Mercury 2.5 vs Solar Pro 4
Solar Pro 4 leads Mercury 2.5 on the Artificial Analysis Intelligence Index, 28.2 to 12.3, and Mercury 2.5 costs 4.0x less per output token ($0.15 vs $0.60 per million). Updated October 22, 2026; 5 benchmarks have a result for both.
Mercury 2.5 or Solar Pro 4: which to pick
Only Mercury 2.5 has a coding score, 1.6 on the Vibe Coding Index; Solar Pro 4 has none, so the two cannot be ranked on coding.
Pick Solar Pro 4 for a larger context window (524K against 260K tokens) and work measured by SciCode or AA Intelligence Index, where it leads.
- Shared results
- 5
- Mercury 2.5 only
- 17
- Solar Pro 4 only
- 40
- Like-for-like categories
- 4 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 Mercury 2.5 has a coding score, so no call is made.
One side not measured
Intelligence
AA Intelligence Index
Solar Pro 4
Solar Pro 4 leads, 28.2 against 12.3.
Same board, both measured
Web design
Design Arena: websites
No call
Only Solar Pro 4 has a Design Arena: websites result, 1176.
Directional only
Long documents
Listed context window
Solar Pro 4
Solar Pro 4 takes 524K tokens against 260K.
Listed by OpenRouter
Everyday cost
1K input + 500 output tokens
Mercury 2.5
Mercury 2.5 $0.0001, Solar Pro 4 $0.0004 per turn.
List prices
At a glance
- Coding index
- Mercury 2.5 1.6 from 2 benchmarks, Solar Pro 4 not benchmarked.
- Widest category
- Reasoning, 18.0 points apart on average over 1 shared benchmark.
- Widest single gap
- Humanity's Last Exam (Artificial Analysis run): Mercury 2.5 11.8% against Solar Pro 4 29.8%, 18.0 points apart on a 0 to 100 scale.
- Output price
- Mercury 2.5 $0.15 against Solar Pro 4 $0.60 per million output tokens, 4.0x apart.
- Context window
- Mercury 2.5 takes 260K tokens, Solar Pro 4 524K.
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 | Mercury 2.5 | Bars | Solar Pro 4 | Ties |
|---|---|---|---|---|
| Coding | 1 | 1 | ||
| Intelligence | 0 | 1 | ||
| Reasoning | 0 | 1 | ||
| General | 1 | 0 | ||
| All shared boards | 2 | 3 |
CodingLike-for-likeSix of these boards feed the Vibe Coding Index11
| Benchmark | Mercury 2.5 | Solar Pro 4 | Leader |
|---|---|---|---|
| LMArena WebDev | Not measured | 1371 | Only Solar Pro 4 measured |
| AA Coding Index | Not measured | 52.7 | Only Solar Pro 4 measured |
| Terminal-Bench 4 (Vals AI) | 0.0% | Not measured | Only Mercury 2.5 measured |
| Vibe Code Bench (Vals AI) | 3.7% | Not measured | Only Mercury 2.5 measured |
| Code migration (Vals AI) | 4.5% | Not measured | Only Mercury 2.5 measured |
| IOI (Vals AI) | 2.4% | Not measured | Only Mercury 2.5 measured |
| Terminal-Bench 2.1 (Vals AI) | 34.5% | Not measured | Only Mercury 2.5 measured |
| SkillsBench (Vals AI) | 18.1% | Not measured | Only Mercury 2.5 measured |
| CyberBench (Vals AI) | 45.5% | Not measured | Only Mercury 2.5 measured |
| SciCode | 38.5% | 48.0% | Solar Pro 4 |
| ALE-Bench | 301.6 | 179.3 | Mercury 2.5 |
| LMArena Text: coding | Not measured | 1438 | Only Solar Pro 4 measured |
| LMArena Text: software and IT | Not measured | 1431 | Only Solar Pro 4 measured |
| LMArena WebDev: React | Not measured | 1363 | Only Solar Pro 4 measured |
| LMArena WebDev: HTML | Not measured | 1371 | Only Solar Pro 4 measured |
| Neither model has a result on the other 24 boards here | |||
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index01
| Benchmark | Mercury 2.5 | Solar Pro 4 | Leader |
|---|---|---|---|
| AA Intelligence Index | 12.3 | 28.2 | Solar Pro 4 |
