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Llama 3.1-70B

19 benchmarks · 22 observations · 17 sources · released 2024-07-23

Scores at a glance

19 benchmarks · large dot: Llama 3.1-70B; small dots: closest models where reported

GPQA Diamond ↗44.19%
9.2896.4

Llama 3.1-70B · GPQA diamond · Best score (across scorers) · % ↗

MATH Level 5 ↗36.68%
3.2998.13

Llama 3.1-70B · MATH level 5 · Best score (across scorers) · % ↗

BALROG ↗27.9%
3.768.3

Llama 3.1-70B · Balrog · Average progress · % ↗

MMLU ↗80.1%
29.587.3

Llama 3.1-70B · MMLU · EM · % ↗

LMCA ↗14.85%
2.7868.26

Llama 3.1-70B · LMCA · Score · % ↗

Fortress ↗44.18%
5.7874.39

Llama 3.1 70B · Scale Labs · Risk elicitation score ↗

ZebraLogic ↗24.9%
6.481

Llama-3.1-70B · ZebraLogic · Grid-level accuracy · complete puzzles ↗

InfiniteBench ↗35.1 points
1.960.3

Llama-3.1-70B · InfiniteBench · InfiniteBench aggregate · HELMET paper · original-author harness ↗

HumanEval ↗80.5%
71.599.3

Llama 3.1 70b · HumanEval · Pass@1 · OpenAI Simple Evals · archived July 2025 ↗

Closest models by score

Similar positions on shared benchmark leaderboards. Smaller gaps are closer.

2.8 percentile-point gap

3 of 4 shared benchmark comparisons

How similarity is measured

Mean absolute gap in percentile positions on shared benchmark settings; lower is closer. At least 60% overlap is required, with a minimum of three when available. Independent evaluations are used when there are at least three; otherwise published report comparisons are used. Repeated model observations within one setting are averaged before ranking. Writing-style traits and composite indices are excluded. This describes similarity, not an overall quality ranking.

Filter comparisons to this model →

Sources

Every plotted observation links to its evaluation. Reported configurations, benchmark versions and task subsets can differ; similarity describes shared scores, not training lift.

  1. HELMET: How to Evaluate Long-Context Language Models Effectively and Thoroughly — published result table ↗

    Howard Yen, Tianyu Gao, Minmin Hou, Ke Ding, Daniel Fleischer, Peter Izsak et al. · 2024

    All 8 authors

    Howard Yen, Tianyu Gao, Minmin Hou, Ke Ding, Daniel Fleischer, Peter Izsak, Moshe Wasserblat, Danqi Chen

  2. HARP: A challenging human-annotated math reasoning benchmark — published result table ↗

    Yue, Albert S., Madaan, Lovish, Moskovitz, Ted, Strouse, DJ, Singh, Aaditya K. · 2024

  3. ZebraLogic: On the Scaling Limits of LLMs for Logical Reasoning — published result table ↗

    Bill Yuchen Lin, Ronan Le Bras, Kyle Richardson, Ashish Sabharwal, Radha Poovendran, Peter Clark et al. · 2025

    All 7 authors

    Bill Yuchen Lin, Ronan Le Bras, Kyle Richardson, Ashish Sabharwal, Radha Poovendran, Peter Clark, Yejin Choi

  4. Putnam-AXIOM: A Functional and Static Benchmark for Measuring Higher Level Mathematical Reasoning in LLMs — published result table ↗

    Gulati, Aryan, Miranda, Brando, Chen, Eric, Xia, Emily, Fronsdal, Kai, Dumont, Bruno et al. · 2025

    All 8 authors

    Gulati, Aryan, Miranda, Brando, Chen, Eric, Xia, Emily, Fronsdal, Kai, Dumont, Bruno, Obbad, Elyas, Koyejo, Sanmi

  5. TasteVal: Measuring the Experimental Research Taste of AI Systems Against Human Experts — published result table ↗

    Jaffe, Oliver, Sherburn, Dane · 2026

  6. BALROG: Benchmarking Agentic LLM and VLM Reasoning On Games ↗

    Paglieri, Davide, Cupiał, Bartłomiej, Coward, Samuel, Piterbarg, Ulyana, Wolczyk, Maciej, Khan, Akbir et al. · 2024

    All 13 authors

    Paglieri, Davide, Cupiał, Bartłomiej, Coward, Samuel, Piterbarg, Ulyana, Wolczyk, Maciej, Khan, Akbir, Pignatelli, Eduardo, Kuciński, Łukasz, Pinto, Lerrel, Fergus, Rob, Foerster, Jakob Nicolaus, Parker-Holder, Jack, Rocktäschel, Tim

  7. DTBench — Conceptual Reasoning Index ↗

    Conceptual Reasoning Index

  8. LMCA — Conceptual Reasoning Index ↗

    Conceptual Reasoning Index

  9. Holistic Evaluation of Language Models (HELM) ↗

    Stanford Center for Research on Foundation Models

  10. GPQA Diamond ↗

    Epoch AI

  11. MATH Level 5 ↗

    Epoch AI

  12. OTIS Mock AIME 2024-2025 ↗

    Epoch AI

  13. The Agent Company ↗

    Epoch AI

  14. AI benchmarks & capabilities ↗

    Epoch AI

  15. WeirdML ↗

    Håvard Tveit Ihle

  16. Scale Labs — evaluation methodology and results ↗

    Scale Labs / SEAL · 2026

  17. Simple Evals — model benchmark results ↗

    OpenAI · 2025

Names used in source tables

Llama 3.1 70B · Llama 3.1 70b · Llama 3.1-70B · Llama-3.1-70B · Meta Llama 3.1-70B