GPT-6 Sol vs Mercury 2
GPT-6 Sol leads Mercury 2 on the Artificial Analysis Intelligence Index, 47.6 to 10.8, and Mercury 2 costs 13.3x less per output token ($0.75 vs $10.00 per million). Updated October 21, 2026; 35 benchmarks have a result for both.
GPT-6 Sol or Mercury 2: which to pick
Only GPT-6 Sol has a coding score, 76.0 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 LMArena Text: Chinese, where it leads.
- Shared results
- 35
- GPT-6 Sol only
- 66
- Mercury 2 only
- 7
- 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
Only GPT-6 Sol has a coding score, so no call is made.
One side not measured
Intelligence
AA Intelligence Index
GPT-6 Sol
GPT-6 Sol leads, 47.6 against 10.8.
Same board, both measured
Agentic work
AA Agentic Index
No call
Only Mercury 2 has a AA Agentic Index result, 1.6.
Directional only
Web design
Design Arena: websites
GPT-6 Sol
GPT-6 Sol leads, 1292 against 1036.
Same board, both measured
Long documents
Listed context window
GPT-6 Sol
GPT-6 Sol takes 1.05M tokens against 128K.
Listed by OpenRouter
Everyday cost
1K input + 500 output tokens
Mercury 2
GPT-6 Sol $0.0070, Mercury 2 $0.0006 per turn.
List prices
At a glance
- Coding index
- GPT-6 Sol 76.0 from 5 benchmarks, Mercury 2 not benchmarked.
- Widest category
- Coding, 43.2 points apart on average over 7 shared benchmarks.
- Widest single gap
- LMArena WebDev: React: GPT-6 Sol 1685 against Mercury 2 1160, 73.4 points apart on a 0 to 100 scale.
- Output price
- GPT-6 Sol $10.00 against Mercury 2 $0.75 per million output tokens, 13.3x apart.
- Context window
- GPT-6 Sol 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 | GPT-6 Sol | Bars | Mercury 2 | Ties |
|---|---|---|---|---|
| Coding | 7 | 0 | ||
| Intelligence | 1 | 0 | ||
| Reasoning | 4 | 0 | ||
| Knowledge | 3 | 0 | ||
| Web design | 8 | 0 | ||
| General | 11 | 1 | ||
| All shared boards | 34 | 1 |
CodingLike-for-likeSix of these boards feed the Vibe Coding Index70
| Benchmark | GPT-6 Sol | Mercury 2 | Leader |
|---|---|---|---|
| LiveBench coding | 93.1% | Not measured | Only GPT-6 Sol measured |
| LMArena WebDev | 1683 | 1171 | GPT-6 Sol |
| AA Coding Index | Not measured | 31.1 | Only Mercury 2 measured |
| Terminal-Bench 4 (Vals AI) | 44.4% | Not measured | Only GPT-6 Sol measured |
| Vibe Code Bench (Vals AI) | 87.8% | Not measured | Only GPT-6 Sol measured |
| Code migration (Vals AI) | 57.2% | Not measured | Only GPT-6 Sol measured |
| ProgramBench (Vals AI) | 2.0% | Not measured | Only GPT-6 Sol measured |
| IOI (Vals AI) | 82.6% | Not measured | Only GPT-6 Sol measured |
| Terminal-Bench 2.1 (Vals AI) | 83.2% | Not measured | Only GPT-6 Sol measured |
| CyberBench (Vals AI) | 78.0% | Not measured | Only GPT-6 Sol measured |
| SciCode | 57.6% | 37.7% | GPT-6 Sol |
| Terminal-Bench Hard (Artificial Analysis run) | Not measured | 26.5% | Only Mercury 2 measured |
| FrontierCode | 49.3% | Not measured | Only GPT-6 Sol measured |
| WeirdML | Not measured | 43.2% | Only Mercury 2 measured |
| ALE-Bench | 2462.0 | 785.6 | GPT-6 Sol |
| LMArena Text: coding | 1448 | 1390 | GPT-6 Sol |
| LMArena Text: software and IT | 1433 | 1385 | GPT-6 Sol |
| LMArena WebDev: React | 1685 | 1160 | GPT-6 Sol |
| LMArena WebDev: HTML | 1685 | 1199 | GPT-6 Sol |
| LMArena WebDev: from an image | 1660 | Not measured | Only GPT-6 Sol measured |
| Neither model has a result on the other 19 boards here | |||
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index10
| Benchmark | GPT-6 Sol | Mercury 2 | Leader |
|---|---|---|---|
| AA Intelligence Index | 47.6 | 10.8 | GPT-6 Sol |
| Epoch Capabilities Index | 163.7 | Not measured | Only GPT-6 Sol measured |
Agentic workDirectional onlyPublic boards, shown as published, kept out of the index19 boards, none shared
| Benchmark | GPT-6 Sol | Mercury 2 | Leader |
|---|---|---|---|
| AA Agentic Index | Not measured | 1.6 | Only Mercury 2 measured |
| Design Arena: agents building web apps | 1231 | Not measured | Only GPT-6 Sol measured |
| Design Arena: agents building full-stack apps | 1238 | Not measured | Only GPT-6 Sol measured |
