Gemma 3 12B vs Mercury 2
Mercury 2 leads Gemma 3 12B on the Artificial Analysis Intelligence Index, 10.8 to 3.8, and Gemma 3 12B costs 4.6x less per output token ($0.1625 vs $0.75 per million). Updated October 22, 2026; 28 benchmarks have a result for both.
Gemma 3 12B or Mercury 2: which to pick
Neither model has a coding score yet, so the two cannot be ranked on coding.
Pick Gemma 3 12B for output tokens 4.6x cheaper ($0.1625 vs $0.75 per million) and a larger context window (131K against 128K tokens).
- Shared results
- 28
- Gemma 3 12B only
- 15
- Mercury 2 only
- 14
- Like-for-like categories
- 6 of 9
Only benchmarks that tested both models count toward a pick; a result only one model has is shown but not compared.
Which one for your work
Each card is decided by one number both models carry. Where only one has it, the card says so and makes no call.
Coding
Vibe Coding Index, six public coding benchmarks
No call
Neither has a coding score yet.
One side not measured
Intelligence
AA Intelligence Index
Mercury 2
Mercury 2 leads, 10.8 against 3.8.
Same board, both measured
Agentic work
AA Agentic Index
Mercury 2
Mercury 2 leads, 1.6 against 0.1.
Same board, both measured
Web design
Design Arena: websites
No call
Only Mercury 2 has a Design Arena: websites result, 1036.
Directional only
Long documents
Listed context window
Gemma 3 12B
Gemma 3 12B takes 131K tokens against 128K.
Listed by OpenRouter
Everyday cost
1K input + 500 output tokens
Gemma 3 12B
Gemma 3 12B $0.0002, Mercury 2 $0.0006 per turn.
List prices
At a glance
- Coding index
- Gemma 3 12B not benchmarked, Mercury 2 not benchmarked.
- Widest category
- Agentic work, 30.7 points apart on average over 2 shared benchmarks.
- Widest single gap
- τ²-Bench Telecom: Gemma 3 12B 10.8% against Mercury 2 70.8%, 59.9 points apart on a 0 to 100 scale.
- Output price
- Gemma 3 12B $0.1625 against Mercury 2 $0.75 per million output tokens, 4.6x apart.
- Context window
- Gemma 3 12B takes 131K tokens, Mercury 2 128K.
Benchmark by benchmark
First the score: boards each model leads, per category, where both have a result. Then every board, a category to a fold; bars are each result on a 0 to 100 scale, so compare the two in a row, not one row with another.
| Category | Gemma 3 12B | Bars | Mercury 2 | Ties |
|---|---|---|---|---|
| Coding | 0 | 5 | ||
| Intelligence | 0 | 1 | ||
| Agentic work | 0 | 2 | ||
| Reasoning | 0 | 5 | ||
| Knowledge | 2 | 1 | ||
| General | 3 | 9 | ||
| All shared boards | 5 | 23 |
CodingLike-for-likeSix of these boards feed the Vibe Coding Index05
| Benchmark | Gemma 3 12B | Mercury 2 | Leader |
|---|---|---|---|
| LMArena WebDev | Not measured | 1171 | Only Mercury 2 measured |
| AA Coding Index | 5.8 | 31.1 | Mercury 2 |
| LiveCodeBench (Artificial Analysis run) | 13.7% | Not measured | Only Gemma 3 12B measured |
| SciCode | 16.4% | 37.7% | Mercury 2 |
| Terminal-Bench Hard (Artificial Analysis run) | 0.8% | 26.5% | Mercury 2 |
| WeirdML | Not measured | 43.2% | Only Mercury 2 measured |
| ALE-Bench | Not measured | 785.6 | Only Mercury 2 measured |
| LMArena Text: coding | 1281 | 1390 | Mercury 2 |
| LMArena Text: software and IT | 1313 | 1385 | Mercury 2 |
| LMArena WebDev: React | Not measured | 1160 | Only Mercury 2 measured |
| LMArena WebDev: HTML | Not measured | 1199 | Only Mercury 2 measured |
| SciCode | 0.0% | Not measured | Only Gemma 3 12B measured |
