Mixtral 8x22B (MoE) at AWQ 4-bit needs 77.6 GB for its weights and 92.6 GB in total at 8K context with 8 concurrent users. That means it fits on a single Mac M4 Max (128GB). Every figure is computed by tokcalc's open-source capacity model.
| GPUs | Total VRAM | VRAM needed | Decode tok/s | Aggregate tok/s | TTFT | Cost / 1M tok | Fits? |
|---|---|---|---|---|---|---|---|
| 1× Mac | 128 GB | 92.6 GB | 14.56 | 109.0 | 75.27 s | — | ✓ |
| 2× Mac | 256 GB | 92.6 GB | 24.75 | 435.9 | 37.66 s | — | ✓ |
| 4× Mac | 512 GB | 92.6 GB | 49.50 | 1744 | 18.84 s | — | ✓ |
| 8× Mac | 1024 GB | 92.6 GB | 99.01 | 6974 | 9.44 s | — | ✓ |
| Context | Concurrent users | KV per request | Fits? |
|---|---|---|---|
| 4K | 53 | 962.1 MB | ✓ fits |
| 8K | 26 | 1.88 GB | ✓ fits |
| 33K | 6 | 7.52 GB | ✓ fits |
| 66K | 3 | 15.03 GB | ✓ fits |
| 131K | 1 | 30.06 GB | ✓ fits |
| GPU | GPUs | Aggregate tok/s | Cost / 1M tok |
|---|---|---|---|
| RTX 5090 32GB | 4× | 7799 | $0.0712 |
| A100 80GB SXM4 | 2× | 2176 | $0.3064 |
| H100 SXM5 80GB | 2× | 3645 | $0.3811 |
| AMD MI300X 192GB | 1× | 1696 | $0.4095 |
| L40S 48GB | 2× | 940.0 | $0.4137 |
| AMD MI325X 288GB | 1× | 1920 | $0.5064 |
Yes. Mixtral 8x22B (MoE) at AWQ 4-bit needs 92.6 GB including the KV cache, and Mac M4 Max (128GB) has 128 GB — so it fits on a single GPU.
14.56 tokens/sec per stream and 109.0 tok/s aggregate with continuous batching at 8 concurrent users. Time to first token is 75.27 s, and inter-token latency is 68.7 ms.
— per 1M output tokens at 1× Mac M4 Max (128GB). That is the marginal hardware cost — add idle capacity, ops, and egress for the real figure.
77.6 GB for the weights at AWQ 4-bit, plus 15.0 GB of KV cache for 8 concurrent requests at 8K context — 92.6 GB total. Every extra concurrent user at long context costs more, so leave headroom.
It works. Compare — per 1M tokens against the alternatives below — the cheapest option that fits the same workload is 8× RTX 4080 16GB at $0.0534, and the fastest is 4× Cerebras CS-3 (WSE-3) at 87040 tok/s.
Same formulas, your context length, concurrency, and quantisation.