Nandi Mini V1.1 600M Intermediate Checkpoint 400GT — Hardware Requirements & GPU Compatibility
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Nandi Mini V1.1 600M Intermediate Checkpoint 400GT is a 649M-parameter open language model from FrontiersMind. It supports a context window of up to 2,048 tokens. At BF16 it needs about 1.78 GB of VRAM — see which GPUs and Macs can run it below.
253 downloads
8 likesSpecifications
- Publisher
- FrontiersMind
- Parameters
- 649M
- Architecture
- NandiForCausalLM
- Context Length
- 2,048 tokens
- Vocabulary Size
- 131,072
- Release Date
- 2026-05-30
- License
- Apache 2.0
Get Started
How Much VRAM Does Nandi Mini V1.1 600M Intermediate Checkpoint 400GT Need?
Select a quantization to see compatible GPUs below.
| Quantization | Bits | VRAM | + Context | File Size | Quality |
|---|---|---|---|---|---|
| BF16 | 16.00 | 1.8 GB | — | 1.30 GB | Brain floating point 16 — preferred for training |
Which GPUs Can Run Nandi Mini V1.1 600M Intermediate Checkpoint 400GT?
BF16 · 1.8 GBNandi Mini V1.1 600M Intermediate Checkpoint 400GT (BF16) requires 1.8 GB of VRAM to load the model weights. For comfortable inference with headroom for KV cache and system overhead, 3+ 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 Nandi Mini V1.1 600M Intermediate Checkpoint 400GT?
BF16 · 1.8 GB33 devices with unified memory can run Nandi Mini V1.1 600M Intermediate Checkpoint 400GT, including NVIDIA DGX H100, NVIDIA DGX A100 640GB.
Runs great
— Plenty of headroomRelated Models
Frequently Asked Questions
- How much VRAM does Nandi Mini V1.1 600M Intermediate Checkpoint 400GT need?
Nandi Mini V1.1 600M Intermediate Checkpoint 400GT requires 1.8 GB of VRAM at BF16.
VRAM = Weights + KV Cache + Overhead
Weights = 649M × 16 bits ÷ 8 = 1.3 GB
KV Cache + Overhead ≈ 0.5 GB (at 2K context + ~0.3 GB framework)
VRAM usage by quantization
BF161.8 GB- Can I run Nandi Mini V1.1 600M Intermediate Checkpoint 400GT on a Mac?
Nandi Mini V1.1 600M Intermediate Checkpoint 400GT requires at least 1.8 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 Nandi Mini V1.1 600M Intermediate Checkpoint 400GT locally?
Yes — Nandi Mini V1.1 600M Intermediate Checkpoint 400GT can run locally on consumer hardware. At BF16 quantization it needs 1.8 GB of VRAM. Popular tools include Ollama, LM Studio, and llama.cpp.
- How fast is Nandi Mini V1.1 600M Intermediate Checkpoint 400GT?
At BF16, Nandi Mini V1.1 600M Intermediate Checkpoint 400GT can reach ~1638 tok/s on AMD Instinct MI300X. On NVIDIA GeForce RTX 4090: ~368 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 ÷ 1.8 × 0.55 = ~1638 tok/s
Estimated speed at BF16 (1.8 GB)
~1638 tok/s~368 tok/s~1224 tok/s~1013 tok/sReal-world results typically within ±20%. Speed depends on batch size, quantization kernel, and software stack.
- What's the download size of Nandi Mini V1.1 600M Intermediate Checkpoint 400GT?
At BF16, the download is about 1.30 GB.
- Which GPUs can run Nandi Mini V1.1 600M Intermediate Checkpoint 400GT?
35 consumer GPUs can run Nandi Mini V1.1 600M Intermediate Checkpoint 400GT at BF16 (1.8 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 Nandi Mini V1.1 600M Intermediate Checkpoint 400GT?
33 devices with unified memory can run Nandi Mini V1.1 600M Intermediate Checkpoint 400GT at BF16 (1.8 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.