UnifyBench

RankingEffort benchmarks

Command R 03 2024 effort benchmarks

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

Command R 03 2024

10 measured results · 1 reported effort labels · 5 benchmark/harness combinations. Model evidence and sources →

Capability score evidence

Command R 03 2024 · Non-reasoning: 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: 11 observations, 0 contributing, 0 matched without graph weight and 11 excluded. Counts do not establish rank eligibility.

    • 10 · Conflicting values for this configuration in the same evaluation
    • 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
    Command R 03 2024 · Non-reasoning capability radarComparison scores from 0 to 100. Unknown capabilities have no point; lines stop at gaps. Hollow points are preliminary. Exact values and support labels follow the chart.AgenticHard reasoningCodingHuman prefKnowledgeMultimodalLong context50100

    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 / sourceNon-reasoning
    GPQA DiamondArtificial Analysis · Artificial Analysis published evaluation; see source for benchmark-specific settings
    Benchmark details

    Independently benchmarked by Artificial Analysis · Evaluation results measured independently by Artificial Analysis

    Unit: percent. Source collected 2026-09-12.

    32.32%
    Reported settings

    Command-R+ (Apr '24); Reported effort: non-reasoning; Model source: https://artificialanalysis.ai/models/command-r-plus-04-2024; Mode from evaluator isReasoning metadata; effort budget not specified

    28.38%
    Reported settings

    Command-R (Mar '24); Reported effort: non-reasoning; Model source: https://artificialanalysis.ai/models/command-r-03-2024; Mode from evaluator isReasoning metadata; effort budget not specified

    Humanity's Last ExamArtificial Analysis · Artificial Analysis published evaluation; see source for benchmark-specific settings
    Benchmark details

    Independently benchmarked by Artificial Analysis · Evaluation results measured independently by Artificial Analysis

    Unit: percent. Source collected 2026-09-12.

    4.79%
    Reported settings

    Command-R (Mar '24); Reported effort: non-reasoning; Model source: https://artificialanalysis.ai/models/command-r-03-2024; Mode from evaluator isReasoning metadata; effort budget not specified

    4.63%
    Reported settings

    Command-R+ (Apr '24); Reported effort: non-reasoning; Model source: https://artificialanalysis.ai/models/command-r-plus-04-2024; Mode from evaluator isReasoning metadata; effort budget not specified

    LiveCodeBenchArtificial Analysis · Artificial Analysis published evaluation; see source for benchmark-specific settings
    Benchmark details

    Independently benchmarked by Artificial Analysis · Evaluation results measured independently by Artificial Analysis

    Unit: percent. Source collected 2026-09-12.

    4.76%
    Reported settings

    Command-R (Mar '24); Reported effort: non-reasoning; Model source: https://artificialanalysis.ai/models/command-r-03-2024; Mode from evaluator isReasoning metadata; effort budget not specified

    12.17%
    Reported settings

    Command-R+ (Apr '24); Reported effort: non-reasoning; Model source: https://artificialanalysis.ai/models/command-r-plus-04-2024; Mode from evaluator isReasoning metadata; effort budget not specified

    MATH-500Artificial Analysis · Artificial Analysis published evaluation; see source for benchmark-specific settings
    Benchmark details

    Independently benchmarked by Artificial Analysis · Evaluation results measured independently by Artificial Analysis

    Unit: percent. Source collected 2026-09-12.

    16.4%
    Reported settings

    Command-R (Mar '24); Reported effort: non-reasoning; Model source: https://artificialanalysis.ai/models/command-r-03-2024; Mode from evaluator isReasoning metadata; effort budget not specified

    27.87%
    Reported settings

    Command-R+ (Apr '24); Reported effort: non-reasoning; Model source: https://artificialanalysis.ai/models/command-r-plus-04-2024; Mode from evaluator isReasoning metadata; effort budget not specified

    MMLU-ProArtificial Analysis · Artificial Analysis published evaluation; see source for benchmark-specific settings
    Benchmark details

    Independently benchmarked by Artificial Analysis · Evaluation results measured independently by Artificial Analysis

    Unit: percent. Source collected 2026-09-12.

    43.18%
    Reported settings

    Command-R+ (Apr '24); Reported effort: non-reasoning; Model source: https://artificialanalysis.ai/models/command-r-plus-04-2024; Mode from evaluator isReasoning metadata; effort budget not specified

    33.84%
    Reported settings

    Command-R (Mar '24); Reported effort: non-reasoning; Model source: https://artificialanalysis.ai/models/command-r-03-2024; Mode from evaluator isReasoning metadata; effort budget not specified

    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