AceReason Nemotron 14B GGUF — Hardware Requirements & GPU Compatibility
ChatReasoning
477 downloads
9 likesSpecifications
- Publisher
- Unsloth
- Parameters
- 14B
- Architecture
- Qwen2ForCausalLM
- Context Length
- 131,072 tokens
- Vocabulary Size
- 152,064
- Release Date
- 2025-05-23
- License
- Other
Get Started
HuggingFace
How Much VRAM Does AceReason Nemotron 14B GGUF Need?
Select a quantization to see compatible GPUs below.
| Quantization | Bits | VRAM | + Context | File Size | Quality |
|---|---|---|---|---|---|
| Q2_K | 3.40 | 6.7 GB | 32.0 GB | 5.95 GB | 2-bit quantization with K-quant improvements |
| Q3_K_S | 3.50 | 6.8 GB | 32.2 GB | 6.13 GB | 3-bit small quantization |
| Q3_K_M | 3.90 | 7.5 GB | 32.9 GB | 6.83 GB | 3-bit medium quantization |
| Q4_K_M | 4.80 | 9.1 GB | 34.5 GB | 8.40 GB | 4-bit medium quantization — most popular sweet spot |
| Q5_K_M | 5.70 | 10.7 GB | 36.0 GB | 9.97 GB | 5-bit medium quantization — good quality/size tradeoff |
| Q6_K | 6.60 | 12.3 GB | 37.6 GB | 11.55 GB | 6-bit quantization, very good quality |
Which GPUs Can Run AceReason Nemotron 14B GGUF?
Q4_K_M · 9.1 GBAceReason Nemotron 14B GGUF (Q4_K_M) requires 9.1 GB of VRAM to load the model weights. For comfortable inference with headroom for KV cache and system overhead, 12+ GB is recommended. Using the full 131K context window can add up to 25.4 GB, bringing total usage to 34.5 GB. 28 GPUs can run it, including NVIDIA GeForce RTX 5090, NVIDIA GeForce RTX 3090 Ti, NVIDIA GeForce RTX 3080 Ti.
Runs great
— Plenty of headroom
Decent
— Enough VRAM, may be tightWhich Devices Can Run AceReason Nemotron 14B GGUF?
Q4_K_M · 9.1 GB27 devices with unified memory can run AceReason Nemotron 14B GGUF, including NVIDIA DGX H100, NVIDIA DGX A100 640GB.
Runs great
— Plenty of headroomRelated Models
Frequently Asked Questions
- How much VRAM does AceReason Nemotron 14B GGUF need?
AceReason Nemotron 14B GGUF requires 9.1 GB of VRAM at Q4_K_M, or 12.3 GB at Q6_K. Full 131K context adds up to 25.4 GB (34.5 GB total).
VRAM = Weights + KV Cache + Overhead
Weights = 14B × 4.8 bits ÷ 8 = 8.4 GB
KV Cache + Overhead ≈ 0.7 GB (at 2K context + ~0.3 GB framework)
KV Cache + Overhead ≈ 26.1 GB (at full 131K context)
VRAM usage by quantization
Q4_K_M9.1 GBQ4_K_M + full context34.5 GB- What's the best quantization for AceReason Nemotron 14B GGUF?
For AceReason Nemotron 14B GGUF, Q4_K_M (9.1 GB) offers the best balance of quality and VRAM usage. Q5_K_S (10.3 GB) provides better quality if you have the VRAM. The smallest option is IQ2_XXS at 4.5 GB.
VRAM requirement by quantization
IQ2_XXS4.5 GB~53%Q2_K6.7 GB~75%Q4_18.6 GB~88%Q4_K_M ★9.1 GB~89%Q5_K_S10.3 GB~92%Q6_K12.3 GB~95%★ Recommended — best balance of quality and VRAM usage.
- Can I run AceReason Nemotron 14B GGUF on a Mac?
AceReason Nemotron 14B GGUF requires at least 4.5 GB at IQ2_XXS, 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 AceReason Nemotron 14B GGUF locally?
Yes — AceReason Nemotron 14B GGUF can run locally on consumer hardware. At Q4_K_M quantization it needs 9.1 GB of VRAM. Popular tools include Ollama, LM Studio, and llama.cpp.
- How fast is AceReason Nemotron 14B GGUF?
At Q4_K_M, AceReason Nemotron 14B GGUF can reach ~320 tok/s on AMD Instinct MI300X. On NVIDIA GeForce RTX 4090: ~72 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 ÷ 9.1 × 0.55 = ~320 tok/s
Estimated speed at Q4_K_M (9.1 GB)
AMD Instinct MI300X~320 tok/sNVIDIA GeForce RTX 4090~72 tok/sNVIDIA H100 SXM~239 tok/sAMD Instinct MI250X~198 tok/sReal-world results typically within ±20%. Speed depends on batch size, quantization kernel, and software stack.
- What's the download size of AceReason Nemotron 14B GGUF?
At Q4_K_M, the download is about 8.40 GB. The full-precision Q6_K version is 11.55 GB. The smallest option (IQ2_XXS) is 3.85 GB.
- Which GPUs can run AceReason Nemotron 14B GGUF?
28 consumer GPUs can run AceReason Nemotron 14B GGUF at Q4_K_M (9.1 GB). Top options include AMD Radeon RX 6800, AMD Radeon RX 6800 XT, AMD Radeon RX 6900 XT, AMD Radeon RX 6700 XT. 17 GPUs have plenty of headroom for comfortable inference.
- Which devices can run AceReason Nemotron 14B GGUF?
27 devices with unified memory can run AceReason Nemotron 14B GGUF at Q4_K_M (9.1 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.