Gemini 2.5 Pro vs Mercury 2
Gemini 2.5 Pro leads Mercury 2 on the Artificial Analysis Intelligence Index, 16.1 to 10.8, and Mercury 2 costs 13.3x less per output token ($0.75 vs $10.00 per million). Updated October 22, 2026; 38 benchmarks have a result for both.
Gemini 2.5 Pro or Mercury 2: which to pick
Only Gemini 2.5 Pro has a coding score, 19.1 on the Vibe Coding Index; Mercury 2 has none, so the two cannot be ranked on coding.
Pick Mercury 2 for output tokens 13.3x cheaper ($0.75 vs $10.00 per million) and work measured by τ²-Bench Telecom or IFBench, where it leads.
- Shared results
- 38
- Gemini 2.5 Pro only
- 52
- Mercury 2 only
- 4
- Like-for-like categories
- 7 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
Only Gemini 2.5 Pro has a coding score, so no call is made.
One side not measured
Intelligence
AA Intelligence Index
Gemini 2.5 Pro
Gemini 2.5 Pro leads, 16.1 against 10.8.
Same board, both measured
Agentic work
AA Agentic Index
No call
Tied at 1.6.
Same board, both measured
Web design
Design Arena: websites
Gemini 2.5 Pro
Gemini 2.5 Pro leads, 1167 against 1036.
Same board, both measured
Long documents
Listed context window
Gemini 2.5 Pro
Gemini 2.5 Pro takes 1.05M tokens against 128K.
Listed by OpenRouter
Everyday cost
1K input + 500 output tokens
Mercury 2
Gemini 2.5 Pro $0.0063, Mercury 2 $0.0006 per turn.
List prices
Cost per solved task
One SWE-bench Verified task, solved
No call
Only Gemini 2.5 Pro has the number, $0.64.
Directional only
At a glance
- Coding index
- Gemini 2.5 Pro 19.1 from 3 benchmarks, Mercury 2 not benchmarked.
- Widest category
- General, 20.6 points apart on average over 13 shared benchmarks.
- Widest single gap
- LMArena Text: creative writing: Gemini 2.5 Pro 1454 against Mercury 2 1286, 27.9 points apart on a 0 to 100 scale.
- Output price
- Gemini 2.5 Pro $10.00 against Mercury 2 $0.75 per million output tokens, 13.3x apart.
- Context window
- Gemini 2.5 Pro takes 1.05M 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 | Gemini 2.5 Pro | Bars | Mercury 2 | Ties |
|---|---|---|---|---|
| Coding | 7 | 0 | 1 tie | |
| Intelligence | 1 | 0 | ||
| Agentic work | 0 | 1 | 1 tie | |
| Reasoning | 5 | 0 | ||
| Knowledge | 3 | 0 | ||
| Web design | 6 | 0 | ||
| General | 12 | 1 | ||
| All shared boards | 34 | 2 | 2 ties |
CodingLike-for-likeSix of these boards feed the Vibe Coding Index70
| Benchmark | Gemini 2.5 Pro | Mercury 2 | Leader |
|---|---|---|---|
| SWE-bench Verified | 53.6% | Not measured | Only Gemini 2.5 Pro measured |
| LMArena WebDev | 1226 | 1171 | Gemini 2.5 Pro |
| AA Coding Index | 33.3 | 31.1 | Gemini 2.5 Pro |
| SWE-bench Verified (Vals AI) | 54.4% | Not measured | Only Gemini 2.5 Pro measured |
| Vibe Code Bench (Vals AI) | 0.4% | Not measured | Only Gemini 2.5 Pro measured |
| LiveCodeBench (Artificial Analysis run) | 80.1% | Not measured | Only Gemini 2.5 Pro measured |
| SciCode | 46.3% | 37.7% | Gemini 2.5 Pro |
| Terminal-Bench Hard (Artificial Analysis run) | 26.5% | 26.5% | Tie |
| Terminal-Bench | 32.6% | Not measured | Only Gemini 2.5 Pro measured |