| Neither model has a result on the other 27 boards here | |||
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index01
| Benchmark | Gemma 3 12B | Mercury 2 | Leader |
|---|---|---|---|
| AA Intelligence Index | 3.8 | 10.8 | Mercury 2 |
| Epoch Capabilities Index | 123.5 | Not measured | Only Gemma 3 12B measured |
Agentic workLike-for-likePublic boards, shown as published, kept out of the index02
| Benchmark | Gemma 3 12B | Mercury 2 | Leader |
|---|---|---|---|
| AA Agentic Index | 0.1 | 1.6 | Mercury 2 |
| τ²-Bench Telecom | 10.8% | 70.8% | Mercury 2 |
| Berkeley Function Calling Leaderboard (BFCL) | 30.4% | Not measured | Only Gemma 3 12B measured |
| Neither model has a result on the other 38 boards here | |||
ReasoningLike-for-likePublic boards, shown as published, kept out of the index05
| Benchmark | Gemma 3 12B | Mercury 2 | Leader |
|---|---|---|---|
| GPQA Diamond (Artificial Analysis run) | 34.9% | 77.0% | Mercury 2 |
| Humanity's Last Exam (Artificial Analysis run) | 4.2% | 17.1% | Mercury 2 |
| GPQA Diamond (Epoch AI run) | 39.5% | Not measured | Only Gemma 3 12B measured |
| LMArena Text: hard prompts | 1309 | 1362 | Mercury 2 |
| LMArena Text: expert | 1248 | 1358 | Mercury 2 |
| LMArena Text: hard prompts in English | 1318 | 1374 | Mercury 2 |
| Neither model has a result on the other 16 boards here | |||
MathDirectional onlyPublic boards, shown as published, kept out of the index5 boards, none shared
| Benchmark | Gemma 3 12B | Mercury 2 | Leader |
|---|---|---|---|
| AA Math Index | 18.3 | Not measured | Only Gemma 3 12B measured |
| AIME 2025 (Artificial Analysis run) | 18.3% | Not measured | Only Gemma 3 12B measured |
| OTIS Mock AIME | 16.7% | Not measured | Only Gemma 3 12B measured |
| LMArena Text: math | 1307 | Not measured | Only Gemma 3 12B measured |
| LMArena Text: mathematical work | 1336 | Not measured | Only Gemma 3 12B measured |
| Neither model has a result on the other 8 boards here | |||
KnowledgeLike-for-likePublic boards, shown as published, kept out of the index21
| Benchmark | Gemma 3 12B | Mercury 2 | Leader |
|---|---|---|---|
| MMLU Pro (Artificial Analysis run) | 59.5% | Not measured | Only Gemma 3 12B measured |
| LMArena Text: science | 1366 | 1343 | Gemma 3 12B |
| LMArena Text: medicine and healthcare | 1334 | 1363 | Mercury 2 |
| LMArena Text: legal and government | 1381 | Not measured | Only Gemma 3 12B measured |
| LMArena Text: business and finance | 1376 | 1349 | Gemma 3 12B |
| Neither model has a result on the other 13 boards here | |||
Web designDirectional onlyPublic boards, shown as published, kept out of the index8 boards, none shared
| Benchmark | Gemma 3 12B | Mercury 2 | Leader |
|---|---|---|---|
| Design Arena: websites | Not measured | 1036 | Only Mercury 2 measured |
| Design Arena: UI components | Not measured | 996 | Only Mercury 2 measured |
| Design Arena: game dev | Not measured | 984 | Only Mercury 2 measured |
| Design Arena: data viz | Not measured | 1009 | Only Mercury 2 measured |
| Design Arena: 3D | Not measured | 982 | Only Mercury 2 measured |
| Design Arena: all code categories | Not measured | 1021 | Only Mercury 2 measured |
| Design Arena: SVG | Not measured | 998 | Only Mercury 2 measured |
| Design Arena: ASCII art | Not measured | 988 | Only Mercury 2 measured |
| Neither model has a result on the other 1 board here | |||
