Model guide · prices from 2026-09-10 · API prices daily, full survey weekly
Cheapest way to run Qwen3 235B (MoE)
Qwen3 235B (MoE) needs ≈141 GB of VRAM at 4-bit — this week that starts at $1.81/hour (2× A100-SXM, cheapest tracked walk-up price). FP8 and FP16 below. VRAM calculators stop at the memory number; this connects it to live, graded prices across 20 providers.
MoE note: Qwen3 235B (MoE) activates ~22B active per token, but the full 235B weights must fit in VRAM — memory scales with total parameters, speed with active ones.
FP16 — ≈564 GB needed
| GPU | VRAM | GPUs needed | Cheapest tracked | Verifiable A/B |
|---|---|---|---|---|
| RTX5090 | 32 GB | 18 (multi-node) | $7.22/hr | — |
| A100-SXM | 80 GB | 8 | $7.26/hr | $18.40/hr |
| RTX4090 | 24 GB | 24 (multi-node) | $8.98/hr | — |
| MI300X | 192 GB | 3 | $10.35/hr | — |
| A100-PCIe | 80 GB | 8 | $10.80/hr | — |
| B300 | 288 GB | 2 | $15.00/hr | $35.60/hr |
| H100-PCIe | 80 GB | 8 | $15.92/hr | — |
| H200-SXM | 141 GB | 4 | $15.96/hr | $17.16/hr |
FP8/INT8 — ≈282 GB needed
| GPU | VRAM | GPUs needed | Cheapest tracked | Verifiable A/B |
|---|---|---|---|---|
| RTX5090 | 32 GB | 9 (multi-node) | $3.61/hr | — |
| A100-SXM | 80 GB | 4 | $3.63/hr | $9.20/hr |
| RTX4090 | 24 GB | 12 (multi-node) | $4.49/hr | — |
| A100-PCIe | 80 GB | 4 | $5.40/hr | — |
| MI300X | 192 GB | 2 | $6.90/hr | — |
| B300 | 288 GB | 1 | $7.50/hr | $17.80/hr |
| H100-PCIe | 80 GB | 4 | $7.96/hr | — |
| H200-SXM | 141 GB | 2 | $7.98/hr | $8.58/hr |
4-bit — ≈141 GB needed
| GPU | VRAM | GPUs needed | Cheapest tracked | Verifiable A/B |
|---|---|---|---|---|
| A100-SXM | 80 GB | 2 | $1.81/hr | $4.60/hr |
| RTX5090 | 32 GB | 5 | $2.00/hr | — |
| RTX4090 | 24 GB | 6 | $2.24/hr | — |
| A100-PCIe | 80 GB | 2 | $2.70/hr | — |
| MI300X | 192 GB | 1 | $3.45/hr | — |
| H100-PCIe | 80 GB | 2 | $3.98/hr | — |
| H200-SXM | 141 GB | 1 | $3.99/hr | $4.29/hr |
| L40S | 48 GB | 3 | $4.11/hr | — |
Method: VRAM ≈ parameters × bytes/parameter × 1.2 (20% headroom for KV cache and activations at ~8K context). Longer context or high concurrency needs more; training needs far more (optimizer states: ~4–8× weights). GPU counts assume even sharding. Above one 8-GPU node, the interconnect becomes the constraint — restrict to Grade A/B listings. Grades measure what sellers publish — deliverability of the written claim, not measured performance. No fleet holds a measured (Verified) badge yet; that tier arrives with the verification harness. Prices are this week's cheapest tracked walk-up listings (teaser prices excluded); every listing with grades and sources on the GPU pages. Interactive version for any model size: Model Fit.
These prices move weekly
The Delivered Compute Report tracks them — free, every row sourced.
Subscribe free