GPT-5.4 vs Mercury 2.5
GPT-5.4 leads Mercury 2.5 on coding, 64.4 to 1.6 on the Vibe Coding Index, and Mercury 2.5 costs 100.0x less per output token ($0.15 vs $15.00 per million). Updated October 22, 2026; 11 benchmarks have a result for both.
GPT-5.4 or Mercury 2.5: which to pick
Pick GPT-5.4 for coding: it scores 64.4 on the Vibe Coding Index against 1.6 for Mercury 2.5.
Pick Mercury 2.5 for output tokens 100.0x cheaper ($0.15 vs $15.00 per million).
- Shared results
- 11
- GPT-5.4 only
- 99
- Mercury 2.5 only
- 11
- 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
GPT-5.4
GPT-5.4 scores 64.4 against 1.6.
3 and 2 benchmarks behind the scores
Intelligence
AA Intelligence Index
GPT-5.4
GPT-5.4 leads, 39.0 against 12.3.
Same board, both measured
Reasoning
GPQA Diamond
No call
Only GPT-5.4 has a GPQA Diamond result, 91.7%.
Directional only
Math
AIME
No call
Only GPT-5.4 has a AIME result, 96.7%.
Directional only
Knowledge
MMLU Pro
No call
Only GPT-5.4 has a MMLU Pro result, 87.5%.
Directional only
Web design
Design Arena: websites
No call
Only GPT-5.4 has a Design Arena: websites result, 1198.
Directional only
Long documents
Listed context window
GPT-5.4
GPT-5.4 takes 1.05M tokens against 260K.
Listed by OpenRouter
Everyday cost
1K input + 500 output tokens
Mercury 2.5
GPT-5.4 $0.010, Mercury 2.5 $0.0001 per turn.
List prices
Cost per solved task
One SWE-bench Verified task, solved
No call
Only GPT-5.4 has the number, $1.02.
Directional only
At a glance
- Coding index
- GPT-5.4 64.4 from 3 benchmarks, Mercury 2.5 1.6 from 2 benchmarks.
- Widest category
- Math, 53.0 points apart on average over 1 shared benchmark.
- Widest single gap
- Vibe Code Bench (Vals AI): GPT-5.4 67.4% against Mercury 2.5 3.7%, 63.7 points apart on a 0 to 100 scale.
- Output price
- GPT-5.4 $15.00 against Mercury 2.5 $0.15 per million output tokens, 100.0x apart.
- Context window
- GPT-5.4 takes 1.05M tokens, Mercury 2.5 260K.
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-5.4 | Bars | Mercury 2.5 | Ties |
|---|---|---|---|---|
| Coding | 4 | 0 | ||
| Intelligence | 1 | 0 | ||
| Reasoning | 1 | 0 | ||
| Math | 1 | 0 | ||
| Knowledge | 2 | 0 | ||
| General | 2 | 0 | ||
| All shared boards | 11 | 0 |
CodingLike-for-likeSix of these boards feed the Vibe Coding Index40
| Benchmark | GPT-5.4 | Mercury 2.5 | Leader |
|---|---|---|---|
| LMArena WebDev | 1464 | Not measured | Only GPT-5.4 measured |
| AA Coding Index | 71.1 | Not measured | Only GPT-5.4 measured |
| LiveCodeBench (Vals AI) | 84.1% | Not measured | Only GPT-5.4 measured |
| SWE-bench Verified (Vals AI) | 78.2% | Not measured | Only GPT-5.4 measured |
| Terminal-Bench 4 (Vals AI) | Not measured | 0.0% | Only Mercury 2.5 measured |
| Vibe Code Bench (Vals AI) | 67.4% | 3.7% | GPT-5.4 |
| Code migration (Vals AI) | 35.0% | 4.5% | GPT-5.4 |
| ProgramBench (Vals AI) | 0.5% | Not measured | Only GPT-5.4 measured |
| IOI (Vals AI) | Not measured | 2.4% | Only Mercury 2.5 measured |
| Terminal-Bench 2.1 (Vals AI) | Not measured | 34.5% | Only Mercury 2.5 measured |
| SkillsBench (Vals AI) | 51.7% | 18.1% | GPT-5.4 |
| CyberBench (Vals AI) | Not measured | 45.5% | Only Mercury 2.5 measured |
| SciCode | Not measured | 38.5% | Only Mercury 2.5 measured |
| Terminal-Bench Hard (Artificial Analysis run) | 57.6% | Not measured | Only GPT-5.4 measured |
| Terminal-Bench | 81.8% | Not measured | Only GPT-5.4 measured |
| GSO-Bench | 31.4% | Not measured | Only GPT-5.4 measured |
| WeirdML | 77.7% | Not measured | Only GPT-5.4 measured |
