Btlm 3B 8k Base — Hardware Requirements & GPU Compatibility
Chat
Btlm 3B 8k Base is a 3B-parameter open language model from Cerebras. It supports a context window of up to 8,192 tokens. At BF16 it needs about 6.60 GB of VRAM — see which GPUs and Macs can run it below.
1.3K downloads
269 likesSpecifications
- Publisher
- Cerebras
- Parameters
- 3B
- Architecture
- BTLMLMHeadModel
- Context Length
- 8,192 tokens
- Vocabulary Size
- 50,257
- Release Date
- 2023-10-23
- License
- Apache 2.0
Get Started
HuggingFace
How Much VRAM Does Btlm 3B 8k Base Need?
Select a quantization to see compatible GPUs below.
| Quantization | Bits | VRAM | + Context | File Size | Quality |
|---|---|---|---|---|---|
| BF16 | 16.00 | 6.6 GB | — | 6.00 GB | Brain floating point 16 — preferred for training |
Which GPUs Can Run Btlm 3B 8k Base?
BF16 · 6.6 GBBtlm 3B 8k Base (BF16) requires 6.6 GB of VRAM to load the model weights. For comfortable inference with headroom for KV cache and system overhead, 9+ GB is recommended. 35 GPUs can run it, including NVIDIA GeForce RTX 5090, NVIDIA GeForce RTX 3090 Ti, NVIDIA GeForce RTX 3070 Ti.
Runs great
— Plenty of headroom
Which Devices Can Run Btlm 3B 8k Base?
BF16 · 6.6 GB33 devices with unified memory can run Btlm 3B 8k Base, including NVIDIA DGX H100, NVIDIA DGX A100 640GB, MacBook Air 13" M3 (8 GB).
Runs great
— Plenty of headroomDecent
— Enough memory, may be tightRelated Models
Frequently Asked Questions
- How much VRAM does Btlm 3B 8k Base need?
Btlm 3B 8k Base requires 6.6 GB of VRAM at BF16.
VRAM = Weights + KV Cache + Overhead
Weights = 3B × 16 bits ÷ 8 = 6 GB
KV Cache + Overhead ≈ 0.6 GB (at 2K context + ~0.3 GB framework)
VRAM usage by quantization
BF166.6 GB- Can I run Btlm 3B 8k Base on a Mac?
Btlm 3B 8k Base requires at least 6.6 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 Btlm 3B 8k Base locally?
Yes — Btlm 3B 8k Base can run locally on consumer hardware. At BF16 quantization it needs 6.6 GB of VRAM. Popular tools include Ollama, LM Studio, and llama.cpp.
- How fast is Btlm 3B 8k Base?
At BF16, Btlm 3B 8k Base can reach ~442 tok/s on AMD Instinct MI300X. On NVIDIA GeForce RTX 4090: ~99 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 ÷ 6.6 × 0.55 = ~442 tok/s
Estimated speed at BF16 (6.6 GB)
~442 tok/s~99 tok/s~330 tok/s~273 tok/sReal-world results typically within ±20%. Speed depends on batch size, quantization kernel, and software stack.
- What's the download size of Btlm 3B 8k Base?
At BF16, the download is about 6.00 GB.
- Which GPUs can run Btlm 3B 8k Base?
35 consumer GPUs can run Btlm 3B 8k Base at BF16 (6.6 GB). Top options include AMD Radeon RX 6700 XT, AMD Radeon RX 6800, AMD Radeon RX 6800 XT, AMD Radeon RX 7600. 28 GPUs have plenty of headroom for comfortable inference.
- Which devices can run Btlm 3B 8k Base?
33 devices with unified memory can run Btlm 3B 8k Base at BF16 (6.6 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.