DeepSeek: R1 Distill Llama 70B vs GPT-4o benchmark

Recommended Workload Routing

Frequently Asked Questions

Which is better overall, DeepSeek: R1 Distill Llama 70B or GPT-4o?

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, DeepSeek: R1 Distill Llama 70B or GPT-4o?

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?

DeepSeek: R1 Distill Llama 70B output tokens are $0.8/1M versus $10/1M. Input prices and retry rates still move the real bill.

Which is faster, DeepSeek: R1 Distill Llama 70B or GPT-4o?

We do not have TTFT for both models.

Which has the larger context window?

GPT-4o accepts 128k tokens versus 8k.

Can I self-host either model?

Neither model is marked open-weights here. You are comparing hosted APIs.

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. DeepSeek: R1 Distill Llama 70B and GPT-4o Elo cells are dated snapshots from the named source — we do not compute Arena ourselves.