ChatMusician — Hardware Requirements & GPU Compatibility
Chat
ChatMusician is a 6.7B-parameter open language model from m-a-p. It supports a context window of up to 2,048 tokens. At FP16 it needs about 14.85 GB of VRAM — see which GPUs and Macs can run it below.
1.8K downloads
155 likesSpecifications
- Publisher
- m-a-p
- Parameters
- 6.7B
- Architecture
- LlamaForCausalLM
- Context Length
- 2,048 tokens
- Vocabulary Size
- 32,000
- Release Date
- 2024-04-08
- License
- MIT
Get Started
HuggingFace
How Much VRAM Does ChatMusician Need?
Select a quantization to see compatible GPUs below.
| Quantization | Bits | VRAM | + Context | File Size | Quality |
|---|---|---|---|---|---|
| FP16 | 16.00 | 14.8 GB | — | 13.48 GB | Full half-precision — baseline for inference |
Which GPUs Can Run ChatMusician?
FP16 · 14.8 GBChatMusician (FP16) requires 14.8 GB of VRAM to load the model weights. For comfortable inference with headroom for KV cache and system overhead, 20+ GB is recommended. 17 GPUs can run it, including NVIDIA GeForce RTX 5090, NVIDIA GeForce RTX 3090 Ti, NVIDIA GeForce RTX 5080.
Runs great
— Plenty of headroom
Decent
— Enough VRAM, may be tightWhich Devices Can Run ChatMusician?
FP16 · 14.8 GB27 devices with unified memory can run ChatMusician, including NVIDIA DGX H100, NVIDIA DGX A100 640GB, Mac Mini M4 (16 GB).
Runs great
— Plenty of headroomRelated Models
Frequently Asked Questions
- How much VRAM does ChatMusician need?
ChatMusician requires 14.8 GB of VRAM at FP16.
VRAM = Weights + KV Cache + Overhead
Weights = 6.7B × 16 bits ÷ 8 = 13.5 GB
KV Cache + Overhead ≈ 1.3 GB (at 2K context + ~0.3 GB framework)
VRAM usage by quantization
FP1614.8 GB- Can I run ChatMusician on a Mac?
ChatMusician requires at least 14.8 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 ChatMusician locally?
Yes — ChatMusician can run locally on consumer hardware. At FP16 quantization it needs 14.8 GB of VRAM. Popular tools include Ollama, LM Studio, and llama.cpp.
- How fast is ChatMusician?
At FP16, ChatMusician can reach ~196 tok/s on AMD Instinct MI300X. On NVIDIA GeForce RTX 4090: ~44 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 ÷ 14.8 × 0.55 = ~196 tok/s
Estimated speed at FP16 (14.8 GB)
~196 tok/s~44 tok/s~147 tok/s~121 tok/sReal-world results typically within ±20%. Speed depends on batch size, quantization kernel, and software stack.
- What's the download size of ChatMusician?
At FP16, the download is about 13.48 GB.
- Which GPUs can run ChatMusician?
17 consumer GPUs can run ChatMusician at FP16 (14.8 GB). Top options include AMD Radeon RX 7900 XTX, NVIDIA GeForce RTX 3090, NVIDIA GeForce RTX 3090 Ti, AMD Radeon RX 6800. 5 GPUs have plenty of headroom for comfortable inference.
- Which devices can run ChatMusician?
27 devices with unified memory can run ChatMusician at FP16 (14.8 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.