LLMs TigerLive LLM benchmarks

Gemma 2 9B: benchmark scores, price and ranking

Gemma 2 9B from Google DeepMind ranks #515 of 743 LLMs on the LLMs Tiger aggregate benchmark score (46.5), based on 2 benchmark results captured up to 2026-10-13.

Organisation
Google DeepMind
Type
Open-weight / local model
Open weights
Yes
Released
2024-06-24 (source: epoch)
Cheapest API price
$0.200 in / $0.200 out per million tokens (via vercel_ai_gateway, observed 2026-10-13T20:47Z)
Aggregate rank
#515 of 743 (score 46.5)

Across the 2 benchmarks where at least ten models are scored, Gemma 2 9B is in the top 10% on 0 and in the top half on 0.

Its cheapest listed input price, $0.200 per million tokens, is lower than that of 67% of the 427 models with a listed price.

Gemma 2 9B benchmark results

Gemma 2 9B benchmark scores, ranked against all models measured on each benchmark
BenchmarkScoreRankSourceCaptured
Epoch ECI120#128 of 204Epoch AI Benchmarking Hub2026-10-13
MMLU-Pro45.1%#87 of 136HuggingFace MMLU-Pro leaderboard2026-10-13

About Gemma 2 9B

Gemma 2 9B is an open-weight model that can run on your own hardware from Google DeepMind. It was released on 2024-06-24, according to Epoch AI. The cheapest API listing we track charges $0.200 per million input tokens and $0.200 per million output tokens, through vercel_ai_gateway. We hold 2 benchmark results for it across 2 areas, and none is in the top tenth of its board.

Where Gemma 2 9B stands

On our aggregate score, Gemma 2 9B is #515 of 743 ranked models, in the lower half. Its score is 46.5; the scale is centred on 50, so it sits 3.5 points below the typical model. That beats 31% of the ranked field. Among the 41 ranked Google DeepMind models it is #25. The next one up is gemini-2.0-flash-lite at 46.6. The next one down is gemini-2.5-flash at 45.6.

Gemma 2 9B, benchmark by benchmark

Gemma 2 9B lands below the middle on Epoch ECI: 120, #128 of 204, with 62% of the field scoring higher. Qwen 3.8 Max leads at 156; the closest result above is Claude 2 at 120. It covers Epoch Capabilities Index: Epoch's own aggregate of ~40 benchmarks. The board median is 127, so Gemma 2 9B is 7 points below it. Source: Epoch AI Benchmarking Hub, captured 2026-10-13.

Gemma 2 9B lands below the middle on MMLU-Pro: 45.1%, #87 of 136, with 63% of the field scoring higher. Darwin-180B-RSI leads at 88.1%; the closest result above is aya-expanse-32b at 45.4%. It covers 57-subject knowledge + reasoning. The board median is 55.3%, so Gemma 2 9B is 10.2 points below it. Source: HuggingFace MMLU-Pro leaderboard, captured 2026-10-13.

Strengths and weaknesses

Gemma 2 9B has too few results on boards with ten or more models to say where it is strong or weak. Treat any single score as a data point, not a verdict.

Price and value

The median input price across the 427 priced models is $0.500 per million tokens, so Gemma 2 9B costs less than the typical listing. Models that score within 1.5 points or better and cost less: Qwen2.5-Coder-7B-Instruct ($0.010, 49.5), DeepSeek V4.1 Flash (high) ($0.010, 48.9), Qwen2.5-Coder-3B-Instruct ($0.010, 46.5). Similar scores cost more on MiniMax-M3 ($0.230) and gemini-3.1-flash-lite (high) ($0.250).

Release history

The Google DeepMind model released before it was gemma-2-27b-it on 2024-06-24, which scores 43.8. The next one was gemma-2-9b-it on 2024-06-24, at 43.0.

Reading these numbers

The 2 scores on this page come from 2 sources: Epoch AI Benchmarking Hub (1), HuggingFace MMLU-Pro leaderboard (1). No official leaderboard supplied any of them, so treat them as third-party measurements. With 2 results the aggregate rank can move a lot when one new score arrives.

Models ranked nearby

More from Google DeepMind

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