Mamba2 8B 3t 4k — Hardware Requirements & GPU Compatibility
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Mamba2 8B 3t 4k is a 8B-parameter open language model from NVIDIA. At BF16 it needs about 17.60 GB of VRAM — see which GPUs and Macs can run it below.
23 likesSpecifications
- Publisher
- NVIDIA
- Parameters
- 8B
- Release Date
- 2024-06-13
- License
- Apache 2.0
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HuggingFace
How Much VRAM Does Mamba2 8B 3t 4k Need?
Select a quantization to see compatible GPUs below.
| Quantization | Bits | VRAM | + Context | File Size | Quality |
|---|---|---|---|---|---|
| BF16 | 16.00 | 17.6 GB | — | 16.00 GB | Brain floating point 16 — preferred for training |
Which GPUs Can Run Mamba2 8B 3t 4k?
BF16 · 17.6 GBMamba2 8B 3t 4k (BF16) requires 17.6 GB of VRAM to load the model weights. For comfortable inference with headroom for KV cache and system overhead, 23+ GB is recommended. 6 GPUs can run it, including NVIDIA GeForce RTX 5090, NVIDIA GeForce RTX 3090 Ti.
Runs great
— Plenty of headroom
Which Devices Can Run Mamba2 8B 3t 4k?
BF16 · 17.6 GB21 devices with unified memory can run Mamba2 8B 3t 4k, including NVIDIA DGX H100, NVIDIA DGX A100 640GB, Mac Mini M4 Pro (24 GB).
Runs great
— Plenty of headroomRelated Models
Frequently Asked Questions
- How much VRAM does Mamba2 8B 3t 4k need?
Mamba2 8B 3t 4k requires 17.6 GB of VRAM at BF16.
VRAM = Weights + KV Cache + Overhead
Weights = 8B × 16 bits ÷ 8 = 16 GB
KV Cache + Overhead ≈ 1.6 GB (at 2K context + ~0.3 GB framework)
VRAM usage by quantization
BF1617.6 GB- Can I run Mamba2 8B 3t 4k on a Mac?
Mamba2 8B 3t 4k requires at least 17.6 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 Mamba2 8B 3t 4k locally?
Yes — Mamba2 8B 3t 4k can run locally on consumer hardware. At BF16 quantization it needs 17.6 GB of VRAM. Popular tools include Ollama, LM Studio, and llama.cpp.
- How fast is Mamba2 8B 3t 4k?
At BF16, Mamba2 8B 3t 4k can reach ~166 tok/s on AMD Instinct MI300X. On NVIDIA GeForce RTX 4090: ~37 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 ÷ 17.6 × 0.55 = ~166 tok/s
Estimated speed at BF16 (17.6 GB)
~166 tok/s~37 tok/s~124 tok/s~102 tok/sReal-world results typically within ±20%. Speed depends on batch size, quantization kernel, and software stack.
- What's the download size of Mamba2 8B 3t 4k?
At BF16, the download is about 16.00 GB.
- Which GPUs can run Mamba2 8B 3t 4k?
6 consumer GPUs can run Mamba2 8B 3t 4k at BF16 (17.6 GB). Top options include NVIDIA GeForce RTX 5090, AMD Radeon RX 7900 XT, AMD Radeon RX 7900 XTX. 1 GPU have plenty of headroom for comfortable inference.
- Which devices can run Mamba2 8B 3t 4k?
21 devices with unified memory can run Mamba2 8B 3t 4k at BF16 (17.6 GB), including Mac Mini M4 (32 GB), Mac Mini M4 Pro (24 GB), Mac Mini M4 Pro (48 GB), Mac Pro M2 Ultra (192 GB). Apple Silicon Macs use unified memory shared between CPU and GPU, making them well-suited for local LLM inference.