microsoft/Phi-3-medium-4k-instruct
14B params · est. 8.4 GB Q4
Head-to-head
Dedicated comparison page for two real hardware profiles. This is built from your benchmark database, trust metadata, and buyer flow instead of generic spec-sheet comparisons.
Device profile
70B FP16 with substantial context, 405B Q4 with headroom. Production multi-tenant serving at batch 8-64 via TensorRT-LLM or vLLM.
612 tok/s
80 GB
700 W
9.4
Device profile
Large-model inference where VRAM capacity matters more than peak compute — 405B Q4 with headroom, 70B FP16 comfortably
920 tok/s
192 GB
750 W
9.3
NVIDIA H100 SXM5 80GB scores 9.4 while AMD Instinct MI300X 192GB scores 9.3 on MyAIHardware's composite rating.
AMD Instinct MI300X 192GB wins VRAM capacity.
NVIDIA H100 SXM5 80GB is the lower-power path.
On shared workload evidence, Llama 3 8B Q4 is benchmarked at 178 tok/s for NVIDIA H100 SXM5 80GB and 122 tok/s for AMD Instinct MI300X 192GB.
| Metric | NVIDIA H100 SXM5 80GB | AMD Instinct MI300X 192GB |
|---|---|---|
| MyAI rating | 9.4 | 9.3 |
| Best LLM | 612 tok/s | 920 tok/s |
| VRAM | 80 GB | 192 GB |
| TDP | 700 W | 750 W |
| MSRP | $25k | $15k |
| Workloads | 13 | 12 |
Llama 3 8B Q4
Llama 3 8B Q4
NVIDIA H100 SXM5 80GB
178 tok/s
Q4_K_M / 80GB / 2024-11-08
AMD Instinct MI300X 192GB
122 tok/s
Q4_K_M / 192GB / 2025-04-08
Mistral 7B Q4
Mistral 7B
NVIDIA H100 SXM5 80GB
295 tok/s
Q4_K_M / 80GB / 2025-05-08
AMD Instinct MI300X 192GB
268 tok/s
Q4_K_M / 192GB / 2025-05-19
Gemma 2 9B Q4
Gemma 2 9B
NVIDIA H100 SXM5 80GB
215 tok/s
Q4_K_M / 80GB / 2024-10-14
AMD Instinct MI300X 192GB
188 tok/s
Q4_K_M / 192GB / 2025-12-08
DeepSeek-R1 Distill 7B
DeepSeek-R1 7B
NVIDIA H100 SXM5 80GB
245 tok/s
Q4_K_M / 80GB / 2024-08-04
AMD Instinct MI300X 192GB
215 tok/s
Q4_K_M / 192GB / 2026-03-19
Qwen 2.5 14B Q4
Qwen 2.5 14B
NVIDIA H100 SXM5 80GB
168 tok/s
Q4_K_M / 80GB / 2024-10-21
AMD Instinct MI300X 192GB
142 tok/s
Q4_K_M / 192GB / 2024-12-04
Llama 3 70B Q4
Llama 3 70B Q4
NVIDIA H100 SXM5 80GB
66.0 tok/s
Q4_K_M / 80GB / 2024-06-24
AMD Instinct MI300X 192GB
72.0 tok/s
Q4_K_M / 192GB / 2025-07-11
This shortlist cross-references the external OpenEvals snapshot with an approximate Q4-class VRAM estimate. Use it to sanity-check whether the hardware you are comparing can host strong open models, not just benchmark toy workloads.
microsoft/Phi-3-medium-4k-instruct
14B params · est. 8.4 GB Q4
Qwen/Qwen2-72B
73B params · est. 43.6 GB Q4
microsoft/Phi-3.5-mini-instruct
3.8B params · est. 2.3 GB Q4
internlm/internlm2_5-7b-chat
7.7B params · est. 4.6 GB Q4