AMD Instinct MI300X vs NVIDIA H100 80GB
Side-by-side local AI comparison: VRAM, memory bandwidth, model compatibility, and estimated tokens per second across 107 open-weight models.
Quick verdict
AMD Instinct MI300X wins for local AI inference. It has 112 GB more VRAM and 58.2% more memory bandwidth, runs 87 models natively (vs 72), and exclusively fits 15 models the other cannot. Note: AMD Instinct MI300X uses ROCM while NVIDIA H100 80GB uses CUDA; software ecosystem matters for your framework.
Specs comparison
| Spec | AMD Instinct MI300X | NVIDIA H100 80GB |
|---|---|---|
| VRAM | 192 GB | 80 GB |
| Memory type | HBM3 | HBM3 |
| Bandwidth | 5300 GB/s(+58%) | 3350 GB/s |
| Architecture | CDNA 3 | Hopper |
| Backend | ROCM | CUDA |
| Tier | Datacenter | Datacenter |
| Released | 2023 | 2022 |
| Models (native) | 87 | 72 |
Estimated tokens per second
Computed from memory bandwidth and model active-parameter weight. Assumes model fits natively in VRAM.
| Model | AMD Instinct MI300X | NVIDIA H100 80GB | Delta |
|---|---|---|---|
| Llama 3.3 70B Instruct(70B) | 11.1 t/s(BF16) | 20.7 t/s(Q6_K) | +18%at Q6_K |
| Qwen 3.6 27B(27B) | 27.4 t/s(BF16) | 23.1 t/s(BF16) | +19% |
| Llama 3.1 8B Instruct(8B) | 82.3 t/s(BF16) | 70 t/s(BF16) | +18% |
| Qwen 2.5 7B Instruct(7.6B) | 90.4 t/s(BF16) | 76.8 t/s(BF16) | +18% |
Delta is AMD Instinct MI300X relative to NVIDIA H100 80GB, compared at the highest quantization that fits natively on both cards.
Only AMD Instinct MI300X can run(15)
- Llama 3.1 405B Instruct405B
- Llama 4 Maverick 400B400B
- Ornith 1.5 397B (MoE)396.8B
- GLM-4.7 358B358B
- GLM-4.5 355B355B
- GLM-4.6 355B355B
- GLM-5.3-Flash 320B320B
- DeepSeek V4 Flash 284B284B
- DeepSeek V4 Flash 0731 284B284B
- Qwen3 235B-A22B (MoE)235B
- MiniMax M2.5 229B229B
- MiniMax M2.7 229B229B
- +3 more
Only NVIDIA H100 80GB can run(0)
No exclusive models: AMD Instinct MI300X can run everything NVIDIA H100 80GB can.
Both run natively(72)
These models fit in VRAM on both GPUs. Bandwidth determines which runs them faster.
- Mixtral 8x22B Instruct v0.127.7 t/svs59.9 t/s
- Mistral Medium 3.5 128B11.3 t/svs19.2 t/s
- Ornith 1.5 122B (MoE)66.1 t/svs132.2 t/s
- Qwen 3.5 122B-A10B (MoE)66.1 t/svs132.2 t/s
- Nemotron 3 Super 120B42.5 t/svs82.4 t/s
- Nemotron 3.5 Super VL 120B-A12B42.5 t/svs87.4 t/s
- GPT-OSS 120B100.9 t/svs194.2 t/s
- Llama 4 Scout 109B37.3 t/svs69.3 t/s
- GLM-4.5 Air 106B59.4 t/svs98.2 t/s
- GLM-4.6V 106B59.4 t/svs98.2 t/s
- Qwen 2.5 72B Instruct10.8 t/svs20.2 t/s
- Llama 3.3 70B Instruct11.1 t/svs20.7 t/s
- DeepSeek R1 Distill Llama 70B11.1 t/svs20.7 t/s
- Llama 3.1 70B Instruct11.1 t/svs20.7 t/s
- Mixtral 8x7B Instruct v0.145.7 t/svs75 t/s
- Flint 40B (MoE)83.5 t/svs162.9 t/s
- +56 more on both
Which should you choose?
- • You need to run larger models (>80 GB VRAM)
- • Faster token generation is the priority
- • You want the newer architecture and longer driver support lifecycle
- • You rely on CUDA-based tools (PyTorch, vLLM, Ollama)
Frequently asked questions
- Which is better for local AI, the AMD Instinct MI300X or NVIDIA H100 80GB?
- For local AI inference, the AMD Instinct MI300X has the edge. It offers 192 GB VRAM (vs 80 GB) and 5300 GB/s bandwidth (vs 3350 GB/s), letting it run 87 models natively in VRAM vs 72 for its rival.
- How much VRAM does the AMD Instinct MI300X have vs the NVIDIA H100 80GB?
- The AMD Instinct MI300X has 192 GB of HBM3 at 5300 GB/s. The NVIDIA H100 80GB has 80 GB of HBM3 at 3350 GB/s. The AMD Instinct MI300X has 112 GB more VRAM, allowing it to run 15 models the NVIDIA H100 80GB cannot fit natively.
- Can the AMD Instinct MI300X run Llama 3.3 70B?
- Yes. The AMD Instinct MI300X runs Llama 3.3 70B natively at BF16 quantization at approximately 11.1 tokens per second.
- Can the NVIDIA H100 80GB run Llama 3.3 70B?
- Yes. The NVIDIA H100 80GB runs Llama 3.3 70B natively at Q6_K quantization at approximately 20.7 tokens per second.
- What is the difference between the AMD Instinct MI300X and NVIDIA H100 80GB for AI?
- The key difference for AI inference is VRAM and memory bandwidth. The AMD Instinct MI300X has 192 GB VRAM at 5300 GB/s (ROCM backend). The NVIDIA H100 80GB has 80 GB VRAM at 3350 GB/s (CUDA backend). VRAM determines which models fit; bandwidth determines tokens per second. The AMD Instinct MI300X runs 87 models natively vs 72 for the NVIDIA H100 80GB.