What it costs to run Llama 3.3 70B Instruct
70.6B paramsllama3.3
We don't yet have the layer/attention shape for this model — its repository is licence-gated, so the KV-cache figures below can't be computed. Weight sizes are still accurate.
How these numbers are produced
- Model shape comes from the model's own config.json.
- Weight size is parameters × effective bits-per-weight. Those constants are checked against real published quantised file sizes — median error 0.7% across 40 measurements.
- KV cache is 2 × layers × KV-heads × head-dim × context × 2 bytes. Using KV-heads rather than attention heads is what makes this correct for grouped-query attention; treating a GQA model as multi-head overstates the cache by up to 8×.
- Tokens/sec is an estimate, not a benchmark. Generation is memory-bandwidth-bound, so this is bandwidth ÷ weight-bytes derated to 75%. Real throughput depends on your runtime, batch size and kernels. We don't run our own hardware tests — see our editorial policy.
- Rental prices are pulled hourly from provider APIs (last updated Tue, 21 Jul 2026 15:20:05 GMT). Spot/interruptible pricing can change or vanish without notice.