HARDWARE FIT CHECK • Meta Muse Spark Open (816B-A42B MoE) + AMD Radeon RX 7900 XT (20GB GDDR6)512.86 GB / 20 GB VRAM

Can I Run Meta Muse Spark Open (816B-A42B MoE) on AMD Radeon RX 7900 XT (20GB GDDR6)?

Full VRAM footprint analysis, tokens/sec generation benchmark, and copy-paste Ollama & vLLM runtime commands for running Meta Muse Spark Open (816B-A42B MoE) (816B) on AMD Radeon RX 7900 XT (20GB GDDR6) (20 GB).

✕ OOM512.86 GB (2564%)0 t/s

Meta Muse Spark Open (816B-A42B MoE) on AMD Radeon RX 7900 XT (20GB GDDR6)

✕ Out of Memory — Exceeds VRAM Capacity

✕ OOM

Required VRAM

512.86 GB

2564% of hardware capacity (20 GB)

Est. Decode Speed

0 tok/s

42B active params @ 800 GB/s

Available Headroom

-492.86 GB

Needs +492.86 GB more VRAM

Memory Allocation & Headroom

512.86 GB allocated of 20 GB capacity

2564% utilized

Weights: 489.6 GB

KV: (32K): 5.37 GB

Overhead: 17.89 GB

Deficit: -492.86 GB

⚡ Architecture & Throughput Transparency: Single-user decode speed (~0 tok/s) is memory-bandwidth bound at batch size = 1 on AMD Radeon RX 7900 XT (20GB GDDR6) (800 GB/s). Prompt prefill / TTFT (~0 tok/s) is compute-bound and utilizes GPU Tensor cores. Actual latency varies with FlashAttention-2 and runtime engine (Ollama/vLLM/llama.cpp).

OLLAMA_FLASH_ATTENTION=1 OLLAMA_KV_CACHE_TYPE=q8_0 ollama run muse-spark:816b

Local Hardware Configurations & Pricing

⚠️ Out of VRAM: High-Capacity Hardware Upgrades

High-bandwidth VRAM specs and current market prices

Multi-GPU Rig↑ Upgrade

48 GB VRAM

2x NVIDIA RTX 3090 Dual Rig (48GB Total VRAM)

Best price-to-VRAM homelab rig for 70B Q4_K_M & Qwen 3.8 27B Q8

936 GB/s700W TDP

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Apple Silicon↑ Upgrade

112 GB VRAM

Apple Mac Studio M4 Max (128GB Unified Memory)

Running Llama 4 Scout 109B & 70B Q8 locally with 128K+ context

546 GB/s145W TDP

$3,499Amazon Prime →

Consumer GPU

20 GB VRAM

AMD Radeon RX 7900 XT (20GB GDDR6)

Sub-$700 GPU with 20GB VRAM fitting 14B Q8 and 27B Q4 models

800 GB/s315W TDP

$699Amazon Prime →

⚠️ Out of VRAM? Don't downgrade model quality.

Out of VRAM

Spin up an on-demand cloud GPU instance in 60 seconds with pre-installed Ollama and vLLM. (Meta Muse Spark Open (816B-A42B MoE) @ 512.86 GB VRAM)

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Rent Spot GPU →

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Quantization Precision Matrix

32K ctx • KV: Q8_0

Quantization	Weights	KV Cache	Total VRAM	Fit Status
FP1616 bpw	1632 GB	5.37 GB	1695.24 GB (8476%)	OOM
Q8_08.5 bpw	864.96 GB	5.37 GB	901.35 GB (4507%)	OOM
Q6_K6.56 bpw	669.12 GB	5.37 GB	698.66 GB (3493%)	OOM
Q5_K_M5.68 bpw	579.36 GB	5.37 GB	605.76 GB (3029%)	OOM
Q4_K_M4.8 bpw	489.6 GB	5.37 GB	512.86 GB (2564%)	OOM
FP44.25 bpw	432.48 GB	5.37 GB	453.74 GB (2269%)	OOM
IQ3_XS3.3 bpw	334.56 GB	5.37 GB	352.39 GB (1762%)	OOM

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FAQ & Reference

Frequently Asked Questions: Meta Muse Spark Open (816B-A42B MoE) on AMD Radeon RX 7900 XT (20GB GDDR6)

How much VRAM does Meta Muse Spark Open (816B-A42B MoE) need on AMD Radeon RX 7900 XT (20GB GDDR6)?

At standard 4-bit quantization (Q4_K_M) with 32K context, Meta Muse Spark Open (816B-A42B MoE) requires 512.86 GB of total VRAM (weights + KV cache + CUDA runtime overhead).

What inference speed will Meta Muse Spark Open (816B-A42B MoE) achieve on AMD Radeon RX 7900 XT (20GB GDDR6)?

Based on AMD Radeon RX 7900 XT (20GB GDDR6)'s 800 GB/s memory bandwidth, expected decode speed is approximately 0 tokens per second.

Can I expand context beyond 32K tokens?

Each additional 32K tokens of context requires additional KV cache memory. For longer context windows, consider 8-bit or 4-bit KV cache quantization.