Cheapest way to run Qwen3.8-35B-A3B (Empero Distill)
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Qwen3.8-35B-A3B (Empero Distill) needs 21.9 GB at 4-bit — cheapest rental $0.33/hr.
Quick answer
At 4-bit with an 8K-token conversation, Qwen3.8-35B-A3B (Empero Distill) needs about 21.9 GB. It fits a RTX 5090 (32 GB), so if you already own one it costs nothing per token; the cheapest rental big enough is RTX A6000 on Runpod at $0.33 an hour.
| Option | What you need | Cost | Notes |
|---|---|---|---|
| Your own GPU | RTX 5090 (32 GB) at 4-bit (Q4_K_M), needs 21.9 GB | No GPU purchase prices in our data. Check price on Amazon Amazon affiliate link | $0 per token or hour once you own the card (power not counted) |
| Mac (unified memory) | Mac, 32 GB at 4-bit (Q4_K_M), needs 21.9 GB | No Mac prices in our data | $0 per token once you own it |
| Rent a GPU | RTX A6000 (48 GB total) on Runpod Referral link, Community Cloud | $0.33 per hour | Pay only while it runs. Price checked 2026-11-09 |
Fit rule: the Q4_K_M file (or the highest precision that fits) plus an 8K-token FP16 KV cache under 90% of memory, same as the calculator. Sizes and sources: Qwen3.8-35B-A3B (Empero Distill) VRAM page. Rental prices: GPU prices (checked 2026-11-09). Hourly and per-token prices measure different things, so which is cheaper depends on how much you use it.
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Precision ladder: what each quant costs
| Precision | Needs at 8K | Smallest consumer GPU | Smallest Mac | Cheapest single-GPU rental | Cheapest rental overall (any GPU count) |
|---|---|---|---|---|---|
| 16-bit (FP16/BF16) | 71.2 GB | none (max 32 GB) | Mac, 96 GB at 16-bit (FP16/BF16) | A100 PCIe (80 GB) on Vast.ai, $0.40/hr | A100 PCIe (80 GB) on Vast.ai, $0.40/hr |
| 8-bit (Q8_0) | 38.0 GB | none (max 32 GB) | Mac, 48 GB at 8-bit (Q8_0) | RTX A6000 (48 GB) on Runpod, $0.33/hr | RTX A6000 (48 GB) on Runpod, $0.33/hr |
| 4-bit (Q4_K_M) | 21.9 GB | RTX 5090 (32 GB) | Mac, 32 GB at 4-bit (Q4_K_M) | RTX A6000 (48 GB) on Runpod, $0.33/hr | RTX A6000 (48 GB) on Runpod, $0.33/hr |
Every row names its precision, Mac rows included (Macs share unified memory with the system, so the same 90% rule applies). Single-GPU and multi-GPU rentals are listed separately: a multi-GPU rental needs software that splits the model across cards (llama.cpp, vLLM tensor parallel). Prices checked 2026-11-09.
How context length changes the bill (4-bit)
| Context | Needs | Cheapest rental overall |
|---|---|---|
| 8K tokens | 21.9 GB | RTX A6000 (48 GB) on Runpod, $0.33/hr |
| 32K tokens | 22.4 GB | RTX A6000 (48 GB) on Runpod, $0.33/hr |
| 128K tokens | 24.4 GB | RTX A6000 (48 GB) on Runpod, $0.33/hr |
What $100 of rental buys you
We list no GPU purchase prices (they change daily and we cannot check them), so this page does not compare renting with buying. At the cheapest rental that fits (RTX A6000 (48 GB) on Runpod, $0.33/hr), $100 of rental buys about 303 hours of running Qwen3.8-35B-A3B (Empero Distill) at 4-bit with 8K context. Electricity, storage and setup time are not counted.
Fit quirks for this model
- Mixture-of-experts: about 3.0B parameters are active per token, but every expert must still be in memory, so VRAM follows the total size, not the active size.
- Only the 10 full-attention layers grow with context: 10 × 2 KV heads × 256 head dim × 2 × 2 bytes. The 30 Gated DeltaNet layers keep a fixed-size state that is not included.
- GGUF sizes from Empero's own Distill-GGUF repo (imatrix-calibrated IQ* and K-quants).
Model data checked 2026-10-28; rental prices checked 2026-11-09. For file sizes, sources and the full fit table see the Qwen3.8-35B-A3B (Empero Distill) VRAM requirements page; this page is only about cost.
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