| MirrorCode | 15.6% | Not measured | Only GPT-5.4 measured |
| ALE-Bench | 1607.0 | 301.6 | GPT-5.4 |
| LMArena Text: coding | 1496 | Not measured | Only GPT-5.4 measured |
| LMArena Text: software and IT | 1491 | Not measured | Only GPT-5.4 measured |
| LMArena WebDev: React | 1454 | Not measured | Only GPT-5.4 measured |
| LMArena WebDev: HTML | 1478 | Not measured | Only GPT-5.4 measured |
| LMArena WebDev: from an image | 1436 | Not measured | Only GPT-5.4 measured |
| Neither model has a result on the other 15 boards here | |||
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index10
| Benchmark | GPT-5.4 | Mercury 2.5 | Leader |
|---|---|---|---|
| AA Intelligence Index | 39.0 | 12.3 | GPT-5.4 |
| Epoch Capabilities Index | 157.3 | Not measured | Only GPT-5.4 measured |
Agentic workDirectional onlyPublic boards, shown as published, kept out of the index16 boards, none shared
| Benchmark | GPT-5.4 | Mercury 2.5 | Leader |
|---|---|---|---|
| Design Arena: agents building web apps | 1059 | Not measured | Only GPT-5.4 measured |
| Design Arena: agents building full-stack apps | 1017 | Not measured | Only GPT-5.4 measured |
| Design Arena: agents building mobile apps | 1087 | Not measured | Only GPT-5.4 measured |
| Design Arena: agents building Android apps | 1031 | Not measured | Only GPT-5.4 measured |
| Design Arena: agents building Godot games | 1135 | Not measured | Only GPT-5.4 measured |
| Finance Agent (Vals AI) | Not measured | 18.9% | Only Mercury 2.5 measured |
| Tax Agent Bench (Vals AI) | Not measured | 2.5% | Only Mercury 2.5 measured |
| Legal Research Bench (Vals AI) | Not measured | 4.3% | Only Mercury 2.5 measured |
| Excel Modeling Benchmark (Vals AI) | Not measured | 8.8% | Only Mercury 2.5 measured |
| Terminal-Bench-Science (Vals AI) | Not measured | 0.0% | Only Mercury 2.5 measured |
| τ²-Bench Telecom | 87.1% | Not measured | Only GPT-5.4 measured |
| APEX-Agents | 52.4% | Not measured | Only GPT-5.4 measured |
| METR time horizons | 74.3% | Not measured | Only GPT-5.4 measured |
| DeepResearch Bench | 35.1% | Not measured | Only GPT-5.4 measured |
| PostTrainBench | 19.0% | Not measured | Only GPT-5.4 measured |
| Vending-Bench 2 | $6,144 | Not measured | Only GPT-5.4 measured |
| Neither model has a result on the other 25 boards here | |||
ReasoningLike-for-likePublic boards, shown as published, kept out of the index10
| Benchmark | GPT-5.4 | Mercury 2.5 | Leader |
|---|---|---|---|
| GPQA Diamond | 91.7% | Not measured | Only GPT-5.4 measured |
| MMMU Pro (Vals AI) | 87.5% | Not measured | Only GPT-5.4 measured |
| GPQA Diamond (Artificial Analysis run) | 92.0% | Not measured | Only GPT-5.4 measured |
| Humanity's Last Exam (Artificial Analysis run) | 43.7% | 11.8% | GPT-5.4 |
| GPQA Diamond (Epoch AI run) | 93.3% | Not measured | Only GPT-5.4 measured |
| ARC-AGI | 93.7% | Not measured | Only GPT-5.4 measured |
| ARC-AGI-2 | 74.0% | Not measured | Only GPT-5.4 measured |
| Chess puzzles | 48.0% | Not measured | Only GPT-5.4 measured |
| Mystery game puzzles | 37.0% | Not measured | Only GPT-5.4 measured |
| EBR-bench | 25.4% | Not measured | Only GPT-5.4 measured |
| LMArena Text: hard prompts | 1485 | Not measured | Only GPT-5.4 measured |
| LMArena Text: expert | 1507 | Not measured | Only GPT-5.4 measured |
| LMArena Text: hard prompts in English | 1479 | Not measured | Only GPT-5.4 measured |
| LMArena Vision: diagrams | 1327 | Not measured | Only GPT-5.4 measured |
