Moderato V1 Pro — Hardware Requirements & GPU Compatibility
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Moderato V1 Pro is a 113.3B-parameter open language model from nitrai-research. It supports a context window of up to 262,144 tokens. At BF16 it needs about 227.44 GB of VRAM — see which GPUs and Macs can run it below.
Moderato V1 Pro runs on a 256 GB+ Mac or a datacenter GPU
Best local pick → Mac Studio (M3 Ultra, 256GB) · BF16 · 230.6 GB · ~3 tok/s
Macs from 256 GB (BF16 · ~3 tok/s)
Apache 2.0
Not set up for it?
Reference GPU · RTX 4090 24 GB
Estimates, ±20% · how we estimate
Run Moderato V1 Pro
One recommended way. Every other method, OS and quant is in the step-by-step guide.
Recommended
vllm serve nitrai-research/Moderato-V1-Pro --max-model-len 16384 --tensor-parallel-size 8vLLM repo with its own quantisation
Download: Weights on Hugging Face
Other ways
each opens step-by-stepRun in cloud
Fits on B300 (288 GB) (57 GB headroom) · BF16
- Generation speed
- ~23 tok/s
- generation speed
- Cost per 1M output tokens
- $84.18
- per 1M output tokens
How Much VRAM Does Moderato V1 Pro Need?
Select a quantization level; the listed hardware adheres to it.
| Quantization | VRAM | +32K | Runs on | |
|---|---|---|---|---|
| 227.4 GB | 234.2 GB | 16-bit · bfloat — Brain floating point 16 — preferred for training | Runs on Instinct MI325X 256 GB |
Selected BF16
Brain floating point 16230.6GBat 16K context
- Weights
- 226.7 GB
- KV cache
- 3.6 GB
- Overhead
- 0.3 GB
Server-class: ~230.6 GB at 16K context · one Instinct MI325X 256 GB
Which Hardware Can Run Moderato V1 Pro?
BF16 · 227.4 GBModerato V1 Pro (BF16) requires 227.4 GB of VRAM to load the model weights. For comfortable inference with headroom for KV cache and system overhead, 296+ GB is recommended. Using the full 262K context window can add up to 56.8 GB, bringing total usage to 284.3 GB. No consumer GPU has enough memory. 2 devices with unified memory can run Moderato V1 Pro, including Mac Studio (M3 Ultra, 512GB), Mac Studio (M3 Ultra, 256GB).
Needs server-class hardware
Moderato V1 Pro runs on a 256 GB+ Mac or a datacenter GPU · BF16 needs ~230.6 GB
| Hardware | Quant | Memory | Speed | Context | Hardware page | |
|---|---|---|---|---|---|---|
| Mac 256 GB · Mac Studio (M3 Ultra, 256GB) | BF16 | 230.6 GB | ~3 tok/s | 64K ctx | Mac Studio → | BF16 · 230.6 GB · ~3 tok/s · 64K ctx |
| Instinct MI325X 256 GB · one GPU | BF16 | 230.6 GB | ~16 tok/s | 128K ctx | Instinct MI325X → | BF16 · 230.6 GB · ~16 tok/s · 128K ctx |
| 4× H100 SXM 80 GB · 320 GB | BF16 | 230.6 GB | — | 256K ctx | H100 SXM → | BF16 · 230.6 GB · 256K ctx |
| 2× H200 SXM 141 GB · 282 GB | BF16 | 230.6 GB | — | 64K ctx | H200 SXM → | BF16 · 230.6 GB · 64K ctx |
| 2× B200 192 GB · 384 GB | BF16 | 230.6 GB | — | 256K ctx | B200 → | BF16 · 230.6 GB · 256K ctx |
Also: Instinct MI325X · Instinct MI350X · Instinct MI355X · B300 · Mac Studio (M3 Ultra, 256GB) · Mac Studio (M3 Ultra, 512GB) · NVIDIA DGX A100 640GB · NVIDIA DGX H100
