GPT-5 Pro vs Mercury 2
Mercury 2 costs 160.0x less per output token than GPT-5 Pro ($0.75 vs $120.00 per million). Updated October 21, 2026; 1 benchmarks have a result for both.
GPT-5 Pro or Mercury 2: which to pick
Neither model has a coding score yet, so the two cannot be ranked on coding.
Pick GPT-5 Pro for a larger context window (400K against 128K tokens).
- Shared results
- 1
- GPT-5 Pro only
- 8
- Mercury 2 only
- 41
- Like-for-like categories
- 1 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
No call
Only Mercury 2 has a AA Intelligence Index result, 10.8.
Directional only
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
No call
Only Mercury 2 has a Design Arena: websites result, 1036.
Directional only
Long documents
Listed context window
GPT-5 Pro
GPT-5 Pro takes 400K tokens against 128K.
Listed by OpenRouter
Everyday cost
1K input + 500 output tokens
Mercury 2
GPT-5 Pro $0.075, Mercury 2 $0.0006 per turn.
List prices
At a glance
- Coding index
- GPT-5 Pro not benchmarked, Mercury 2 not benchmarked.
- Widest category
- Coding, 17.2 points apart on average over 1 shared benchmark.
- Widest single gap
- WeirdML: GPT-5 Pro 60.4% against Mercury 2 43.2%, 17.2 points apart on a 0 to 100 scale.
- Output price
- GPT-5 Pro $120.00 against Mercury 2 $0.75 per million output tokens, 160.0x apart.
- Context window
- GPT-5 Pro takes 400K 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-5 Pro | Bars | Mercury 2 | Ties |
|---|---|---|---|---|
| Coding | 1 | 0 | ||
| All shared boards | 1 | 0 |
CodingLike-for-likeSix of these boards feed the Vibe Coding Index10
| Benchmark | GPT-5 Pro | Mercury 2 | Leader |
|---|---|---|---|
| LMArena WebDev | Not measured | 1171 | Only Mercury 2 measured |
| AA Coding Index | Not measured | 31.1 | Only Mercury 2 measured |
| SciCode | Not measured | 37.7% | Only Mercury 2 measured |
| Terminal-Bench Hard (Artificial Analysis run) | Not measured | 26.5% | Only Mercury 2 measured |
| WeirdML | 60.4% | 43.2% | GPT-5 Pro |
| ALE-Bench | Not measured | 785.6 | Only Mercury 2 measured |
| LMArena Text: coding | Not measured | 1390 | Only Mercury 2 measured |
| LMArena Text: software and IT | Not measured | 1385 | Only Mercury 2 measured |
| LMArena WebDev: React | Not measured | 1160 | Only Mercury 2 measured |
| LMArena WebDev: HTML | Not measured | 1199 | Only Mercury 2 measured |
| Neither model has a result on the other 29 boards here | |||
IntelligenceDirectional onlyPublic boards, shown as published, kept out of the index2 boards, none shared
| Benchmark | GPT-5 Pro | Mercury 2 | Leader |
|---|---|---|---|
| AA Intelligence Index | Not measured | 10.8 | Only Mercury 2 measured |
| Epoch Capabilities Index | 150.6 | Not measured | Only GPT-5 Pro measured |
Agentic workDirectional onlyPublic boards, shown as published, kept out of the index2 boards, none shared
| Benchmark | GPT-5 Pro | Mercury 2 | Leader |
|---|---|---|---|
| AA Agentic Index | Not measured | 1.6 | Only Mercury 2 measured |
| τ²-Bench Telecom | Not measured | 70.8% | Only Mercury 2 measured |
| Neither model has a result on the other 39 boards here | |||
ReasoningDirectional onlyPublic boards, shown as published, kept out of the index10 boards, none shared
| Benchmark | GPT-5 Pro | Mercury 2 | Leader |
|---|---|---|---|
| GPQA Diamond (Artificial Analysis run) | Not measured | 77.0% | Only Mercury 2 measured |
| Humanity's Last Exam (Artificial Analysis run) | Not measured | 17.1% | Only Mercury 2 measured |
| ARC-AGI | 70.2% | Not measured | Only GPT-5 Pro measured |
| ARC-AGI-2 | 18.3% | Not measured | Only GPT-5 Pro measured |
| SimpleBench | 61.6% | Not measured | Only GPT-5 Pro measured |
| Chess puzzles | 48.0% | Not measured | Only GPT-5 Pro measured |
| LMArena Text: hard prompts | Not measured | 1362 | Only Mercury 2 measured |
| LMArena Text: expert | Not measured | 1358 | Only Mercury 2 measured |
| LMArena Text: hard prompts in English | Not measured | 1374 | Only Mercury 2 measured |
