Llama-3.3-70B-Instruct vs Numa 1 in finance

Every finance benchmark where both have a score (Meta and Moneda). Data refreshed 2 Nov 2026.

Shared benchmarks
1
Llama-3.3-70B-Instruct only
0
Numa 1 only
6

Shared benchmarks, side by side

Each benchmark is drawn on its own scale. Bars are not comparable across rows.

  • Llama-3.3-70B-Instruct
  • Numa 1
  • FinanceQA accuracy (total, 0-1), higher is better

    Llama-3.3-70B-Instruct:0.311
    Numa 1:0.355 (better)
Benchmark
Llama-3.3-70B-Instruct
Numa 1

8 benchmarks, 1 scored for both. Bold marks the better score where both have one.

FinanceQAaccuracy (total, 0-1), higher is better
0.311
Paper Table 1 (Reported by the authors, 30 Jan 2025)
0.355
Moneda run, 2026-11-01 (Run by Moneda, 1 Nov 2026)
FinanceBench% correct, no filing given (150-question sample), higher is better
Not scored
67
Moneda run, 2026-11-02 (Run by Moneda, 2 Nov 2026)
FinSearchCompGlobal subset average accuracy %, higher is better
Not scored
59.4
Moneda run, 2026-11-01 (Run by Moneda, 1 Nov 2026)
FinSearchCompGreater China subset average accuracy %, higher is better
Not scored
57.1
Moneda run, 2026-11-01 (Run by Moneda, 1 Nov 2026)
Moneda CiteBenchFactual share of linked claims %, higher is better
Not scored
63.3
Moneda run, 2026-11-02 (Run by Moneda, 2 Nov 2026)
Moneda FilingsBench% correct (private split), higher is better
Not scored
91.6
Moneda run, 2026-11-02 (Run by Moneda, 2 Nov 2026)
Moneda PortfolioBenchPortfolio tasks, % correct, higher is better
Not scored
96
Moneda run, 2026-11-01 (Run by Moneda, 1 Nov 2026)
Finance Agent BenchmarkPartial credit % on the 27 public questions (run by Moneda; not comparable, unranked), higher is better
Not scored
80.2
Moneda run, 2026-10-09 (Run by Moneda, 9 Oct 2026)

Scores from different benchmarks use different scales and are not added up. Settings can differ between sources; see each leaderboard for details.