Supra Mini V5 8M — Hardware Requirements & GPU Compatibility
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Supra Mini V5 8M is a 8M-parameter open language model from SupraLabs. It supports a context window of up to 1,024 tokens. At BF16 it needs about 0.33 GB of VRAM — see which GPUs and Macs can run it below.
460 downloads
6 likesSpecifications
- Publisher
- SupraLabs
- Parameters
- 8M
- Architecture
- LlamaForCausalLM
- Context Length
- 1,024 tokens
- Vocabulary Size
- 16,384
- Release Date
- 2026-05-18
- License
- Apache 2.0
Get Started
HuggingFace
How Much VRAM Does Supra Mini V5 8M Need?
Select a quantization to see compatible GPUs below.
| Quantization | Bits | VRAM | + Context | File Size | Quality |
|---|---|---|---|---|---|
| BF16 | 16.00 | 0.3 GB | — | 0.02 GB | Brain floating point 16 — preferred for training |
Which GPUs Can Run Supra Mini V5 8M?
BF16 · 0.3 GBSupra Mini V5 8M (BF16) requires 0.3 GB of VRAM to load the model weights. For comfortable inference with headroom for KV cache and system overhead, 1+ GB is recommended. 35 GPUs can run it, including NVIDIA GeForce RTX 5090, NVIDIA GeForce RTX 3090 Ti.
Runs great
— Plenty of headroomWhich Devices Can Run Supra Mini V5 8M?
BF16 · 0.3 GB33 devices with unified memory can run Supra Mini V5 8M, including NVIDIA DGX H100, NVIDIA DGX A100 640GB.
Runs great
— Plenty of headroomRelated Models
Frequently Asked Questions
- How much VRAM does Supra Mini V5 8M need?
Supra Mini V5 8M requires 0.3 GB of VRAM at BF16.
VRAM = Weights + KV Cache + Overhead
Weights = 8M × 16 bits ÷ 8 = 0 GB
KV Cache + Overhead ≈ 0.3 GB (at 2K context + ~0.3 GB framework)
VRAM usage by quantization
BF160.3 GB- Can I run Supra Mini V5 8M on a Mac?
Supra Mini V5 8M requires at least 0.3 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 Supra Mini V5 8M locally?
Yes — Supra Mini V5 8M can run locally on consumer hardware. At BF16 quantization it needs 0.3 GB of VRAM. Popular tools include Ollama, LM Studio, and llama.cpp.
- How fast is Supra Mini V5 8M?
At BF16, Supra Mini V5 8M can reach ~8833 tok/s on AMD Instinct MI300X. On NVIDIA GeForce RTX 4090: ~1986 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 ÷ 0.3 × 0.55 = ~8833 tok/s
Estimated speed at BF16 (0.3 GB)
~8833 tok/s~1986 tok/s~6602 tok/s~5461 tok/sReal-world results typically within ±20%. Speed depends on batch size, quantization kernel, and software stack.
- What's the download size of Supra Mini V5 8M?
At BF16, the download is about 0.02 GB.
- Which GPUs can run Supra Mini V5 8M?
35 consumer GPUs can run Supra Mini V5 8M at BF16 (0.3 GB). Top options include AMD Radeon RX 6700 XT, AMD Radeon RX 6800, AMD Radeon RX 6800 XT. 35 GPUs have plenty of headroom for comfortable inference.
- Which devices can run Supra Mini V5 8M?
33 devices with unified memory can run Supra Mini V5 8M at BF16 (0.3 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.