GPT-5.4 Nano vs Mercury 2.5
GPT-5.4 Nano leads Mercury 2.5 on coding, 44.8 to 1.6 on the Vibe Coding Index, and Mercury 2.5 costs 8.3x less per output token ($0.15 vs $1.25 per million). Updated October 22, 2026; 16 benchmarks have a result for both.
GPT-5.4 Nano or Mercury 2.5: which to pick
Pick GPT-5.4 Nano for coding: it scores 44.8 on the Vibe Coding Index against 1.6 for Mercury 2.5.
Pick Mercury 2.5 for output tokens 8.3x cheaper ($0.15 vs $1.25 per million) and work measured by LegalBench (Vals AI), where it leads.
- Shared results
- 16
- GPT-5.4 Nano only
- 69
- Mercury 2.5 only
- 6
- 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
GPT-5.4 Nano
GPT-5.4 Nano scores 44.8 against 1.6.
2 benchmarks behind each score
Intelligence
AA Intelligence Index
GPT-5.4 Nano
GPT-5.4 Nano leads, 20.7 against 12.3.
Same board, both measured
Agentic work
AA Agentic Index
No call
Only GPT-5.4 Nano has a AA Agentic Index result, 16.0.
Directional only
Reasoning
GPQA Diamond
No call
Only GPT-5.4 Nano has a GPQA Diamond result, 77.5%.
Directional only
Math
AIME
No call
Only GPT-5.4 Nano has a AIME result, 88.8%.
Directional only
Knowledge
MMLU Pro
No call
Only GPT-5.4 Nano has a MMLU Pro result, 77.2%.
Directional only
Long documents
Listed context window
GPT-5.4 Nano
GPT-5.4 Nano takes 400K tokens against 260K.
Listed by OpenRouter
Everyday cost
1K input + 500 output tokens
Mercury 2.5
GPT-5.4 Nano $0.0008, 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 Nano has the number, $0.14.
Directional only
At a glance
- Coding index
- GPT-5.4 Nano 44.8 from 2 benchmarks, Mercury 2.5 1.6 from 2 benchmarks.
- Widest category
- Reasoning, 16.5 points apart on average over 1 shared benchmark.
- Widest single gap
- Excel Modeling Benchmark (Vals AI): GPT-5.4 Nano 44.8% against Mercury 2.5 8.8%, 36.0 points apart on a 0 to 100 scale.
- Output price
- GPT-5.4 Nano $1.25 against Mercury 2.5 $0.15 per million output tokens, 8.3x apart.
- Context window
- GPT-5.4 Nano takes 400K 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 Nano | Bars | Mercury 2.5 | Ties |
|---|---|---|---|---|
| Coding | 5 | 0 | ||
| Intelligence | 1 | 0 | ||
| Agentic work | 4 | 0 | ||
| Reasoning | 1 | 0 | ||
| Math | 1 | 0 | ||
| Knowledge | 1 | 1 | ||
| General | 2 | 0 | ||
| All shared boards | 15 | 1 |
CodingLike-for-likeSix of these boards feed the Vibe Coding Index50
| Benchmark | GPT-5.4 Nano | Mercury 2.5 | Leader |
|---|---|---|---|
| AA Coding Index | 56.1 | Not measured | Only GPT-5.4 Nano measured |
| LiveCodeBench (Vals AI) | 84.0% | Not measured | Only GPT-5.4 Nano measured |
| SWE-bench Verified (Vals AI) | 69.8% | Not measured | Only GPT-5.4 Nano measured |
| Terminal-Bench 4 (Vals AI) | Not measured | 0.0% | Only Mercury 2.5 measured |
| Vibe Code Bench (Vals AI) | 26.1% | 3.7% | GPT-5.4 Nano |
| Code migration (Vals AI) | 14.5% | 4.5% | GPT-5.4 Nano |
| IOI (Vals AI) | Not measured | 2.4% | Only Mercury 2.5 measured |
| Terminal-Bench 2.1 (Vals AI) | 41.6% | 34.5% | GPT-5.4 Nano |
| SkillsBench (Vals AI) | Not measured | 18.1% | Only Mercury 2.5 measured |
| CyberBench (Vals AI) | Not measured | 45.5% | Only Mercury 2.5 measured |
| SciCode | 47.2% | 38.5% | GPT-5.4 Nano |
| Terminal-Bench Hard (Artificial Analysis run) | 42.4% | Not measured | Only GPT-5.4 Nano measured |
| WeirdML | 49.2% | Not measured | Only GPT-5.4 Nano measured |
| ALE-Bench | 1004.5 | 301.6 | GPT-5.4 Nano |
| LMArena Text: coding | 1404 | Not measured | Only GPT-5.4 Nano measured |
| LMArena Text: software and IT | 1402 | Not measured | Only GPT-5.4 Nano measured |
| Neither model has a result on the other 23 boards here | |||
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index10