By VRAM tier · typical GPUs and Macs at BF16
Consumer GPUs (up to 32 GB) and Macs up to 192 GB: too small for this model (needs ≥ 230.6 GB)8 GB tier →12 GB tier →16 GB tier →24 GB tier →Macs →
Similar models
6| Model | Score | VRAM | tok/s | Why it is similar |
|---|---|---|---|---|
| GPT OSS 120BOpenAI | 97.5 | 70.8 GB | —needs > 24 GB | same size |
| Llama 4 Scout 17B 16E InstructMeta | 81.8 | 77 GB | —needs > 24 GB | same size |
| C4ai Command A 03 2025Cohere | 79.8 | 78.7 GB | —needs > 24 GB | same size |
| Leanstral 1.5 119B A6BMistral AI | — | 84 GB | —needs > 24 GB | same size |
| GLM 4.6VZ.ai | — | 66 GB | —needs > 24 GB | same size |
| Qwen1.5 110BAlibaba | — | 72.4 GB | —needs > 24 GB | same size |
Specifications
- Publisher
- nitrai-research
- Parameters
- 113.3B
- Architecture
- ModeratoRRRMoeForCausalLM
- Context Length
- 262,144 tokens
- Vocabulary Size
- 248,320
- Release Date
- 2026-08-25
- License
- Apache 2.0
Frequently Asked Questions
How much VRAM does Moderato V1 Pro need?
Moderato V1 Pro requires 227.4 GB of VRAM at BF16. Full 262K context adds up to 56.8 GB (284.3 GB total).
VRAM = Weights + KV Cache + Overhead
Weights = 113.3B × 16 bits ÷ 8 = 226.7 GB
KV Cache + Overhead ≈ 0.7 GB (at 2K context + ~0.3 GB framework)
Fit ratings and hardware model lists check this model with room for a 16K-token context, which needs a little more memory.
KV Cache + Overhead ≈ 57.6 GB (at full 262K context)
VRAM usage by quantization
Can NVIDIA GeForce RTX 5090 run Moderato V1 Pro?
No — Moderato V1 Pro requires at least 227.4 GB at BF16, which exceeds the NVIDIA GeForce RTX 5090's 32 GB of VRAM.
Can I run Moderato V1 Pro on a Mac?
Yes — Mac Studio (M3 Ultra, 256GB) and 1 other Mac can run Moderato V1 Pro. Apple Silicon uses unified memory, so the model shares RAM with the system. At BF16 you need at least 227.4 GB of usable unified memory (RAM minus macOS overhead).
Can I run Moderato V1 Pro locally?
Yes — Moderato V1 Pro can run locally on consumer hardware. Popular tools include Ollama, LM Studio, and llama.cpp.
How fast is Moderato V1 Pro?
At BF16, Moderato V1 Pro can reach ~21 tok/s on AMD Instinct MI350X. Speed depends mainly on GPU memory bandwidth. Real-world results typically within ±20%.
tok/s = (bandwidth GB/s ÷ model GB) × efficiency
Example: NVIDIA B300 → 8000 ÷ 227.4 × 0.65 = ~23 tok/s
Estimated speed at BF16 (227.4 GB)
Real-world results typically within ±20%. Speed depends on batch size, quantization kernel, and software stack.
What's the download size of Moderato V1 Pro?
At BF16, the download is about 226.70 GB.
Which GPUs can run Moderato V1 Pro?
No single consumer GPU has enough VRAM to run Moderato V1 Pro at BF16 (227.4 GB). Multi-GPU or professional hardware is required.
Which devices can run Moderato V1 Pro?
2 devices with unified memory can run Moderato V1 Pro at BF16 (227.4 GB), including Mac Studio (M3 Ultra, 256GB), Mac Studio (M3 Ultra, 512GB). Apple Silicon Macs use unified memory shared between CPU and GPU, making them well-suited for local LLM inference.