Model comparison
Gemma 3 27B vs Mercury 2
Mercury 2 is the stronger model overall, scoring 39.1 to 30.8 on the Noometry Index. Gemma 3 27B costs 3.8× less per token, which makes it the better buy when Mercury 2's lead doesn't matter for your workload.
Last verified . 14 shared benchmarks.
GoogleSummary
- They share 14 benchmarks with published results for both. Gemma 3 27B scores higher in 2 categories and Mercury 2 in 5 categories; 5 gaps are clear of the uncertainty.
- The widest gap is in long context, where Mercury 2 leads 40.5 to 27.6.
- The biggest single-benchmark swing is SciCode: 21.2% for Gemma 3 27B and 38.7% for Mercury 2.
- Gemma 3 27B is cheaper at $0.08 / $0.16 per million input/output tokens, against $0.25 / $0.75 for Mercury 2.
- Gemma 3 27B accepts more context: 131K tokens versus 128K.
- Gemma 3 27B has downloadable open weights; the other is API-only.
Side by side
| Gemma 3 27B | Mercury 2 | |
|---|---|---|
| Provider | Inception | |
| Noometry Index | 30.8 | 39.1 |
| Released | 2025-03-11 | 2026-02-20 |
| Weights | Open | Proprietary |
| Context window | 131K | 128K |
| Max output | 8K | 50K |
| Input $ / M tokens | $0.08 | $0.25 |
| Output $ / M tokens | $0.16 | $0.75 |
| Results tracked | 43 | 17 |
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Category by category
Coding Mercury 2 leads
Gemma 3 27B: 22.5 (#334), Mercury 2: 33.5 (#255)
| Benchmark | Gemma 3 27B | Mercury 2 |
|---|---|---|
| SciCode | 21.2% | 38.7% |
| LMArena Coding | 1322 | 1391 |
| Aider Polyglot | 4.9% | — |
| LMArena WebDev | — | 1171 |
| WeirdML | — | 43.2% |
| LiveBench Coding | 39.9% | — |
| ALE-Bench | — | 785.58 |
Agentic & Tool Use Not comparable
Gemma 3 27B: 25.1 (#110), Mercury 2: —
| Benchmark | Gemma 3 27B | Mercury 2 |
|---|---|---|
| Berkeley Function Calling Leaderboard | 29.5% | — |
Reasoning Mercury 2 leads
Gemma 3 27B: 16.7 (#301), Mercury 2: 23.8 (#170)
| Benchmark | Gemma 3 27B | Mercury 2 |
|---|---|---|
| CritPt | 0% | 0.8% |
| LMArena Hard Prompts | 1340 | 1362 |
| Kagi LLM Benchmark | 40.4% | — |
| Chess Puzzles | 0% | — |
| LiveBench Reasoning | 43.8% | — |
| DTBench | 52.5% | — |
| LiveBench Data Analysis | 51.5% | — |
| LMCA | 12.3% | — |
| Epoch Capabilities Index | 130.04 | — |
| LiveBench | 50% | — |
Math Not comparable
Gemma 3 27B: 25.9 (#265), Mercury 2: —
| Benchmark | Gemma 3 27B | Mercury 2 |
|---|---|---|
| OTIS Mock AIME 2024-2025 | 22.5% | — |
| LiveBench Math | 55.4% | — |
| LMArena Math | 1312 | — |
| MATH Level 5 | 74% | — |
Knowledge Mercury 2 leads
Gemma 3 27B: 25.5 (#261), Mercury 2: 36.2 (#172)
| Benchmark | Gemma 3 27B | Mercury 2 |
|---|---|---|
| Vectara Hallucination Rate | 7.4% | 12.3% |
| LMArena Expert | 1304 | 1358 |
| GPQA Diamond | 47.7% | — |
| Confabulations | 40.3% | — |
Multimodal Not comparable
Gemma 3 27B: 32.6 (#100), Mercury 2: —
| Benchmark | Gemma 3 27B | Mercury 2 |
|---|---|---|
| LMArena Vision | 1164 | — |
| GeoBench | 52% | — |
Multilingual Too close to call
Gemma 3 27B: 46.9 (#155), Mercury 2: 46.6 (#157)
| Benchmark | Gemma 3 27B | Mercury 2 |
|---|---|---|
| LMArena Non-English | 1334 | 1331 |
| LMArena Chinese | 1346 | 1417 |
| LMArena Russian | 1349 | 1304 |
| LMArena French | 1368 | — |
| LMArena German | 1362 | — |
| LMArena Japanese | 1287 | — |
| LMArena Korean | 1308 | — |
| LMArena Spanish | 1349 | — |
Instruction Following Too close to call
Gemma 3 27B: 70.6 (#160), Mercury 2: 70.2 (#165)
| Benchmark | Gemma 3 27B | Mercury 2 |
|---|---|---|
| LMArena Instruction Following | 1321 | 1329 |
| LiveBench Instruction Following | 74.9% | — |
Long Context Mercury 2 leads
Gemma 3 27B: 27.6 (#293), Mercury 2: 40.5 (#154)
| Benchmark | Gemma 3 27B | Mercury 2 |
|---|---|---|
| LMArena Longer Query | 1333 | 1330 |
| Fiction.LiveBench | 33.3% | — |
Writing & Preference Mercury 2 leads
Gemma 3 27B: 52.5 (#168), Mercury 2: 53.8 (#155)
| Benchmark | Gemma 3 27B | Mercury 2 |
|---|---|---|
| LMArena Text | 1358 | 1355 |
| LMArena Creative Writing | 1346 | 1289 |
| LMArena Multi-Turn | 1345 | 1358 |
| Short-Story Creative Writing | 79.9% | — |
| EQ-Bench Creative Writing | 1266 | — |
| LiveBench Language | 34.6% | — |
Frequently asked questions
Is Gemma 3 27B better than Mercury 2?
Mercury 2 is the stronger model overall, scoring 39.1 to 30.8 on the Noometry Index. Gemma 3 27B costs 3.8× less per token, which makes it the better buy when Mercury 2's lead doesn't matter for your workload.
Which is cheaper, Gemma 3 27B or Mercury 2?
Gemma 3 27B is cheaper. It lists at $0.08 per million input tokens and $0.16 per million output tokens; Mercury 2 lists at $0.25 and $0.75.
Is Gemma 3 27B or Mercury 2 better for coding?
Mercury 2 scores higher on coding benchmarks: 33.5 versus 22.5 in the Noometry coding category.
Which has the bigger context window?
Gemma 3 27B does, with 131K tokens against 128K.
How many benchmarks do Gemma 3 27B and Mercury 2 share?
14 benchmarks have published results for both models. Gemma 3 27B has 43 scored results on Noometry and Mercury 2 has 17.