI Max+ 395, 128 GB). Apple Silicon Macs use unified memory shared between CPU and GPU, making them well-suited for local LLM inference.