| Kagi LLM Benchmark | 76.8% | Not measured | Only GPT-5 Pro measured |
| Neither model has a result on the other 12 boards here | |||
MathDirectional onlyPublic boards, shown as published, kept out of the index2 boards, none shared
| Benchmark | GPT-5 Pro | Mercury 2 | Leader |
|---|---|---|---|
| FrontierMath, tiers 1 to 3 | 55.8% | Not measured | Only GPT-5 Pro measured |
| FrontierMath, tier 4 | 19.5% | Not measured | Only GPT-5 Pro measured |
| Neither model has a result on the other 11 boards here | |||
KnowledgeDirectional onlyPublic boards, shown as published, kept out of the index3 boards, none shared
| Benchmark | GPT-5 Pro | Mercury 2 | Leader |
|---|---|---|---|
| LMArena Text: science | Not measured | 1343 | Only Mercury 2 measured |
| LMArena Text: medicine and healthcare | Not measured | 1363 | Only Mercury 2 measured |
| LMArena Text: business and finance | Not measured | 1349 | Only Mercury 2 measured |
| Neither model has a result on the other 15 boards here | |||
Web designDirectional onlyPublic boards, shown as published, kept out of the index8 boards, none shared
| Benchmark | GPT-5 Pro | Mercury 2 | Leader |
|---|---|---|---|
| Design Arena: websites | Not measured | 1036 | Only Mercury 2 measured |
| Design Arena: UI components | Not measured | 998 | Only Mercury 2 measured |
| Design Arena: game dev | Not measured | 985 | Only Mercury 2 measured |
| Design Arena: data viz | Not measured | 1009 | Only Mercury 2 measured |
| Design Arena: 3D | Not measured | 983 | Only Mercury 2 measured |
| Design Arena: all code categories | Not measured | 1022 | 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 | |||
GeneralDirectional onlyPublic boards, shown as published, kept out of the index13 boards, none shared
| Benchmark | GPT-5 Pro | Mercury 2 | Leader |
|---|---|---|---|
| IFBench | Not measured | 69.8% | Only Mercury 2 measured |
| Long context reasoning (AA-LCR) | Not measured | 43.7% | Only Mercury 2 measured |
| LMArena Text | Not measured | 1354 | Only Mercury 2 measured |
| LMArena Text: instruction following | Not measured | 1328 | Only Mercury 2 measured |
| LMArena Text: creative writing | Not measured | 1286 | Only Mercury 2 measured |
| LMArena Text: English | Not measured | 1378 | Only Mercury 2 measured |
| LMArena Text: non-English | Not measured | 1330 | Only Mercury 2 measured |
| LMArena Text: Chinese | Not measured | 1414 | Only Mercury 2 measured |
| LMArena Text: Russian | Not measured | 1304 | Only Mercury 2 measured |
| LMArena Text: multi-turn | Not measured | 1357 | Only Mercury 2 measured |
| LMArena Text: longer queries | Not measured | 1329 | Only Mercury 2 measured |
| LMArena Text: writing and language | Not measured | 1300 | Only Mercury 2 measured |
| LMArena Text: entertainment and media | Not measured | 1314 | Only Mercury 2 measured |
| Neither model has a result on the other 33 boards here | |||
Image generationNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
| Benchmark | GPT-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 | OpenAI GPT-5 Pro | Inception Mercury 2 |
|---|---|---|
| Maker | OpenAI | Inception |
| Weights | No public weights listed | No public weights listed |
| Released | October 6, 2025 | March 4, 2026 |
| Context window | 400K | 128K |
| Input $/Mtok | $15.00 | $0.25 |
| Output $/Mtok | $120.00 | $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 GPT-5 Pro better than Mercury 2 for coding?
Neither model has a coding score yet, so the two cannot be ranked on coding. Pick GPT-5 Pro for a larger context window (400K against 128K tokens).
Which is cheaper, GPT-5 Pro or Mercury 2?
GPT-5 Pro costs $15.00 per million input tokens and $120.00 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-5 Pro or Mercury 2?
GPT-5 Pro, with 400K tokens against 128K.
How many benchmarks is the GPT-5 Pro vs Mercury 2 comparison based on?
1 benchmarks have a result for both models as of October 21, 2026. GPT-5 Pro'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.