| GSO-Bench | 3.9% | Not measured | Only Gemini 2.5 Pro measured |
| WeirdML | 54.0% | 43.2% | Gemini 2.5 Pro |
| ALE-Bench | Not measured | 785.6 | Only Mercury 2 measured |
| LMArena Text: coding | 1452 | 1390 | Gemini 2.5 Pro |
| LMArena Text: software and IT | 1459 | 1385 | Gemini 2.5 Pro |
| LMArena WebDev: React | Not measured | 1160 | Only Mercury 2 measured |
| LMArena WebDev: HTML | 1235 | 1199 | Gemini 2.5 Pro |
| LMArena WebDev: from an image | 1285 | Not measured | Only Gemini 2.5 Pro measured |
| Neither model has a result on the other 22 boards here | |||
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index10
| Benchmark | Gemini 2.5 Pro | Mercury 2 | Leader |
|---|---|---|---|
| AA Intelligence Index | 16.1 | 10.8 | Gemini 2.5 Pro |
| Epoch Capabilities Index | 145.1 | Not measured | Only Gemini 2.5 Pro measured |
Agentic workLike-for-likePublic boards, shown as published, kept out of the index01
| Benchmark | Gemini 2.5 Pro | Mercury 2 | Leader |
|---|---|---|---|
| AA Agentic Index | 1.6 | 1.6 | Tie |
| τ²-Bench Telecom | 54.1% | 70.8% | Mercury 2 |
| GDPval | 23.3% | Not measured | Only Gemini 2.5 Pro measured |
| DeepResearch Bench | 41.5% | Not measured | Only Gemini 2.5 Pro measured |
| Vending-Bench 2 | $574 | Not measured | Only Gemini 2.5 Pro measured |
| BrowseComp-Plus | 29.5% | Not measured | Only Gemini 2.5 Pro measured |
| Neither model has a result on the other 35 boards here | |||
ReasoningLike-for-likePublic boards, shown as published, kept out of the index50
| Benchmark | Gemini 2.5 Pro | Mercury 2 | Leader |
|---|---|---|---|
| GPQA Diamond (Artificial Analysis run) | 84.4% | 77.0% | Gemini 2.5 Pro |
| Humanity's Last Exam (Artificial Analysis run) | 22.5% | 17.1% | Gemini 2.5 Pro |
| GPQA Diamond (Epoch AI run) | 85.3% | Not measured | Only Gemini 2.5 Pro measured |
| ARC-AGI | 41.0% | Not measured | Only Gemini 2.5 Pro measured |
| ARC-AGI-2 | 4.9% | Not measured | Only Gemini 2.5 Pro measured |
| LMArena Text: hard prompts | 1455 | 1362 | Gemini 2.5 Pro |
| LMArena Text: expert | 1452 | 1358 | Gemini 2.5 Pro |
| LMArena Text: hard prompts in English | 1453 | 1374 | Gemini 2.5 Pro |
| LMArena Vision: diagrams | 1274 | Not measured | Only Gemini 2.5 Pro measured |
| LMArena Vision: homework | 1281 | Not measured | Only Gemini 2.5 Pro measured |
| Kagi LLM Benchmark | 70.3% | Not measured | Only Gemini 2.5 Pro measured |
| Neither model has a result on the other 11 boards here | |||
MathDirectional onlyPublic boards, shown as published, kept out of the index7 boards, none shared
| Benchmark | Gemini 2.5 Pro | Mercury 2 | Leader |
|---|---|---|---|
| AA Math Index | 87.7 | Not measured | Only Gemini 2.5 Pro measured |
| AIME 2025 (Artificial Analysis run) | 87.7% | Not measured | Only Gemini 2.5 Pro measured |
| OTIS Mock AIME | 84.7% | Not measured | Only Gemini 2.5 Pro measured |
| FrontierMath, tiers 1 to 3 | 24.6% | Not measured | Only Gemini 2.5 Pro measured |
| FrontierMath, tier 4 | 0.0% | Not measured | Only Gemini 2.5 Pro measured |
