Meme Trix MoE 14B A8B V1 — Hardware Requirements & GPU Compatibility
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Meme Trix MoE 14B A8B V1 is a 13.7B-parameter open language model from Naphula. It supports a context window of up to 1,073,152 tokens. At Q4_0 it needs about 7.41 GB of VRAM — see which GPUs and Macs can run it below.
130 downloads
8 likesSpecifications
- Publisher
- Naphula
- Parameters
- 13.7B
- Architecture
- MixtralForCausalLM
- Context Length
- 1,073,152 tokens
- Vocabulary Size
- 129,024
- Release Date
- 2026-03-14
- License
- Apache 2.0
Get Started
HuggingFace
How Much VRAM Does Meme Trix MoE 14B A8B V1 Need?
Select a quantization to see compatible GPUs below.
| Quantization | Bits | VRAM | + Context | File Size | Quality |
|---|---|---|---|---|---|
| Q4_0 | 4.00 | 7.4 GB | 147.8 GB | 6.84 GB | 4-bit legacy quantization |
| Q4_1 | 4.50 | 8.3 GB | 148.7 GB | 7.69 GB | 4-bit legacy quantization with offset |
| Q5_0 | 5.00 | 9.1 GB | 149.5 GB | 8.55 GB | 5-bit legacy quantization |
| Q5_1 | 5.50 | 10.0 GB | 150.4 GB | 9.40 GB | 5-bit legacy quantization with offset |
| Q8_0 | 8.00 | 14.2 GB | 154.6 GB | 13.67 GB | 8-bit quantization, near-lossless |
Which GPUs Can Run Meme Trix MoE 14B A8B V1?
Q4_0 · 7.4 GBMeme Trix MoE 14B A8B V1 (Q4_0) requires 7.4 GB of VRAM to load the model weights. For comfortable inference with headroom for KV cache and system overhead, 10+ GB is recommended. Using the full 1073K context window can add up to 140.4 GB, bringing total usage to 147.8 GB. 35 GPUs can run it, including NVIDIA GeForce RTX 5090, NVIDIA GeForce RTX 3090 Ti, NVIDIA GeForce RTX 3080.
Runs great
— Plenty of headroom
Decent
— Enough VRAM, may be tightWhich Devices Can Run Meme Trix MoE 14B A8B V1?
Q4_0 · 7.4 GB33 devices with unified memory can run Meme Trix MoE 14B A8B V1, including NVIDIA DGX H100, NVIDIA DGX A100 640GB, MacBook Air 13" M3 (8 GB).
Runs great
— Plenty of headroomDecent
— Enough memory, may be tightRelated Models
Frequently Asked Questions
- How much VRAM does Meme Trix MoE 14B A8B V1 need?
Meme Trix MoE 14B A8B V1 requires 7.4 GB of VRAM at Q4_0, or 14.2 GB at Q8_0. Full 1073K context adds up to 140.4 GB (147.8 GB total).
VRAM = Weights + KV Cache + Overhead
Weights = 13.7B × 4 bits ÷ 8 = 6.8 GB
KV Cache + Overhead ≈ 0.6 GB (at 2K context + ~0.3 GB framework)
KV Cache + Overhead ≈ 141 GB (at full 1073K context)
VRAM usage by quantization
Q4_07.4 GBQ4_0 + full context147.8 GB- What's the best quantization for Meme Trix MoE 14B A8B V1?
For Meme Trix MoE 14B A8B V1, Q5_0 (9.1 GB) offers the best balance of quality and VRAM usage. Q5_1 (10.0 GB) provides better quality if you have the VRAM. The smallest option is Q4_0 at 7.4 GB.
VRAM requirement by quantization
Q4_07.4 GBQ4_18.3 GBQ5_0 ★9.1 GBQ5_110.0 GBQ8_014.2 GB★ Recommended — best balance of quality and VRAM usage.
- Can I run Meme Trix MoE 14B A8B V1 on a Mac?
Meme Trix MoE 14B A8B V1 requires at least 7.4 GB at Q4_0, 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 Meme Trix MoE 14B A8B V1 locally?
Yes — Meme Trix MoE 14B A8B V1 can run locally on consumer hardware. At Q4_0 quantization it needs 7.4 GB of VRAM. Popular tools include Ollama, LM Studio, and llama.cpp.
- How fast is Meme Trix MoE 14B A8B V1?
At Q4_0, Meme Trix MoE 14B A8B V1 can reach ~393 tok/s on AMD Instinct MI300X. On NVIDIA GeForce RTX 4090: ~88 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 ÷ 7.4 × 0.55 = ~393 tok/s
Estimated speed at Q4_0 (7.4 GB)
~393 tok/s~88 tok/s~294 tok/s~243 tok/sReal-world results typically within ±20%. Speed depends on batch size, quantization kernel, and software stack.
- What's the download size of Meme Trix MoE 14B A8B V1?
At Q4_0, the download is about 6.84 GB. The full-precision Q8_0 version is 13.67 GB.
- Which GPUs can run Meme Trix MoE 14B A8B V1?
35 consumer GPUs can run Meme Trix MoE 14B A8B V1 at Q4_0 (7.4 GB). Top options include AMD Radeon RX 6700 XT, AMD Radeon RX 6800, AMD Radeon RX 6800 XT, AMD Radeon RX 7600. 26 GPUs have plenty of headroom for comfortable inference.
- Which devices can run Meme Trix MoE 14B A8B V1?
33 devices with unified memory can run Meme Trix MoE 14B A8B V1 at Q4_0 (7.4 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.