MODEL ARCHITECTURE SPEC โข META AI816B MoE
Meta Muse Spark Open (816B-A42B MoE) VRAM & inference speed
816B Total Params42B Active (MoE)80 Layers โข 8 KV Heads64K Default Ctx (Max 977K)Ollama: muse-spark:816b
Accurate memory requirements, KV cache footprint, and tokens/sec generation benchmarks for running Meta Muse Spark Open (816B-A42B MoE) across local GPUs, Apple Silicon Macs, and cloud instances.
โ Out of Memory (OOM) โ Exceeds Hardware VRAM512.86 GB (641%)0 t/s
Meta Muse Spark Open (816B-A42B MoE) on NVIDIA H100 SXM (80GB HBM3 Cloud GPU)
โ Out of Memory โ Exceeds VRAM Capacity
โ OOM
Required VRAM
512.86 GB
641% of hardware capacity (80 GB)Est. Decode Speed
0 tok/s
42B active params @ 3350 GB/sAvailable Headroom
-432.86 GB
Needs +432.86 GB more VRAMMemory Allocation & Headroom
512.86 GB allocated of 80 GB capacity
641% utilized
Weights: 489.6 GB
KV: (32K): 5.37 GB
Overhead: 17.89 GB
Deficit: -432.86 GB
โก Architecture & Throughput Transparency: Single-user decode speed (~0 tok/s) is memory-bandwidth bound at batch size = 1 on NVIDIA H100 SXM (80GB HBM3 Cloud GPU) (3350 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:816bโ ๏ธ Out of VRAM? Don't downgrade model quality.
Out of VRAMSpin 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)
RunPod Cloud GPUsBest 1-Click Ollama & vLLM
$0.34/hr (RTX 4070 Ti) โ $2.39/hr (H100)Vast.ai GPU MarketplaceCheapest Dual RTX 3090 / 4090
$0.18/hr (RTX 3060) โ $0.55/hr (RTX 4090)Lambda GPU CloudEnterprise 8x H100 Clusters
$1.99/hr (GH200 / H100)Quantization Precision Matrix
32K ctx โข KV: Q8_0| Quantization | Weights | KV Cache | Total VRAM | Est. Speed | Fit Status |
|---|---|---|---|---|---|
| FP1616 bpw | 1632 GB | 5.37 GB | 1695.24 GB (2119%) | 0 t/s | OOM |
| Q8_08.5 bpw | 864.96 GB | 5.37 GB | 901.35 GB (1127%) | 0 t/s | OOM |
| Q6_K6.56 bpw | 669.12 GB | 5.37 GB | 698.66 GB (873%) | 0 t/s | OOM |
| Q5_K_M5.68 bpw | 579.36 GB | 5.37 GB | 605.76 GB (757%) | 0 t/s | OOM |
| Q4_K_M4.8 bpw | 489.6 GB | 5.37 GB | 512.86 GB (641%) | 0 t/s | OOM |
| FP44.25 bpw | 432.48 GB | 5.37 GB | 453.74 GB (567%) | 0 t/s | OOM |
| IQ3_XS3.3 bpw | 334.56 GB | 5.37 GB | 352.39 GB (440%) | 0 t/s | OOM |
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Hardware Compatibility Matrix for Meta Muse Spark Open (816B-A42B MoE)
Standard Q4_K_M precision with 32K context window and Q8_0 KV cache
| Hardware System | VRAM Envelope | Required VRAM | Headroom | Est. Decode Speed | Compatibility | Test Fit |
|---|---|---|---|---|---|---|
| NVIDIA GeForce RTX 5090 (32GB GDDR7) Consumer GPU โข 1792 GB/s | 32 GB | 512.86 GB | -480.86 GB | 0 (OOM) | โ OOM | Test Fit โ |
| NVIDIA GeForce RTX 4090 (24GB GDDR6X) Consumer GPU โข 1008 GB/s | 24 GB | 512.86 GB | -488.86 GB | 0 (OOM) | โ OOM | Test Fit โ |
| 2x NVIDIA RTX 3090 Dual Rig (48GB Total VRAM) Multi-GPU Rig โข 936 GB/s | 48 GB | 512.86 GB | -464.86 GB | 0 (OOM) | โ OOM | Test Fit โ |
| NVIDIA GeForce RTX 5080 (16GB GDDR7) Consumer GPU โข 960 GB/s | 16 GB | 512.86 GB | -496.86 GB | 0 (OOM) | โ OOM | Test Fit โ |
| NVIDIA RTX 4070 Ti Super (16GB) Consumer GPU โข 672 GB/s | 16 GB | 512.86 GB | -496.86 GB | 0 (OOM) | โ OOM | Test Fit โ |
| NVIDIA GeForce RTX 3060 (12GB) Consumer GPU โข 360 GB/s | 12 GB | 512.86 GB | -500.86 GB | 0 (OOM) | โ OOM | Test Fit โ |
| Apple Mac Mini M4 Pro (64GB Unified Memory) Apple Silicon โข 273 GB/s | 54 GB | 512.86 GB | -458.86 GB | 0 (OOM) | โ OOM | Test Fit โ |
| Apple Mac Studio M4 Max (128GB Unified Memory) Apple Silicon โข 546 GB/s | 112 GB | 512.86 GB | -400.86 GB | 0 (OOM) | โ OOM | Test Fit โ |
| Apple Mac Studio M5 Ultra (256GB Unified Memory) Apple Silicon โข 890 GB/s | 236 GB | 512.86 GB | -276.86 GB | 0 (OOM) | โ OOM | Test Fit โ |
| AMD Strix Halo Mini-PC (Ryzen AI Max+ 395 128GB) Unified APU / Mini-PC โข 256 GB/s | 110 GB | 512.86 GB | -402.86 GB | 0 (OOM) | โ OOM | Test Fit โ |
| NVIDIA DGX Spark (128GB Grace-Blackwell Unified) AI Appliance โข 273 GB/s | 118 GB | 512.86 GB | -394.86 GB | 0 (OOM) | โ OOM | Test Fit โ |
| NVIDIA H100 SXM (80GB HBM3 Cloud GPU) Datacenter Cloud GPU โข 3350 GB/s | 80 GB | 512.86 GB | -432.86 GB | 0 (OOM) | โ OOM | Test Fit โ |