MythoMax L2 13B — Hardware Requirements & GPU Compatibility
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9.4K downloads
374 likesSpecifications
- Publisher
- Gryphe
- Parameters
- 13B
- Architecture
- LlamaForCausalLM
- Context Length
- 4,096 tokens
- Vocabulary Size
- 32,000
- Release Date
- 2024-04-21
- License
- Other
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HuggingFace
How Much VRAM Does MythoMax L2 13B Need?
Select a quantization to see compatible GPUs below.
| Quantization | Bits | VRAM | + Context | File Size | Quality |
|---|---|---|---|---|---|
| FP16 | 16.00 | 28.0 GB | 29.7 GB | 26.00 GB | Full half-precision — baseline for inference |
Which GPUs Can Run MythoMax L2 13B?
FP16 · 28.0 GBMythoMax L2 13B (FP16) requires 28.0 GB of VRAM to load the model weights. For comfortable inference with headroom for KV cache and system overhead, 37+ GB is recommended. Using the full 4K context window can add up to 1.7 GB, bringing total usage to 29.7 GB. 1 GPU can run it, including NVIDIA GeForce RTX 5090.
All compatible consumer-level GPUs are running near their VRAM limit. You may also want to consider professional GPUs (e.g., NVIDIA A100, H100) which offer significantly more VRAM. For more headroom and better throughput, consider a multi-GPU configuration with tensor parallelism (supported by tools like vLLM, llama.cpp, or text-generation-inference).
Decent
— Enough VRAM, may be tightWhich Devices Can Run MythoMax L2 13B?
FP16 · 28.0 GB15 devices with unified memory can run MythoMax L2 13B, including NVIDIA DGX H100, NVIDIA DGX A100 640GB, Mac Studio M4 Max (36 GB).
Runs great
— Plenty of headroomDecent
— Enough memory, may be tightRelated Models
Frequently Asked Questions
- How much VRAM does MythoMax L2 13B need?
MythoMax L2 13B requires 28.0 GB of VRAM at FP16. Full 4K context adds up to 1.7 GB (29.7 GB total).
VRAM = Weights + KV Cache + Overhead
Weights = 13B × 16 bits ÷ 8 = 26 GB
KV Cache + Overhead ≈ 2 GB (at 2K context + ~0.3 GB framework)
KV Cache + Overhead ≈ 3.7 GB (at full 4K context)
VRAM usage by quantization
FP1628.0 GBFP16 + full context29.7 GB- Can I run MythoMax L2 13B on a Mac?
MythoMax L2 13B requires at least 28.0 GB at FP16, 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 MythoMax L2 13B locally?
Yes — MythoMax L2 13B can run locally on consumer hardware. At FP16 quantization it needs 28.0 GB of VRAM. Popular tools include Ollama, LM Studio, and llama.cpp.
- How fast is MythoMax L2 13B?
At FP16, MythoMax L2 13B can reach ~104 tok/s on AMD Instinct MI300X. 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 ÷ 28.0 × 0.55 = ~104 tok/s
Estimated speed at FP16 (28.0 GB)
AMD Instinct MI300X~104 tok/sNVIDIA H100 SXM~78 tok/sAMD Instinct MI250X~64 tok/sReal-world results typically within ±20%. Speed depends on batch size, quantization kernel, and software stack.
- What's the download size of MythoMax L2 13B?
At FP16, the download is about 26.00 GB.
- Which GPUs can run MythoMax L2 13B?
1 consumer GPU can run MythoMax L2 13B at FP16 (28.0 GB). Top options include NVIDIA GeForce RTX 5090.
- Which devices can run MythoMax L2 13B?
15 devices with unified memory can run MythoMax L2 13B at FP16 (28.0 GB), including Mac Mini M4 (32 GB), Mac Mini M4 Pro (48 GB), Mac Pro M2 Ultra (192 GB), Mac Studio M2 Ultra (192 GB). Apple Silicon Macs use unified memory shared between CPU and GPU, making them well-suited for local LLM inference.