GeneralLike-for-likePublic boards, shown as published, kept out of the index39
| Benchmark | Gemma 3 12B | Mercury 2 | Leader |
|---|---|---|---|
| IFBench | 36.7% | 69.8% | Mercury 2 |
| Long context reasoning (AA-LCR) | 8.3% | 43.7% | Mercury 2 |
| DTBench | 48.8% | Not measured | Only Gemma 3 12B measured |
| LMCA | 4.5% | Not measured | Only Gemma 3 12B measured |
| LMArena Text | 1334 | 1354 | Mercury 2 |
| LMArena Text: instruction following | 1299 | 1328 | Mercury 2 |
| LMArena Text: creative writing | 1331 | 1286 | Gemma 3 12B |
| LMArena Text: English | 1349 | 1378 | Mercury 2 |
| LMArena Text: non-English | 1318 | 1330 | Mercury 2 |
| LMArena Text: Chinese | Not measured | 1414 | Only Mercury 2 measured |
| LMArena Text: German | 1370 | Not measured | Only Gemma 3 12B measured |
| LMArena Text: Russian | 1335 | 1304 | Gemma 3 12B |
| LMArena Text: multi-turn | 1334 | 1357 | Mercury 2 |
| LMArena Text: longer queries | 1317 | 1329 | Mercury 2 |
| LMArena Text: writing and language | 1307 | 1300 | Gemma 3 12B |
| LMArena Text: entertainment and media | 1297 | 1314 | Mercury 2 |
| Neither model has a result on the other 30 boards here | |||
Image generationNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
| Benchmark | Gemma 3 12B | Mercury 2 | Leader |
|---|---|---|---|
| Neither model has a result on 5 boards here | |||
What each workload costs
Three fixed token mixes at each model's listed price, so per-token rates become a bill.
Chat turn
1K input + 500 output tokens
Gemma 3 12B costs less
Repository review
50K input + 3K output tokens
Gemma 3 12B costs less
Agent loop
200K input + 10K output tokens
Gemma 3 12B costs less
Listed OpenRouter rates, without cache or batch discounts. A workload that does not fit a model's context window would need splitting.
Specification differences
The leading value in a row is marked; a row with a missing value names no leader. Our two rows are marked in red.
| Specification | Google Gemma 3 12B | Inception Mercury 2 |
|---|---|---|
| Maker | Inception | |
| Weights | Open weights | No public weights listed |
| Released | March 13, 2025 | March 4, 2026 |
| Context window | 131K | 128K |
| Input $/Mtok | $0.075 | $0.25 |
| Output $/Mtok | $0.1625 | $0.75 |
| Coding index | Not benchmarked | Not benchmarked |
| Independent measurements behind it | 0 | 1 |
| Cost per solved task | Not computable | Not computable |
| Source | OpenRouter listing | OpenRouter listing |
Questions
Is Gemma 3 12B better than Mercury 2 for coding?
Neither model has a coding score yet, so the two cannot be ranked on coding. Pick Gemma 3 12B for output tokens 4.6x cheaper ($0.1625 vs $0.75 per million) and a larger context window (131K against 128K tokens).
Which is cheaper, Gemma 3 12B or Mercury 2?
Gemma 3 12B costs $0.075 per million input tokens and $0.1625 per million output tokens; Mercury 2 costs $0.25 and $0.75. Cost per solved task is known for neither of them.
Which has the bigger context window, Gemma 3 12B or Mercury 2?
Gemma 3 12B, with 131K tokens against 128K.
How many benchmarks is the Gemma 3 12B vs Mercury 2 comparison based on?
28 benchmarks have a result for both models as of October 22, 2026. Gemma 3 12B's coding index rests on 0 independent benchmarks and Mercury 2's on 1. Where only one model has a result, the page says so instead of naming a winner.