NVIDIA·Qwen3ForCausalLM

Nemotron Orchestrator 8B — Hardware Requirements & GPU Compatibility

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13.0K downloads 561 likes41K context
Based on Qwen3 8B

Specifications

Publisher
NVIDIA
Parameters
8B
Architecture
Qwen3ForCausalLM
Context Length
40,960 tokens
Vocabulary Size
151,936
Release Date
2025-12-02

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How Much VRAM Does Nemotron Orchestrator 8B Need?

Select a quantization to see compatible GPUs below.

QuantizationBitsVRAM
Q2_K3.404 GB
Q3_K_S3.504.1 GB
Q3_K_M3.904.5 GB
Q4_K_M4.805.4 GB
Q5_K_M5.706.3 GB
Q6_K6.607.2 GB
Q8_08.008.6 GB

Which GPUs Can Run Nemotron Orchestrator 8B?

Q4_K_M · 5.4 GB

Nemotron Orchestrator 8B (Q4_K_M) requires 5.4 GB of VRAM to load the model weights. For comfortable inference with headroom for KV cache and system overhead, 8+ GB is recommended. Using the full 41K context window can add up to 5.7 GB, bringing total usage to 11.1 GB. 35 GPUs can run it, including NVIDIA GeForce RTX 5090, NVIDIA GeForce RTX 3090 Ti, NVIDIA GeForce RTX 3070 Ti.

Which Devices Can Run Nemotron Orchestrator 8B?

Q4_K_M · 5.4 GB

33 devices with unified memory can run Nemotron Orchestrator 8B, including NVIDIA DGX H100, NVIDIA DGX A100 640GB, MacBook Air 13" M3 (8 GB).

Related Models

Frequently Asked Questions

How much VRAM does Nemotron Orchestrator 8B need?

Nemotron Orchestrator 8B requires 5.4 GB of VRAM at Q4_K_M, or 8.6 GB at Q8_0. Full 41K context adds up to 5.7 GB (11.1 GB total).

VRAM = Weights + KV Cache + Overhead

Weights = 8B × 4.8 bits ÷ 8 = 4.8 GB

KV Cache + Overhead 0.6 GB (at 2K context + ~0.3 GB framework)

KV Cache + Overhead 6.3 GB (at full 41K context)

VRAM usage by quantization

5.4 GB
11.1 GB

Learn more about VRAM estimation →

What's the best quantization for Nemotron Orchestrator 8B?

For Nemotron Orchestrator 8B, Q4_K_M (5.4 GB) offers the best balance of quality and VRAM usage. Q5_K_S (6.1 GB) provides better quality if you have the VRAM. The smallest option is Q2_K at 4 GB.

VRAM requirement by quantization

Q2_K
4.0 GB
Q3_K_L
4.7 GB
Q4_K_S
5.1 GB
Q4_K_M
5.4 GB
Q5_K_S
6.1 GB
Q8_0
8.6 GB

★ Recommended — best balance of quality and VRAM usage.

Learn more about quantization →

Can I run Nemotron Orchestrator 8B on a Mac?

Nemotron Orchestrator 8B requires at least 4 GB at Q2_K, 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 Nemotron Orchestrator 8B locally?

Yes — Nemotron Orchestrator 8B can run locally on consumer hardware. At Q4_K_M quantization it needs 5.4 GB of VRAM. Popular tools include Ollama, LM Studio, and llama.cpp.

How fast is Nemotron Orchestrator 8B?

At Q4_K_M, Nemotron Orchestrator 8B can reach ~540 tok/s on AMD Instinct MI300X. On NVIDIA GeForce RTX 4090: ~121 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 MI300X5300 ÷ 5.4 × 0.55 = ~540 tok/s

Estimated speed at Q4_K_M (5.4 GB)

~540 tok/s
~121 tok/s
~404 tok/s
~334 tok/s

Real-world results typically within ±20%. Speed depends on batch size, quantization kernel, and software stack.

Learn more about tok/s estimation →

What's the download size of Nemotron Orchestrator 8B?

At Q4_K_M, the download is about 4.80 GB. The full-precision Q8_0 version is 8.00 GB. The smallest option (Q2_K) is 3.40 GB.

Which GPUs can run Nemotron Orchestrator 8B?

35 consumer GPUs can run Nemotron Orchestrator 8B at Q4_K_M (5.4 GB). Top options include AMD Radeon RX 6700 XT, AMD Radeon RX 6800, AMD Radeon RX 6800 XT, AMD Radeon RX 7600. 28 GPUs have plenty of headroom for comfortable inference.

Which devices can run Nemotron Orchestrator 8B?

33 devices with unified memory can run Nemotron Orchestrator 8B at Q4_K_M (5.4 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.