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Llama 3 2 Vision 11b Instruct
llama-3-2-vision-11b-instruct- Open weights
- Llama 3.2 licence
- Released 2024-09-25(curated)
- Best percentile
- 6.0Vision Arena
- Cohort standing
- 39.0median 38.2
Thin coverage — read with caution
This model appears on only 1 of 27 benchmark axes considered. The overall standing has been shrunk toward the neutral 50 to reflect the small sample, and no weaknesses have been claimed — a low percentile on 2 axes is a coverage artifact, not a measured weakness.
What the data says
Benchmarked on 1 of 27 tracked axes. Every figure below is the model's own published result on that board.
On only 1 board(s), a ranked list of strengths would be false authority — the per-axis figures are shown below instead, without a verdict.
- Vision Arena6 pct993Verify →
- OverallNot benchmarked
- WebDev ArenaNot benchmarked
- Factuality ArenaNot benchmarked
- Search ArenaNot benchmarked
- Document ArenaNot benchmarked
- Agent ArenaNot benchmarked
- GPQA DiamondNot benchmarked
- AIME (math)Not benchmarked
- FrontierMathNot benchmarked
- SimpleQA VerifiedNot benchmarked
- ARC-AGI-2Not benchmarked
- Humanity's Last ExamNot benchmarked
- SimpleBenchNot benchmarked
- LiveBenchNot benchmarked
- BFCL v4 (function calling)Not benchmarked
- SWE-bench Verified (live board)Not benchmarked
- Terminal-Bench 4.0Not benchmarked
- MMLU-Pro (Artificial Analysis)Not benchmarked
- LiveCodeBench (Artificial Analysis)Not benchmarked
- IFBench (Artificial Analysis)Not benchmarked
- HHEM Hallucination (Vectara)Not benchmarked
- SWE-bench VerifiedNot benchmarked
- Terminal-BenchNot benchmarked
- CodingNot benchmarked
- Instruction followingNot benchmarked
- Hard promptsNot benchmarked
Percentiles are the model's standing within each board's own population. Axes marked "not benchmarked" have no published result for this model — that is an absence of data, not a low score.
llama-3.2-vision-11b-instruct stands at 39 (raw mean 6) — measured on only 1 of 27 axes, so the standing is shrunk toward the neutral 50.
llama-3.2-vision-11b-instruct stands at 39 versus a cohort median of 38.2 across 134 models released within 180 days — above the peer median.
Every claim is a computed fact from the current board data, phrased by a low-temperature model call and rejected by a validation gate if any number is not in the source row. How the leaderboards work →