| LMArena Vision: homework | 1336 | Not measured | Only GPT-5.4 measured |
| Kagi LLM Benchmark | 63.8% | Not measured | Only GPT-5.4 measured |
| Neither model has a result on the other 6 boards here | |||
MathLike-for-likePublic boards, shown as published, kept out of the index10
| Benchmark | GPT-5.4 | Mercury 2.5 | Leader |
|---|---|---|---|
| AIME | 96.7% | Not measured | Only GPT-5.4 measured |
| OTIS Mock AIME | 97.8% | Not measured | Only GPT-5.4 measured |
| FrontierMath, tiers 1 to 3 | 78.6% | Not measured | Only GPT-5.4 measured |
| FrontierMath, tier 4 | 49.0% | Not measured | Only GPT-5.4 measured |
| ProofBench | 56.0% | 3.0% | GPT-5.4 |
| LMArena Text: math | 1488 | Not measured | Only GPT-5.4 measured |
| LMArena Text: mathematical work | 1497 | Not measured | Only GPT-5.4 measured |
| Neither model has a result on the other 6 boards here | |||
KnowledgeLike-for-likePublic boards, shown as published, kept out of the index20
| Benchmark | GPT-5.4 | Mercury 2.5 | Leader |
|---|---|---|---|
| MMLU Pro | 87.5% | Not measured | Only GPT-5.4 measured |
| LegalBench (Vals AI) | 86.0% | 83.1% | GPT-5.4 |
| CaseLaw (Vals AI) | 63.8% | Not measured | Only GPT-5.4 measured |
| CorpFin (Vals AI) | 65.3% | Not measured | Only GPT-5.4 measured |
| TaxEval (Vals AI) | 74.0% | Not measured | Only GPT-5.4 measured |
| MortgageTax (Vals AI) | 68.3% | Not measured | Only GPT-5.4 measured |
| MedQA (Vals AI) | 96.1% | Not measured | Only GPT-5.4 measured |
| MedCode (Vals AI) | 41.3% | 31.3% | GPT-5.4 |
| SimpleQA Verified | 45.1% | Not measured | Only GPT-5.4 measured |
| LMArena Text: science | 1479 | Not measured | Only GPT-5.4 measured |
| LMArena Text: medicine and healthcare | 1458 | Not measured | Only GPT-5.4 measured |
| LMArena Text: legal and government | 1486 | Not measured | Only GPT-5.4 measured |
| LMArena Text: business and finance | 1474 | Not measured | Only GPT-5.4 measured |
| Neither model has a result on the other 5 boards here | |||
Web designDirectional onlyPublic boards, shown as published, kept out of the index8 boards, none shared
| Benchmark | GPT-5.4 | Mercury 2.5 | Leader |
|---|---|---|---|
| Design Arena: websites | 1198 | Not measured | Only GPT-5.4 measured |
| Design Arena: UI components | 1212 | Not measured | Only GPT-5.4 measured |
| Design Arena: game dev | 1194 | Not measured | Only GPT-5.4 measured |
| Design Arena: data viz | 1196 | Not measured | Only GPT-5.4 measured |
| Design Arena: 3D | 1065 | Not measured | Only GPT-5.4 measured |
| Design Arena: all code categories | 1179 | Not measured | Only GPT-5.4 measured |
| Design Arena: SVG | 1141 | Not measured | Only GPT-5.4 measured |
| Design Arena: ASCII art | 1188 | Not measured | Only GPT-5.4 measured |
| Neither model has a result on the other 1 board here | |||
GeneralLike-for-likePublic boards, shown as published, kept out of the index20
| Benchmark | GPT-5.4 | Mercury 2.5 | Leader |
|---|---|---|---|
| Public Benefits Bench (Vals AI) | Not measured | 45.3% | Only Mercury 2.5 measured |
| SAGE (Vals AI) | 43.3% | Not measured | Only GPT-5.4 measured |
| MedScribe (Vals AI) | 77.5% | 55.1% | GPT-5.4 |
| IFBench | 73.9% | Not measured | Only GPT-5.4 measured |
| Long context reasoning (AA-LCR) | 82.0% | 71.7% | GPT-5.4 |
| DTBench | 94.4% | Not measured | Only GPT-5.4 measured |
| LMCA | 52.0% | Not measured | Only GPT-5.4 measured |
| CL-bench | 27.9% | Not measured | Only GPT-5.4 measured |
| Furniture assembly | 37.5% | Not measured | Only GPT-5.4 measured |
