AMDCDNA 4

Best AI Models for AMD Instinct MI355X (288.0GB)

VRAM:288.0 GB HBM3e·Bandwidth:8000.0 GB/s·Stream Processors:16,384·TDP:1400W

Top-bin CDNA4, liquid-cooled 1400 W — datacenter/cloud only. Listed for comparison.

With 288 GB of memory, this is a high-end configuration for local AI. You can comfortably run most open-source LLMs including large 70B parameter models at good quantization levels, making it one of the best setups for serious local AI work.

At this memory tier, nearly every popular open-source model is within reach. You can run Llama 3 70B at Q4_K_M or even Q5_K_M quantization with room to spare, handle coding assistants like DeepSeek Coder 33B at high quality, and easily run any 7B–30B model at full or near-full precision. Context windows remain generous even with larger models, so multi-turn conversations and long-document processing work smoothly.

Runs Well

  • 70B models (Llama 3 70B, Qwen 72B) at Q4–Q5
  • 30B models at Q6–Q8 quality
  • 7B–14B models at full FP16 precision
  • Vision models (LLaVA, CogVLM) without compromise

Challenging

  • Mixture-of-experts models like Mixtral 8x22B at higher quants
  • 120B+ models still require lower quantizations

What LLMs Can AMD Instinct MI355X Run?

166 models · 133 excellent · 17 good

Showing compatibility for AMD Instinct MI355X

LLM models compatible with AMD Instinct MI355X — ranked by performance
ModelVRAMGrade
GPT OSS 120B120.4B
Q4_K_M·66.1 t/s tok/s·131K ctx·RUNS GREAT
72.7 GBS85
Q4_K_M·64.3 t/s tok/s·262K ctx·RUNS WELL
74.7 GBA84
Q4_K_M·56.4 t/s tok/s·66K ctx·RUNS WELL
85.1 GBA82
Q4_K_M·66.9 t/s tok/s·RUNS GREAT
71.7 GBS85
Q4_K_M·56.4 t/s tok/s·66K ctx·RUNS WELL
85.1 GBA82
GLM 4.5 Air110.5B
Q4_K_M·72.0 t/s tok/s·131K ctx·RUNS GREAT
66.7 GBS86
MiniMax M3427.0B
Q4_K_M·18.7 t/s tok/s·1049K ctx·DECENT
256.7 GBB46
GLM 5.2753.3B
IQ2_M·18.6 t/s tok/s·1049K ctx·BARELY RUNS
258.5 GBC44
Q4_K_M·103.1 t/s tok/s·131K ctx·RUNS GREAT
46.6 GBS92
Gemma 4 31B IT32.7B
Q4_K_M·226.1 t/s tok/s·262K ctx·RUNS GREAT
21.2 GBS100
BF16·66.1 t/s tok/s·262K ctx·RUNS GREAT
72.6 GBS85
Q4_K_M·103.1 t/s tok/s·131K ctx·RUNS GREAT
46.6 GBS92
Q4_K_M·107.6 t/s tok/s·33K ctx·RUNS GREAT
44.6 GBS92
Q4_K_M·97.6 t/s tok/s·262K ctx·RUNS GREAT
49.2 GBS91
Qwen3 32B32.8B
Q4_K_M·236.6 t/s tok/s·41K ctx·RUNS GREAT
20.3 GBS100
Q4_K_M·289.7 t/s tok/s·262K ctx·RUNS GREAT
16.6 GBS100

AMD Instinct MI355X Specifications

Brand
AMD
Architecture
CDNA 4
VRAM
288.0 GB HBM3e
Memory Bandwidth
8000.0 GB/s
Stream Processors
16,384
FP16 Performance
2517.00 TFLOPS
TDP
1400W
Release Date
2025-06-12

Get Started

Ollama (Recommended)

$curl -fsSL https://ollama.com/install.sh | sh
$ollama run llama3:8b

LM Studio

LM Studio

Download LM Studio, search for a model, and run it with one click.

