RankingEffort benchmarks

Llama-3.1-405B-Instruct effort benchmarks

Compare measured Low, Medium, High and other settings. Every number keeps its source.

Model

Llama-3.1-405B-Instruct

2 measured results · 1 reported effort labels · 2 benchmark/harness combinations. Model evidence and sources →

Capability score evidence

Llama-3.1-405B-Instruct · Unspecified: No connected estimate. No admitted path to the complete configuration reference panel

Which sources carry the weight?

These shares describe the comparisons entering the fit, not fractions of the final score.

This configuration did not qualify for the dated stability audit.

What evidence is missing from the fit?

Across all collected settings for this model: 3 observations, 0 contributing, 0 matched without graph weight and 3 excluded. Counts do not establish rank eligibility.

2 · Effort is not identified
1 · No reviewed effort for this catalog observation; any separately collected effort measurement is counted separately

Inspect every observation and exclusion →

Capability profile

One configuration, seven capabilities

Comparison score · 0–100

ALlama-3.1-405B-Instruct · Unspecified0 of 7 capabilities supported

Gaps are unknown, not zero. Hollow points are preliminary.

Agentic
Unknown
Hard reasoning
Unknown
Coding
Unknown
Human pref
Unknown
Knowledge
Unknown
Multimodal
Unknown
Long context
Unknown

Each profile belongs to the named configuration. Capability scores use a shared panel for all axes, distinct from the overall ranking panel; they are not accuracy percentages or direct head-to-head wins.

Compare this configuration →Explore the model evidence profile →

These are published benchmark scores. Supported effort estimates also appear on the Capability leaderboard. Results from different harnesses occupy different rows. Missing cells stay unknown; no scores are copied between effort levels.

Benchmark / source	Unspecified
Epoch · GPQA diamond · v1.0.0Epoch AI · Epoch AI Inspect; task 1.0.0; scorer choice Benchmark details Epoch AI internal evaluation. Mean accuracy under the published setting; exact task version and scorer stay separate. Related tasks share a family budget. Data by Epoch AI, CC BY. Unit: percent. Source collected 2026-09-12.	50.92% Reported settings Epoch AI Inspect; task 1.0.0; scorer choice; model=Llama-3.1-405B-Instruct; run=S5QYXSvQBRSbUbXSnAGbMm; mean accuracy; https://epoch.ai/data/benchmarks.csv
Epoch · OTIS Mock AIME 2024-2025 · v1.0.0Epoch AI · Epoch AI Inspect; task 1.0.0; scorer model_graded Benchmark details Epoch AI internal evaluation. Mean accuracy under the published setting; exact task version and scorer stay separate. Related tasks share a family budget. Data by Epoch AI, CC BY. Unit: percent. Source collected 2026-09-12.	9.72% Reported settings Epoch AI Inspect; task 1.0.0; scorer model_graded; model=Llama-3.1-405B-Instruct; run=2fQJP3brRApfBdQq7Zy3bm; mean accuracy; https://epoch.ai/data/benchmarks.csv

What these comparisons mean

Each source reports its own effort labels. Matching labels do not establish equal compute budgets or identical fallback behavior. Open Reported settings to inspect the exact model name, agent and task coverage. Multiple results at one level remain visible rather than selecting the best. Source-reported None or Non-reasoning labels are not treated as evidence that an API supports those settings.

These measurements use their own dated source collection. The leaderboard fits identified configurations jointly; it contains no pooled model ratings. Explicit thinking budgets are separate configurations. Read the methodology.

Download all effort benchmark results · 7,424 results across 240 models · Collected 2026-09-12

Llama-3.1-405B-Instruct effort benchmarks