Cerebras GPT 13B — Hardware Requirements & GPU Compatibility
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Cerebras GPT 13B is a 13B-parameter open language model from Cerebras. It supports a context window of up to 2,048 tokens. At BF16 it needs about 28.60 GB of VRAM — see which GPUs and Macs can run it below.
1.6K downloads
651 likesSpecifications
- Publisher
- Cerebras
- Parameters
- 13B
- Architecture
- GPT2Model
- Context Length
- 2,048 tokens
- Vocabulary Size
- 50,257
- Release Date
- 2023-11-22
- License
- Apache 2.0
Get Started
HuggingFace
How Much VRAM Does Cerebras GPT 13B Need?
Select a quantization to see compatible GPUs below.
| Quantization | Bits | VRAM | + Context | File Size | Quality |
|---|---|---|---|---|---|
| BF16 | 16.00 | 28.6 GB | — | 26.00 GB | Brain floating point 16 — preferred for training |
Which GPUs Can Run Cerebras GPT 13B?
BF16 · 28.6 GBCerebras GPT 13B (BF16) requires 28.6 GB of VRAM to load the model weights. For comfortable inference with headroom for KV cache and system overhead, 38+ GB is recommended. 1 GPU 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).
Decent
— Enough VRAM, may be tightWhich Devices Can Run Cerebras GPT 13B?
BF16 · 28.6 GB15 devices with unified memory can run Cerebras GPT 13B, including NVIDIA DGX H100, NVIDIA DGX A100 640GB, Mac Studio M4 Max (36 GB).
Runs great
— Plenty of headroomDecent
— Enough memory, may be tightBenchmarks
View all 2 →Related Models
Frequently Asked Questions
- How much VRAM does Cerebras GPT 13B need?
Cerebras GPT 13B requires 28.6 GB of VRAM at BF16.
VRAM = Weights + KV Cache + Overhead
Weights = 13B × 16 bits ÷ 8 = 26 GB
KV Cache + Overhead ≈ 2.6 GB (at 2K context + ~0.3 GB framework)
VRAM usage by quantization
BF1628.6 GB- Can I run Cerebras GPT 13B on a Mac?
Cerebras GPT 13B requires at least 28.6 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 Cerebras GPT 13B locally?
Yes — Cerebras GPT 13B can run locally on consumer hardware. At BF16 quantization it needs 28.6 GB of VRAM. Popular tools include Ollama, LM Studio, and llama.cpp.
- How fast is Cerebras GPT 13B?
At BF16, Cerebras GPT 13B can reach ~102 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 ÷ 28.6 × 0.55 = ~102 tok/s
Estimated speed at BF16 (28.6 GB)
~102 tok/s~76 tok/s~63 tok/sReal-world results typically within ±20%. Speed depends on batch size, quantization kernel, and software stack.
- What's the download size of Cerebras GPT 13B?
At BF16, the download is about 26.00 GB.
- Which GPUs can run Cerebras GPT 13B?
1 consumer GPU can run Cerebras GPT 13B at BF16 (28.6 GB). Top options include NVIDIA GeForce RTX 5090.
- Which devices can run Cerebras GPT 13B?
15 devices with unified memory can run Cerebras GPT 13B at BF16 (28.6 GB), including Mac Mini M4 (32 GB), Mac Mini M4 Pro (48 GB), Mac Pro M2 Ultra (192 GB), Mac Studio M2 Ultra (192 GB). Apple Silicon Macs use unified memory shared between CPU and GPU, making them well-suited for local LLM inference.