Prompt Processing

Estimated for MiMo V2.5, the compute-bound phase that reads your prompt before the first reply token appears.

890.8tok/s prefill

Short chat

575 ms

512 tok prompt

Long chat

4.6 s

4,096 tok prompt

Document / codebase

36.8 s

32,768 tok prompt

Prefill is compute-bound and a different number from the decode tok/s shown elsewhere on this page — how prompt processing works →

Efficiency & Value

Based on MiMo V2.5 at ~25.7 tok/s decode.

Tokens per watt

0.02tok/s per W

Higher is better.

How efficiency & value are calculated →

Performance figures are estimates calibrated as of 2026-07-30 see calibration basis →

Frequently Asked Questions

Can AMD Instinct MI355X run GLM 4.5?

Yes, the AMD Instinct MI355X with 288 GB can run GLM 4.5, GLM 4.6, Llama 3.2 90B Vision Instruct, and 1764 other models. 1654 models run at excellent quality, and 74 at good quality. Check the compatibility table above for the full list with VRAM usage and estimated speed.

Is AMD Instinct MI355X good for AI?

The AMD Instinct MI355X has 288 GB of HBM3e, making it excellent for running local AI models. It supports 1728 models at good quality or better. With 8000.0 GB/s memory bandwidth, it delivers fast token generation speeds. This is an enthusiast-grade GPU that handles most popular open-source LLMs.

How many parameters can AMD Instinct MI355X handle?

With 288 GB, the AMD Instinct MI355X supports models from 3B to 70B+ parameters depending on quantization level. At Q4_K_M (the recommended sweet spot), you can fit roughly 480B parameters. This means 7B models at high quality (Q6/Q8) or 30B+ models at Q4.

What quantization should I use on AMD Instinct MI355X?

For the best balance of quality and speed on the AMD Instinct MI355X, start with Q4_K_M — it preserves ~85% of the original model quality while keeping VRAM usage reasonable. With 24+ GB, you have the headroom to run 7B models at Q5_K_M or even Q6_K for noticeably better output quality. For larger 30B models, Q4_K_M remains the sweet spot.

How fast is AMD Instinct MI355X for AI inference?

With 8000.0 GB/s memory bandwidth, the AMD Instinct MI355X achieves approximately 1067 tokens/sec on a 7B model at Q4_K_M — that's very fast, well above conversational speed. A 14B model runs at ~533 tok/s. Token generation speed scales inversely with model size — smaller models are significantly faster.

tok/s = (8000 GB/s ÷ model GB) × efficiency

Smaller models = faster inference. Memory bandwidth is the main bottleneck for token generation speed.

Estimated speed on AMD Instinct MI355X

~22 tok/s
~22 tok/s
~27 tok/s

Real-world results typically within ±20%. Speed depends on quantization kernel, batch size, and software stack.

Learn more about tok/s estimation →

What's the best model for AMD Instinct MI355X?

The top-rated models for the AMD Instinct MI355X are GLM 4.5, GLM 4.6, Llama 3.2 90B Vision Instruct. The best choice depends on your use case: coding assistants benefit from code-tuned models, while general chat works well with instruction-tuned models like Llama or Qwen.

What power supply and cooling does AMD Instinct MI355X need?

The AMD Instinct MI355X has a TDP of 1400 W. A good rule of thumb is to provide at least double the GPU's TDP to cover the rest of the system — that means a 1600 W PSU or larger. At this power level, a high-airflow case matters: aim for at least two front intake fans and one rear exhaust, with tidy cabling so hot air isn't trapped around the card. LLM inference sustains full GPU load continuously — longer and more consistently than most gaming workloads — so also make sure your CPU cooler can keep up under combined load.

Anything to watch out for with AMD Instinct MI355X?

Top-bin CDNA4, liquid-cooled 1400 W — datacenter/cloud only. Listed for comparison.