| LMArena Text: math | 1450 | Not measured | Only Gemini 2.5 Pro measured |
| LMArena Text: mathematical work | 1454 | Not measured | Only Gemini 2.5 Pro measured |
| Neither model has a result on the other 6 boards here | |||
KnowledgeLike-for-likePublic boards, shown as published, kept out of the index30
| Benchmark | Gemini 2.5 Pro | Mercury 2 | Leader |
|---|---|---|---|
| CaseLaw (Vals AI) | 63.9% | Not measured | Only Gemini 2.5 Pro measured |
| CorpFin (Vals AI) | 60.8% | Not measured | Only Gemini 2.5 Pro measured |
| MortgageTax (Vals AI) | 68.9% | Not measured | Only Gemini 2.5 Pro measured |
| MedCode (Vals AI) | 50.6% | Not measured | Only Gemini 2.5 Pro measured |
| MMLU Pro (Artificial Analysis run) | 86.2% | Not measured | Only Gemini 2.5 Pro measured |
| LMArena Text: science | 1480 | 1343 | Gemini 2.5 Pro |
| LMArena Text: medicine and healthcare | 1476 | 1363 | Gemini 2.5 Pro |
| LMArena Text: legal and government | 1480 | Not measured | Only Gemini 2.5 Pro measured |
| LMArena Text: business and finance | 1439 | 1349 | Gemini 2.5 Pro |
| FACTS Benchmark Suite | 61.5% | Not measured | Only Gemini 2.5 Pro measured |
| Neither model has a result on the other 8 boards here | |||
Web designLike-for-likePublic boards, shown as published, kept out of the index60
| Benchmark | Gemini 2.5 Pro | Mercury 2 | Leader |
|---|---|---|---|
| Design Arena: websites | 1167 | 1036 | Gemini 2.5 Pro |
| Design Arena: UI components | 1137 | 996 | Gemini 2.5 Pro |
| Design Arena: game dev | 1111 | 984 | Gemini 2.5 Pro |
| Design Arena: data viz | 1222 | 1009 | Gemini 2.5 Pro |
| Design Arena: 3D | 1080 | 982 | Gemini 2.5 Pro |
| Design Arena: all code categories | 1152 | 1021 | Gemini 2.5 Pro |
| 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 index121
| Benchmark | Gemini 2.5 Pro | Mercury 2 | Leader |
|---|---|---|---|
| SAGE (Vals AI) | 41.9% | Not measured | Only Gemini 2.5 Pro measured |
| MedScribe (Vals AI) | 73.5% | Not measured | Only Gemini 2.5 Pro measured |
| IFBench | 48.7% | 69.8% | Mercury 2 |
| Long context reasoning (AA-LCR) | 69.0% | 43.7% | Gemini 2.5 Pro |
| DTBench | 82.4% | Not measured | Only Gemini 2.5 Pro measured |
| LMCA | 34.8% | Not measured | Only Gemini 2.5 Pro measured |
| Creative writing (Lech Mazur) | 83.8% | Not measured | Only Gemini 2.5 Pro measured |
| LMArena Text | 1458 | 1354 | Gemini 2.5 Pro |
| LMArena Text: instruction following | 1437 | 1328 | Gemini 2.5 Pro |
| LMArena Text: creative writing | 1454 | 1286 | Gemini 2.5 Pro |
| LMArena Vision | 1263 | Not measured | Only Gemini 2.5 Pro measured |
| LMArena Text: English | 1458 | 1378 | Gemini 2.5 Pro |
| LMArena Text: non-English | 1452 | 1330 | Gemini 2.5 Pro |
| LMArena Text: Chinese | 1507 | 1414 | Gemini 2.5 Pro |
| LMArena Text: German | 1487 | Not measured | Only Gemini 2.5 Pro measured |
| LMArena Text: Japanese | 1461 | Not measured | Only Gemini 2.5 Pro measured |
| LMArena Text: Korean | 1434 | Not measured | Only Gemini 2.5 Pro measured |
| LMArena Text: French | 1473 | Not measured | Only Gemini 2.5 Pro measured |