| Design Arena: agents building mobile apps | 1214 | Not measured | Only GPT-6 Sol measured |
| LiveBench research | 69.3% | Not measured | Only GPT-6 Sol measured |
| LiveBench browser | 92.0% | Not measured | Only GPT-6 Sol measured |
| LiveBench long agentic | 66.9% | Not measured | Only GPT-6 Sol measured |
| SREBench (Vals AI) | 30.5% | Not measured | Only GPT-6 Sol measured |
| Finance Agent (Vals AI) | 49.0% | Not measured | Only GPT-6 Sol measured |
| Tax Agent Bench (Vals AI) | 15.0% | Not measured | Only GPT-6 Sol measured |
| Legal Research Bench (Vals AI) | 28.9% | Not measured | Only GPT-6 Sol measured |
| Excel Modeling Benchmark (Vals AI) | 71.5% | Not measured | Only GPT-6 Sol measured |
| BioMysteryBench (Vals AI) | 74.8% | Not measured | Only GPT-6 Sol measured |
| Terminal-Bench-Science (Vals AI) | 30.0% | Not measured | Only GPT-6 Sol measured |
| Vals Science Index | 45.0% | Not measured | Only GPT-6 Sol measured |
| τ²-Bench Telecom | Not measured | 70.8% | Only Mercury 2 measured |
| APEX-Agents | 54.3% | Not measured | Only GPT-6 Sol measured |
| SpireClimb | 7.5% | Not measured | Only GPT-6 Sol measured |
| Vending-Bench 2 | $14,428 | Not measured | Only GPT-6 Sol measured |
| Neither model has a result on the other 22 boards here | |||
ReasoningLike-for-likePublic boards, shown as published, kept out of the index40
| Benchmark | GPT-6 Sol | Mercury 2 | Leader |
|---|---|---|---|
| LiveBench reasoning | 88.7% | Not measured | Only GPT-6 Sol measured |
| MysteryMechanism (Vals AI) | 30.2% | Not measured | Only GPT-6 Sol measured |
| GPQA Diamond (Artificial Analysis run) | Not measured | 77.0% | Only Mercury 2 measured |
| Humanity's Last Exam (Artificial Analysis run) | 47.9% | 17.1% | GPT-6 Sol |
| GPQA Diamond (Epoch AI run) | 94.3% | Not measured | Only GPT-6 Sol measured |
| ARC-AGI | 95.5% | Not measured | Only GPT-6 Sol measured |
| ARC-AGI-2 | 89.6% | Not measured | Only GPT-6 Sol measured |
| Chess puzzles | 56.0% | Not measured | Only GPT-6 Sol measured |
| Mystery game puzzles | 56.0% | Not measured | Only GPT-6 Sol measured |
| EBR-bench | 53.3% | Not measured | Only GPT-6 Sol measured |
| LMArena Text: hard prompts | 1422 | 1362 | GPT-6 Sol |
| LMArena Text: expert | 1437 | 1358 | GPT-6 Sol |
| LMArena Text: hard prompts in English | 1420 | 1374 | GPT-6 Sol |
| LMArena Vision: diagrams | 1270 | Not measured | Only GPT-6 Sol measured |
| LMArena Vision: homework | 1286 | Not measured | Only GPT-6 Sol measured |
| Neither model has a result on the other 7 boards here | |||
MathDirectional onlyPublic boards, shown as published, kept out of the index6 boards, none shared
| Benchmark | GPT-6 Sol | Mercury 2 | Leader |
|---|---|---|---|
| OTIS Mock AIME | 100.0% | Not measured | Only GPT-6 Sol measured |
| FrontierMath, tiers 1 to 3 | 89.8% | Not measured | Only GPT-6 Sol measured |
| FrontierMath, tier 4 | 90.0% | Not measured | Only GPT-6 Sol measured |
| ProofBench | 83.0% | Not measured | Only GPT-6 Sol measured |
| LMArena Text: math | 1407 | Not measured | Only GPT-6 Sol measured |
| LMArena Text: mathematical work | 1424 | Not measured | Only GPT-6 Sol measured |
| Neither model has a result on the other 7 boards here | |||
KnowledgeLike-for-likePublic boards, shown as published, kept out of the index30
| Benchmark | GPT-6 Sol | Mercury 2 | Leader |
|---|---|---|---|
| MedCode (Vals AI) | 47.1% | Not measured | Only GPT-6 Sol measured |
| SimpleQA Verified | 60.7% | Not measured | Only GPT-6 Sol measured |
| LMArena Text: science | 1389 | 1343 | GPT-6 Sol |
| LMArena Text: medicine and healthcare | 1366 | 1363 | GPT-6 Sol |
| LMArena Text: legal and government | 1396 | Not measured | Only GPT-6 Sol measured |
| LMArena Text: business and finance | 1380 | 1349 | GPT-6 Sol |
| FACTS Benchmark Suite | 72.5% | Not measured | Only GPT-6 Sol measured |
| Neither model has a result on the other 11 boards here | |||
Web designLike-for-likePublic boards, shown as published, kept out of the index80
| Benchmark | GPT-6 Sol | Mercury 2 | Leader |
|---|---|---|---|
