Claude 3.5 Haiku vs Llama 3.1 405B benchmark

Side-by-Side Benchmark Matrix

Recommended Workload Routing

Frequently Asked Questions

Which is better overall, Claude 3.5 Haiku or Llama 3.1 405B?

Llama 3.1 405B has the higher preference Elo in our latest snapshot (1,370). “Better” still depends on coding, price, and latency — see the table.

Which is better at coding, Claude 3.5 Haiku or Llama 3.1 405B?

Llama 3.1 405B leads SWE-bench at 58.4% vs 36.2%. SWE-bench is one harness, not your repo.

Which is cheaper to run in production?

Llama 3.1 405B output tokens are $3.5/1M versus $4/1M. Input prices and retry rates still move the real bill.

Which is faster, Claude 3.5 Haiku or Llama 3.1 405B?

Claude 3.5 Haiku has the lower time-to-first-token (110 ms vs 360 ms). Tokens/sec is a separate column if you care about long completions.

Which has the larger context window?

Claude 3.5 Haiku accepts 200k tokens versus 128k.

Can I self-host either model?

Llama 3.1 405B 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. Claude 3.5 Haiku and Llama 3.1 405B Elo cells are dated snapshots from the named source — we do not compute Arena ourselves.