Llama 3.3 70B vs Qwen3.8 27B benchmark

Side-by-Side Benchmark Matrix

Recommended Workload Routing

Frequently Asked Questions

Which is better overall, Llama 3.3 70B or Qwen3.8 27B?

Qwen3.8 27B has the higher preference Elo in our latest snapshot (1,398). “Better” still depends on coding, price, and latency — see the table.

Which is better at coding, Llama 3.3 70B or Qwen3.8 27B?

Qwen3.8 27B leads SWE-bench at 58.8% vs 45.1%. SWE-bench is one harness, not your repo.

Which is cheaper to run in production?

Qwen3.8 27B output tokens are $0.4/1M versus $0.59/1M. Input prices and retry rates still move the real bill.

Which is faster, Llama 3.3 70B or Qwen3.8 27B?

Qwen3.8 27B has the lower time-to-first-token (140 ms vs 160 ms). Tokens/sec is a separate column if you care about long completions.

Which has the larger context window?

Qwen3.8 27B accepts 131k tokens versus 128k.

Can I self-host either model?

Both Llama 3.3 70B and Qwen3.8 27B are marked open-weights. Hosting cost is not in this table.

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 Qwen3.8 27B Elo cells are dated snapshots from the named source — we do not compute Arena ourselves.