| CL-bench Life | 21.7% | Not measured | Only GPT-5.4 measured |
| LMArena Text | 1469 | Not measured | Only GPT-5.4 measured |
| LMArena Text: instruction following | 1469 | Not measured | Only GPT-5.4 measured |
| LMArena Text: creative writing | 1439 | Not measured | Only GPT-5.4 measured |
| LMArena Vision | 1303 | Not measured | Only GPT-5.4 measured |
| LMArena Text: English | 1467 | Not measured | Only GPT-5.4 measured |
| LMArena Text: non-English | 1465 | Not measured | Only GPT-5.4 measured |
| LMArena Text: Chinese | 1520 | Not measured | Only GPT-5.4 measured |
| LMArena Text: German | 1472 | Not measured | Only GPT-5.4 measured |
| LMArena Text: Japanese | 1485 | Not measured | Only GPT-5.4 measured |
| LMArena Text: Korean | 1449 | Not measured | Only GPT-5.4 measured |
| LMArena Text: French | 1493 | Not measured | Only GPT-5.4 measured |
| LMArena Text: Spanish | 1452 | Not measured | Only GPT-5.4 measured |
| LMArena Text: Russian | 1480 | Not measured | Only GPT-5.4 measured |
| LMArena Text: Polish | 1472 | Not measured | Only GPT-5.4 measured |
| LMArena Text: multi-turn | 1482 | Not measured | Only GPT-5.4 measured |
| LMArena Text: longer queries | 1473 | Not measured | Only GPT-5.4 measured |
| LMArena Text: writing and language | 1458 | Not measured | Only GPT-5.4 measured |
| LMArena Text: entertainment and media | 1438 | Not measured | Only GPT-5.4 measured |
| LMArena Vision: English | 1301 | Not measured | Only GPT-5.4 measured |
| LMArena Vision: Chinese | 1354 | Not measured | Only GPT-5.4 measured |
| LMArena Vision: reading text | 1312 | Not measured | Only GPT-5.4 measured |
| LMArena Vision: humor | 1284 | Not measured | Only GPT-5.4 measured |
| LMArena Vision: recognizing things | 1251 | Not measured | Only GPT-5.4 measured |
| LMArena Vision: creative writing | 1283 | Not measured | Only GPT-5.4 measured |
| LMArena Document | 1471 | Not measured | Only GPT-5.4 measured |
| Neither model has a result on the other 11 boards here | |||
Image generationNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
| Benchmark | GPT-5.4 | Mercury 2.5 | 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 | OpenAI GPT-5.4 | Inception Mercury 2.5 |
|---|---|---|
| Maker | OpenAI | Inception |
| Weights | No public weights listed | No public weights listed |
| Released | March 5, 2026 | September 8, 2026 |
| Context window | 1.05M | 260K |
| Input $/Mtok | $2.50 | $0.04 |
| Output $/Mtok | $15.00 | $0.15 |
| Coding index | 64.4 | 1.6 |
| Independent measurements behind it | 3 | 2 |
| Cost per solved task | $1.02 | Not computable |
| Source | OpenRouter listing | OpenRouter listing |
Questions
Is GPT-5.4 better than Mercury 2.5 for coding?
Pick GPT-5.4 for coding: it scores 64.4 on the Vibe Coding Index against 1.6 for Mercury 2.5. Pick Mercury 2.5 for output tokens 100.0x cheaper ($0.15 vs $15.00 per million).
Which is cheaper, GPT-5.4 or Mercury 2.5?
GPT-5.4 costs $2.50 per million input tokens and $15.00 per million output tokens; Mercury 2.5 costs $0.04 and $0.15. Cost per solved task is known for GPT-5.4 only.
Which has the bigger context window, GPT-5.4 or Mercury 2.5?
GPT-5.4, with 1.05M tokens against 260K.
How many benchmarks is the GPT-5.4 vs Mercury 2.5 comparison based on?
11 benchmarks have a result for both models as of October 22, 2026. GPT-5.4's coding index rests on 3 independent benchmarks and Mercury 2.5's on 2. Where only one model has a result, the page says so instead of naming a winner.