AMD Instinct MI325X
The AMD Instinct MI325X is an enterprise-class GPU built on the CDNA 3 architecture, featuring 256 GB of memory with 6,000 GB/s of memory bandwidth and a 1,000 W TDP. It delivers 163.4 TFLOPS of FP32 performance and 1,307 TFLOPS of FP16 tensor performance. Currently available from 2 providers starting at $2.25/GPU/hour, with a market median of $3.05/GPU/hour across 5 configurations.
Hardware specifications
Same across all providers
Median price across all providers
2 offerings from 2 providers
Sorted by price ascending. Compare configurations side-by-side.
| Provider | Count | vCPU | RAM | Region | Per GPU hour | Total/hr | Action |
|---|---|---|---|---|---|---|---|
TensorWaveCheapest | ×1 | — | — | $2.250 | $2.25 | Launch | |
Up to$1credit | ×8 | 128 | 1.5 TB | From$3.025 +0.2% 30d | From$24.20 | Launch |
LLMs that fit on the AMD Instinct MI325X
Estimated VRAM for popular open-weight LLMs at 16-bit (FP16/BF16), 8-bit (FP8/INT8) and 4-bit (INT4/MXFP4) precision, against 256 GB per GPU. Showing the 12 largest that fit.
| Model | Parameters | 16-bit | 8-bit | 4-bit |
|---|---|---|---|---|
| Kimi K3 Moonshot AI | 2.8T 104B active | — Not released | — Not released | 1,873 GB 8× · 175 GB free |
| DeepSeek V4 Pro DeepSeek | 1.6T 49B active | — Not released | — Not released | 1,038 GB 8× · 1,010 GB free or 4× · 18% spare |
| Kimi K2.5 Moonshot AI | 1T 32B active | — Not released | — Not released | 714 GB 4× · 310 GB free |
| GLM-5.2 Z.ai | 753B | 1,808 GB 8× · 240 GB free | 994 GB 4× · 30 GB free | 579 GB 4× · 445 GB free or 2× · 6% spare |
| DeepSeek R1 DeepSeek | 671B 37B active | — Not released | 826 GB 4× · 198 GB free | 481 GB 2× · 31 GB free |
| DeepSeek V4 Flash DeepSeek | 284B | — Not released | — Not released | 192 GB 1× · 64 GB free |
| Solar Open2 250B Upstage | 250B 15B active | 601 GB 4× · 423 GB free or 2× · 2% spare | 330 GB 2× · 182 GB free | 192 GB 1× · 64 GB free |
| Qwen3 235B-A22B Alibaba | 235B 22B active | 564 GB 4× · 460 GB free or 2× · 8% spare | 310 GB 2× · 202 GB free | 181 GB 1× · 75 GB free |
| Laguna-S 2.1 Poolside | 118B 8B active | 282 GB 2× · 230 GB free or 1× · 8% spare | 155 GB 1× · 101 GB free | 90 GB 1× · 166 GB free |
| gpt-oss-120b OpenAI | 117B 5.1B active | — Not released | — Not released | 78 GB 1× · 178 GB free |
| Qwen3.6 35B-A3B Alibaba | 35B 3B active | 86 GB 1× · 170 GB free | 47 GB 1× · 209 GB free | 28 GB 1× · 228 GB free |
| Qwen3 32B Alibaba | 32.8B | 79 GB 1× · 177 GB free | 43 GB 1× · 213 GB free | 25 GB 1× · 231 GB free |
Estimates: model weights plus 20% for KV cache and runtime overhead, at short context lengths. Long contexts and large batches need more. Rows marked “tight” hold the weights but not that full margin. A ×N figure is the total VRAM across N of these GPUs and makes no claim about interconnect throughput. How we estimate this · Start from a model instead
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