PaLM 2-L: benchmark scores, price and ranking

PaLM 2-L from Google is a recent or sparsely tested model with 1 benchmark result on record; it has not been measured on enough benchmarks shared with other models to receive an aggregate rank. This page lists every score we have, based on 1 benchmark results captured up to 2026-10-14.

Organisation
Google
Type
Frontier model
Open weights
No
Released
2023-05-17 (source: epoch)
Aggregate rank
Not ranked yet (too few shared benchmarks)

Across the 1 benchmark where at least ten models are scored, PaLM 2-L is in the top 10% on 0 and in the top half on 0.

PaLM 2-L benchmark results

PaLM 2-L benchmark scores, ranked against all models measured on each benchmark
BenchmarkScoreRankSourceCaptured
Epoch ECI115#147 of 204Epoch AI Benchmarking Hub2026-10-14

About PaLM 2-L

PaLM 2-L is a frontier model from Google. It was released on 2023-05-17, according to Epoch AI. No API price is listed for it yet. We hold 1 benchmark result for it across 1 area, and none is in the top tenth of its board.

Where PaLM 2-L stands

PaLM 2-L has 1 result so far and shares too few benchmarks with other models to get an aggregate rank. The rank will appear on its own once more scores are published.

PaLM 2-L, benchmark by benchmark

PaLM 2-L lands below the middle on Epoch ECI: 115, #147 of 204, with 72% of the field scoring higher. Qwen 3.8 Max leads at 156; the closest result above is GPT-3.5 Turbo (Jan 2024) at 116. It covers Epoch Capabilities Index: Epoch's own aggregate of ~40 benchmarks. The board median is 127, so PaLM 2-L is 12 points below it. Source: Epoch AI Benchmarking Hub, captured 2026-10-14.

Release history

The next one was Gemini 1.5 Pro on 2024-02-15, at 47.5.

Reading these numbers

The 1 score on this page comes from 1 source: Epoch AI Benchmarking Hub (1). No official leaderboard supplied any of them, so treat them as third-party measurements. With 1 results the aggregate rank can move a lot when one new score arrives.

More from Google

Compare it on the live leaderboard → · How the aggregate score works