GPU × use-case guide · Code assistant
Is the Instinct MI300X a good GPU for code assistant?
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. Code assistant workloads care most about low time-to-first-token and high single-stream tokens/sec, since developers wait on completions in real time. 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.
| Model | BF16 | FP8 | INT4 |
|---|---|---|---|
| Llama 3.1 8B | ✓ | ✓ | ✓ |
| Qwen 2.5 14B | ✓ | ✓ | ✓ |
| Gemma 2 27B | ✓ | ✓ | ✓ |
| Mixtral 8x7B (MoE) | ✓ | ✓ | ✓ |
| Llama 3.3 70B | ✓ | ✓ | ✓ |
| Qwen 2.5 72B | ✓ | ✓ | ✓ |
| Llama 3.1 405B | — | — | — |
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 code assistant, specifically
Code assistant 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's latency-sensitive, run it at low batch sizes on a fast framework (vLLM ≈ 85% MFU) rather than maximising batch. Size it precisely on the calculator.
Instinct MI300X pricing across providers
| Provider | On-demand $/hr | Reserved $/hr |
|---|---|---|
| fluidstack | $2.39 | — |
| lambda | $2.49 | — |
| tensordock | $2.69 | — |
| vast_ai | $2.79 | — |
| coreweave | $3.39 | $2.49 |
| runpod | $3.49 | — |
Verdict
With 192 GB, the Instinct MI300X is a data-center-class card that comfortably handles code assistant 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.
See full Instinct MI300Xspecs & pricing, size your model on the calculator, or compare every GPU on the GPU list.