| Benchmark | GPT-5.4 Nano | Mercury 2.5 | Leader |
|---|---|---|---|
| AA Intelligence Index | 20.7 | 12.3 | GPT-5.4 Nano |
| Epoch Capabilities Index | 146.0 | Not measured | Only GPT-5.4 Nano measured |
Agentic workLike-for-likePublic boards, shown as published, kept out of the index40
| Benchmark | GPT-5.4 Nano | Mercury 2.5 | Leader |
|---|---|---|---|
| AA Agentic Index | 16.0 | Not measured | Only GPT-5.4 Nano measured |
| Finance Agent (Vals AI) | 38.2% | 18.9% | GPT-5.4 Nano |
| Tax Agent Bench (Vals AI) | 5.0% | 2.5% | GPT-5.4 Nano |
| Legal Research Bench (Vals AI) | 6.3% | 4.3% | GPT-5.4 Nano |
| Excel Modeling Benchmark (Vals AI) | 44.8% | 8.8% | GPT-5.4 Nano |
| Terminal-Bench-Science (Vals AI) | Not measured | 0.0% | Only Mercury 2.5 measured |
| τ²-Bench Telecom | 76.0% | Not measured | Only GPT-5.4 Nano measured |
| Neither model has a result on the other 34 boards here | |||
ReasoningLike-for-likePublic boards, shown as published, kept out of the index10
| Benchmark | GPT-5.4 Nano | Mercury 2.5 | Leader |
|---|---|---|---|
| GPQA Diamond | 77.5% | Not measured | Only GPT-5.4 Nano measured |
| MMMU Pro (Vals AI) | 73.6% | Not measured | Only GPT-5.4 Nano measured |
| GPQA Diamond (Artificial Analysis run) | 81.7% | Not measured | Only GPT-5.4 Nano measured |
| Humanity's Last Exam (Artificial Analysis run) | 28.3% | 11.8% | GPT-5.4 Nano |
| GPQA Diamond (Epoch AI run) | 78.5% | Not measured | Only GPT-5.4 Nano measured |
| ARC-AGI | 51.5% | Not measured | Only GPT-5.4 Nano measured |
| ARC-AGI-2 | 5.7% | Not measured | Only GPT-5.4 Nano measured |
| Chess puzzles | 45.0% | Not measured | Only GPT-5.4 Nano measured |
| Mystery game puzzles | 9.0% | Not measured | Only GPT-5.4 Nano measured |
| LMArena Text: hard prompts | 1381 | Not measured | Only GPT-5.4 Nano measured |
| LMArena Text: expert | 1396 | Not measured | Only GPT-5.4 Nano measured |
| LMArena Text: hard prompts in English | 1387 | Not measured | Only GPT-5.4 Nano measured |
| LMArena Vision: diagrams | 1210 | Not measured | Only GPT-5.4 Nano measured |
| LMArena Vision: homework | 1225 | Not measured | Only GPT-5.4 Nano measured |
| Kagi LLM Benchmark | 39.7% | Not measured | Only GPT-5.4 Nano measured |
| Neither model has a result on the other 7 boards here | |||
MathLike-for-likePublic boards, shown as published, kept out of the index10
| Benchmark | GPT-5.4 Nano | Mercury 2.5 | Leader |
|---|---|---|---|
| AIME | 88.8% | Not measured | Only GPT-5.4 Nano measured |
| OTIS Mock AIME | 87.8% | Not measured | Only GPT-5.4 Nano measured |
| FrontierMath, tiers 1 to 3 | 44.9% | Not measured | Only GPT-5.4 Nano measured |
| FrontierMath, tier 4 | 12.2% | Not measured | Only GPT-5.4 Nano measured |
| ProofBench | 5.0% | 3.0% | GPT-5.4 Nano |
| LMArena Text: math | 1405 | Not measured | Only GPT-5.4 Nano measured |
| LMArena Text: mathematical work | 1409 | Not measured | Only GPT-5.4 Nano measured |
| Neither model has a result on the other 6 boards here | |||
KnowledgeLike-for-likePublic boards, shown as published, kept out of the index11
| Benchmark | GPT-5.4 Nano | Mercury 2.5 | Leader |
|---|---|---|---|
| MMLU Pro | 77.2% | Not measured | Only GPT-5.4 Nano measured |
| LegalBench (Vals AI) | 77.9% | 83.1% | Mercury 2.5 |
| CaseLaw (Vals AI) | 51.9% | Not measured | Only GPT-5.4 Nano measured |
| CorpFin (Vals AI) | 61.2% | Not measured | Only GPT-5.4 Nano measured |
| TaxEval (Vals AI) | 67.4% | Not measured | Only GPT-5.4 Nano measured |
| MortgageTax (Vals AI) | 59.1% | Not measured | Only GPT-5.4 Nano measured |
| MedCode (Vals AI) | 41.0% | 31.3% | GPT-5.4 Nano |
| SimpleQA Verified | 11.7% | Not measured | Only GPT-5.4 Nano measured |