| Neither model has a result on the other 1 board here | |||
Agentic workDirectional onlyPublic boards, shown as published, kept out of the index6 boards, none shared
| Benchmark | Mercury 2.5 | Solar Pro 4 | Leader |
|---|---|---|---|
| Design Arena: agents building web apps | Not measured | 1105 | Only Solar Pro 4 measured |
| Finance Agent (Vals AI) | 18.9% | Not measured | Only Mercury 2.5 measured |
| Tax Agent Bench (Vals AI) | 2.5% | Not measured | Only Mercury 2.5 measured |
| Legal Research Bench (Vals AI) | 4.3% | Not measured | Only Mercury 2.5 measured |
| Excel Modeling Benchmark (Vals AI) | 8.8% | Not measured | Only Mercury 2.5 measured |
| Terminal-Bench-Science (Vals AI) | 0.0% | Not measured | Only Mercury 2.5 measured |
| Neither model has a result on the other 35 boards here | |||
ReasoningLike-for-likePublic boards, shown as published, kept out of the index01
| Benchmark | Mercury 2.5 | Solar Pro 4 | Leader |
|---|---|---|---|
| GPQA Diamond (Artificial Analysis run) | Not measured | 89.1% | Only Solar Pro 4 measured |
| Humanity's Last Exam (Artificial Analysis run) | 11.8% | 29.8% | Solar Pro 4 |
| LMArena Text: hard prompts | Not measured | 1400 | Only Solar Pro 4 measured |
| LMArena Text: expert | Not measured | 1428 | Only Solar Pro 4 measured |
| LMArena Text: hard prompts in English | Not measured | 1427 | Only Solar Pro 4 measured |
| Neither model has a result on the other 17 boards here | |||
MathDirectional onlyPublic boards, shown as published, kept out of the index3 boards, none shared
| Benchmark | Mercury 2.5 | Solar Pro 4 | Leader |
|---|---|---|---|
| ProofBench | 3.0% | Not measured | Only Mercury 2.5 measured |
| LMArena Text: math | Not measured | 1421 | Only Solar Pro 4 measured |
| LMArena Text: mathematical work | Not measured | 1427 | Only Solar Pro 4 measured |
| Neither model has a result on the other 10 boards here | |||
KnowledgeDirectional onlyPublic boards, shown as published, kept out of the index6 boards, none shared
| Benchmark | Mercury 2.5 | Solar Pro 4 | Leader |
|---|---|---|---|
| LegalBench (Vals AI) | 83.1% | Not measured | Only Mercury 2.5 measured |
| MedCode (Vals AI) | 31.3% | Not measured | Only Mercury 2.5 measured |
| LMArena Text: science | Not measured | 1404 | Only Solar Pro 4 measured |
| LMArena Text: medicine and healthcare | Not measured | 1374 | Only Solar Pro 4 measured |
| LMArena Text: legal and government | Not measured | 1383 | Only Solar Pro 4 measured |
| LMArena Text: business and finance | Not measured | 1381 | Only Solar Pro 4 measured |
| Neither model has a result on the other 12 boards here | |||
Web designDirectional onlyPublic boards, shown as published, kept out of the index6 boards, none shared
| Benchmark | Mercury 2.5 | Solar Pro 4 | Leader |
|---|---|---|---|
| Design Arena: websites | Not measured | 1176 | Only Solar Pro 4 measured |
| Design Arena: UI components | Not measured | 1147 | Only Solar Pro 4 measured |
| Design Arena: game dev | Not measured | 1169 | Only Solar Pro 4 measured |
| Design Arena: data viz | Not measured | 1177 | Only Solar Pro 4 measured |
| Design Arena: 3D | Not measured | 1178 | Only Solar Pro 4 measured |
| Design Arena: all code categories | Not measured | 1182 | Only Solar Pro 4 measured |
| Neither model has a result on the other 3 boards here | |||
GeneralLike-for-likePublic boards, shown as published, kept out of the index10
| Benchmark | Mercury 2.5 | Solar Pro 4 | Leader |
|---|---|---|---|
