Llama 3.3 70B vs OpenAI: o3 benchmark

Side-by-Side Benchmark Matrix

Recommended Workload Routing

Frequently Asked Questions

Which is better overall, Llama 3.3 70B or OpenAI: o3?

We do not have preference Elo for both models, so we do not declare an overall winner. Compare the metrics that exist.

Which is better at coding, Llama 3.3 70B or OpenAI: o3?

SWE-bench is missing for at least one model, so we do not rank coding from a single number.

Which is cheaper to run in production?

Llama 3.3 70B output tokens are $0.32/1M versus $8/1M. Input prices and retry rates still move the real bill.

Which is faster, Llama 3.3 70B or OpenAI: o3?

We do not have TTFT for both models.

Which has the larger context window?

OpenAI: o3 accepts 200k tokens versus 131k.

Can I self-host either model?

Llama 3.3 70B is marked open-weights in our catalog. The other side is a closed API. Check the provider license before you ship weights.

Are these scores from CompareLLM’s own evals?

No. V1 aggregates public leaderboards (and optional first-party latency pings). Each cell names its source and date. Read /methodology.

What does preference Elo mean on this page?

Preference Elo is a crowd vote from LMArena / Arena. People see two hidden answers and pick the one they like more. The model that wins more often gets a higher Elo. That means people preferred it — not that it passed a school test. It is not SWE-bench, not accuracy, and not a number we invent. Llama 3.3 70B and OpenAI: o3 Elo cells are dated snapshots from the named source — we do not compute Arena ourselves.