GPU × use-case guide · Summarisation

Is the Instinct MI300X a good GPU for summarisation?

The Instinct MI300X is a cdna3 AMD GPU with 192 GB HBM3 (5300 GB/s), 1307 TFLOPS BF16 / 2614 TFLOPS FP8, and a 750 W TDP. Summarisation workloads care most about large context windows and batch throughput — documents are long and jobs run offline, so cost-per-token beats latency. Here's how the Instinct MI300X measures up.

What models fit on a single Instinct MI300X?

Weights only, reserving ~25% of the 192 GB for KV cache, activations and fragmentation. ✓ = fits on one card.

Largest single-card fit: Qwen 2.5 72B at BF16, Qwen 2.5 72B at FP8, Qwen 2.5 72B at INT4. Bigger models need tensor-parallel across 8 cards.

Instinct MI300X for summarisation, specifically

Summarisation is context-heavy, so the KV cache — not the weights — is what fills the 192 GB. On the Instinct MI300X you'll trade context length against batch size: long prompts mean fewer concurrent requests. Because it runs offline, batch aggressively to push tokens-per-dollar down. Size it precisely on the calculator.

Instinct MI300X pricing across providers

Verdict

With 192 GB, the Instinct MI300X is a data-center-class card that comfortably handles summarisation for models up to Qwen 2.5 72B at full precision on a single card — a strong pick if your budget supports ~$2.39/hr.