| LMArena Text: Spanish | 1474 | Not measured | Only Gemini 2.5 Pro measured |
| LMArena Text: Russian | 1461 | 1304 | Gemini 2.5 Pro |
| LMArena Text: Polish | 1479 | Not measured | Only Gemini 2.5 Pro measured |
| LMArena Text: multi-turn | 1453 | 1357 | Gemini 2.5 Pro |
| LMArena Text: longer queries | 1449 | 1329 | Gemini 2.5 Pro |
| LMArena Text: writing and language | 1454 | 1300 | Gemini 2.5 Pro |
| LMArena Text: entertainment and media | 1441 | 1314 | Gemini 2.5 Pro |
| LMArena Vision: English | 1261 | Not measured | Only Gemini 2.5 Pro measured |
| LMArena Vision: Chinese | 1300 | Not measured | Only Gemini 2.5 Pro measured |
| LMArena Vision: reading text | 1270 | Not measured | Only Gemini 2.5 Pro measured |
| LMArena Vision: humor | 1262 | Not measured | Only Gemini 2.5 Pro measured |
| LMArena Vision: captioning | 1304 | Not measured | Only Gemini 2.5 Pro measured |
| LMArena Vision: recognizing things | 1283 | Not measured | Only Gemini 2.5 Pro measured |
| LMArena Vision: creative writing | 1265 | Not measured | Only Gemini 2.5 Pro measured |
| LMArena Document | 1421 | Not measured | Only Gemini 2.5 Pro measured |
| Neither model has a result on the other 13 boards here | |||
Image generationNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
| Benchmark | Gemini 2.5 Pro | 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
Mercury 2 costs less
Repository review
50K input + 3K output tokens
Mercury 2 costs less
Agent loop
200K input + 10K output tokens
Mercury 2 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 Gemini 2.5 Pro | Inception Mercury 2 |
|---|---|---|
| Maker | Inception | |
| Weights | No public weights listed | No public weights listed |
| Released | June 17, 2025 | March 4, 2026 |
| Context window | 1.05M | 128K |
| Input $/Mtok | $1.25 | $0.25 |
| Output $/Mtok | $10.00 | $0.75 |
| Coding index | 19.1 | Not benchmarked |
| Independent measurements behind it | 3 | 1 |
| Cost per solved task | $0.64 | Not computable |
| Source | OpenRouter listing | OpenRouter listing |
Questions
Is Gemini 2.5 Pro better than Mercury 2 for coding?
Only Gemini 2.5 Pro has a coding score, 19.1 on the Vibe Coding Index; Mercury 2 has none, so the two cannot be ranked on coding. Pick Mercury 2 for output tokens 13.3x cheaper ($0.75 vs $10.00 per million) and work measured by τ²-Bench Telecom or IFBench, where it leads.
Which is cheaper, Gemini 2.5 Pro or Mercury 2?
Gemini 2.5 Pro costs $1.25 per million input tokens and $10.00 per million output tokens; Mercury 2 costs $0.25 and $0.75. Cost per solved task is known for Gemini 2.5 Pro only.
Which has the bigger context window, Gemini 2.5 Pro or Mercury 2?
Gemini 2.5 Pro, with 1.05M tokens against 128K.
How many benchmarks is the Gemini 2.5 Pro vs Mercury 2 comparison based on?
38 benchmarks have a result for both models as of October 22, 2026. Gemini 2.5 Pro's coding index rests on 3 independent benchmarks and Mercury 2's on 1. Where only one model has a result, the page says so instead of naming a winner.