| Public Benefits Bench (Vals AI) | 45.3% | Not measured | Only Mercury 2.5 measured |
| MedScribe (Vals AI) | 55.1% | Not measured | Only Mercury 2.5 measured |
| Long context reasoning (AA-LCR) | 71.7% | 70.7% | Mercury 2.5 |
| LMArena Text | Not measured | 1388 | Only Solar Pro 4 measured |
| LMArena Text: instruction following | Not measured | 1375 | Only Solar Pro 4 measured |
| LMArena Text: creative writing | Not measured | 1317 | Only Solar Pro 4 measured |
| LMArena Text: English | Not measured | 1414 | Only Solar Pro 4 measured |
| LMArena Text: non-English | Not measured | 1363 | Only Solar Pro 4 measured |
| LMArena Text: Chinese | Not measured | 1422 | Only Solar Pro 4 measured |
| LMArena Text: German | Not measured | 1358 | Only Solar Pro 4 measured |
| LMArena Text: Japanese | Not measured | 1320 | Only Solar Pro 4 measured |
| LMArena Text: Korean | Not measured | 1383 | Only Solar Pro 4 measured |
| LMArena Text: French | Not measured | 1400 | Only Solar Pro 4 measured |
| LMArena Text: Spanish | Not measured | 1409 | Only Solar Pro 4 measured |
| LMArena Text: Russian | Not measured | 1357 | Only Solar Pro 4 measured |
| LMArena Text: Polish | Not measured | 1304 | Only Solar Pro 4 measured |
| LMArena Text: multi-turn | Not measured | 1385 | Only Solar Pro 4 measured |
| LMArena Text: longer queries | Not measured | 1382 | Only Solar Pro 4 measured |
| LMArena Text: writing and language | Not measured | 1344 | Only Solar Pro 4 measured |
| LMArena Text: entertainment and media | Not measured | 1332 | Only Solar Pro 4 measured |
| Neither model has a result on the other 26 boards here | |||
Image generationNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
| Benchmark | Mercury 2.5 | Solar Pro 4 | 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 2.5 costs less
Repository review
50K input + 3K output tokens
Mercury 2.5 costs less
Agent loop
200K input + 10K output tokens
Mercury 2.5 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 | Inception Mercury 2.5 | Upstage Solar Pro 4 |
|---|---|---|
| Maker | Inception | Upstage |
| Weights | No public weights listed | No public weights listed |
| Released | September 8, 2026 | August 10, 2026 |
| Context window | 260K | 524K |
| Input $/Mtok | $0.04 | $0.15 |
| Output $/Mtok | $0.15 | $0.60 |
| Coding index | 1.6 | Not benchmarked |
| Independent measurements behind it | 2 | 1 |
| Cost per solved task | Not computable | Not computable |
| Source | OpenRouter listing | OpenRouter listing |
Questions
Is Mercury 2.5 better than Solar Pro 4 for coding?
Only Mercury 2.5 has a coding score, 1.6 on the Vibe Coding Index; Solar Pro 4 has none, so the two cannot be ranked on coding. Pick Solar Pro 4 for a larger context window (524K against 260K tokens) and work measured by SciCode or AA Intelligence Index, where it leads.
Which is cheaper, Mercury 2.5 or Solar Pro 4?
Mercury 2.5 costs $0.04 per million input tokens and $0.15 per million output tokens; Solar Pro 4 costs $0.15 and $0.60. Cost per solved task is known for neither of them.
Which has the bigger context window, Mercury 2.5 or Solar Pro 4?
Solar Pro 4, with 524K tokens against 260K.
How many benchmarks is the Mercury 2.5 vs Solar Pro 4 comparison based on?
5 benchmarks have a result for both models as of October 22, 2026. Mercury 2.5's coding index rests on 2 independent benchmarks and Solar Pro 4's on 1. Where only one model has a result, the page says so instead of naming a winner.