| Design Arena: websites | 1292 | 1036 | GPT-6 Sol |
| Design Arena: UI components | 1292 | 998 | GPT-6 Sol |
| Design Arena: game dev | 1314 | 985 | GPT-6 Sol |
| Design Arena: data viz | 1269 | 1009 | GPT-6 Sol |
| Design Arena: 3D | 1318 | 983 | GPT-6 Sol |
| Design Arena: all code categories | 1301 | 1022 | GPT-6 Sol |
| Design Arena: SVG | 1316 | 998 | GPT-6 Sol |
| Design Arena: ASCII art | 1225 | 988 | GPT-6 Sol |
| LiveBench design | 82.2% | Not measured | Only GPT-6 Sol measured |
GeneralLike-for-likePublic boards, shown as published, kept out of the index111
| Benchmark | GPT-6 Sol | Mercury 2 | Leader |
|---|---|---|---|
| LiveBench data analysis | 81.2% | Not measured | Only GPT-6 Sol measured |
| Public Benefits Bench (Vals AI) | 56.6% | Not measured | Only GPT-6 Sol measured |
| SAGE (Vals AI) | 44.8% | Not measured | Only GPT-6 Sol measured |
| MedScribe (Vals AI) | 82.0% | Not measured | Only GPT-6 Sol measured |
| IFBench | Not measured | 69.8% | Only Mercury 2 measured |
| Long context reasoning (AA-LCR) | 83.7% | 43.7% | GPT-6 Sol |
| DTBench | 97.3% | Not measured | Only GPT-6 Sol measured |
| LMCA | 59.1% | Not measured | Only GPT-6 Sol measured |
| Furniture assembly | 58.3% | Not measured | Only GPT-6 Sol measured |
| LMArena Text | 1398 | 1354 | GPT-6 Sol |
| LMArena Text: instruction following | 1413 | 1328 | GPT-6 Sol |
| LMArena Text: creative writing | 1378 | 1286 | GPT-6 Sol |
| LMArena Vision | 1240 | Not measured | Only GPT-6 Sol measured |
| LMArena Text: English | 1396 | 1378 | GPT-6 Sol |
| LMArena Text: non-English | 1388 | 1330 | GPT-6 Sol |
| LMArena Text: Chinese | 1412 | 1414 | Mercury 2 |
| LMArena Text: German | 1379 | Not measured | Only GPT-6 Sol measured |
| LMArena Text: Japanese | 1377 | Not measured | Only GPT-6 Sol measured |
| LMArena Text: Korean | 1336 | Not measured | Only GPT-6 Sol measured |
| LMArena Text: French | 1399 | Not measured | Only GPT-6 Sol measured |
| LMArena Text: Spanish | 1387 | Not measured | Only GPT-6 Sol measured |
| LMArena Text: Russian | 1402 | 1304 | GPT-6 Sol |
| LMArena Text: Polish | 1372 | Not measured | Only GPT-6 Sol measured |
| LMArena Text: multi-turn | 1414 | 1357 | GPT-6 Sol |
| LMArena Text: longer queries | 1416 | 1329 | GPT-6 Sol |
| LMArena Text: writing and language | 1389 | 1300 | GPT-6 Sol |
| LMArena Text: entertainment and media | 1373 | 1314 | GPT-6 Sol |
| LMArena Vision: English | 1229 | Not measured | Only GPT-6 Sol measured |
| LMArena Vision: reading text | 1258 | Not measured | Only GPT-6 Sol measured |
| LMArena Vision: creative writing | 1219 | Not measured | Only GPT-6 Sol measured |
| Neither model has a result on the other 16 boards here | |||
Image generationNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
| Benchmark | GPT-6 Sol | 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 | OpenAI GPT-6 Sol | Inception Mercury 2 |
|---|---|---|
| Maker | OpenAI | Inception |
| Weights | No public weights listed | No public weights listed |
| Released | September 22, 2026 | March 4, 2026 |
| Context window | 1.05M | 128K |
| Input $/Mtok | $2.00 | $0.25 |
| Output $/Mtok | $10.00 | $0.75 |
| Coding index | 76.0 | Not benchmarked |
| Independent measurements behind it | 5 | 1 |
| Cost per solved task | Not computable | Not computable |
| Source | OpenRouter listing | OpenRouter listing |
Questions
Is GPT-6 Sol better than Mercury 2 for coding?
Only GPT-6 Sol has a coding score, 76.0 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 LMArena Text: Chinese, where it leads.
Which is cheaper, GPT-6 Sol or Mercury 2?
GPT-6 Sol costs $2.00 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 neither of them.
Which has the bigger context window, GPT-6 Sol or Mercury 2?
GPT-6 Sol, with 1.05M tokens against 128K.
How many benchmarks is the GPT-6 Sol vs Mercury 2 comparison based on?
35 benchmarks have a result for both models as of October 21, 2026. GPT-6 Sol's coding index rests on 5 independent benchmarks and Mercury 2's on 1. Where only one model has a result, the page says so instead of naming a winner.