| LMArena Text: science | 1374 | Not measured | Only GPT-5.4 Nano measured |
| LMArena Text: medicine and healthcare | 1369 | Not measured | Only GPT-5.4 Nano measured |
| LMArena Text: legal and government | 1368 | Not measured | Only GPT-5.4 Nano measured |
| LMArena Text: business and finance | 1366 | Not measured | Only GPT-5.4 Nano measured |
| Neither model has a result on the other 6 boards here | |||
Web designNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
| Benchmark | GPT-5.4 Nano | Mercury 2.5 | Leader |
|---|---|---|---|
| Neither model has a result on 9 boards here | |||
GeneralLike-for-likePublic boards, shown as published, kept out of the index20
| Benchmark | GPT-5.4 Nano | Mercury 2.5 | Leader |
|---|---|---|---|
| Public Benefits Bench (Vals AI) | Not measured | 45.3% | Only Mercury 2.5 measured |
| SAGE (Vals AI) | 38.1% | Not measured | Only GPT-5.4 Nano measured |
| MedScribe (Vals AI) | 77.1% | 55.1% | GPT-5.4 Nano |
| Vals Multimodal Index | 47.6% | Not measured | Only GPT-5.4 Nano measured |
| IFBench | 75.9% | Not measured | Only GPT-5.4 Nano measured |
| Long context reasoning (AA-LCR) | 76.7% | 71.7% | GPT-5.4 Nano |
| DTBench | 80.3% | Not measured | Only GPT-5.4 Nano measured |
| LMCA | 36.9% | Not measured | Only GPT-5.4 Nano measured |
| LMArena Text | 1372 | Not measured | Only GPT-5.4 Nano measured |
| LMArena Text: instruction following | 1362 | Not measured | Only GPT-5.4 Nano measured |
| LMArena Text: creative writing | 1315 | Not measured | Only GPT-5.4 Nano measured |
| LMArena Vision | 1196 | Not measured | Only GPT-5.4 Nano measured |
| LMArena Text: English | 1381 | Not measured | Only GPT-5.4 Nano measured |
| LMArena Text: non-English | 1359 | Not measured | Only GPT-5.4 Nano measured |
| LMArena Text: Chinese | 1391 | Not measured | Only GPT-5.4 Nano measured |
| LMArena Text: German | 1368 | Not measured | Only GPT-5.4 Nano measured |
| LMArena Text: Japanese | 1343 | Not measured | Only GPT-5.4 Nano measured |
| LMArena Text: Korean | 1321 | Not measured | Only GPT-5.4 Nano measured |
| LMArena Text: French | 1395 | Not measured | Only GPT-5.4 Nano measured |
| LMArena Text: Spanish | 1371 | Not measured | Only GPT-5.4 Nano measured |
| LMArena Text: Russian | 1363 | Not measured | Only GPT-5.4 Nano measured |
| LMArena Text: Polish | 1366 | Not measured | Only GPT-5.4 Nano measured |
| LMArena Text: multi-turn | 1382 | Not measured | Only GPT-5.4 Nano measured |
| LMArena Text: longer queries | 1365 | Not measured | Only GPT-5.4 Nano measured |
| LMArena Text: writing and language | 1338 | Not measured | Only GPT-5.4 Nano measured |
| LMArena Text: entertainment and media | 1325 | Not measured | Only GPT-5.4 Nano measured |
| LMArena Vision: English | 1202 | Not measured | Only GPT-5.4 Nano measured |
| LMArena Vision: Chinese | 1232 | Not measured | Only GPT-5.4 Nano measured |
| LMArena Vision: reading text | 1204 | Not measured | Only GPT-5.4 Nano measured |
| LMArena Vision: humor | 1161 | Not measured | Only GPT-5.4 Nano measured |
| LMArena Vision: recognizing things | 1141 | Not measured | Only GPT-5.4 Nano measured |
| LMArena Vision: creative writing | 1159 | Not measured | Only GPT-5.4 Nano measured |
| Neither model has a result on the other 14 boards here | |||
Image generationNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
| Benchmark | GPT-5.4 Nano | 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 Nano | Inception Mercury 2.5 |
|---|---|---|
| Maker | OpenAI | Inception |
| Weights | No public weights listed | No public weights listed |
| Released | March 17, 2026 | September 8, 2026 |
| Context window | 400K | 260K |
| Input $/Mtok | $0.20 | $0.04 |
| Output $/Mtok | $1.25 | $0.15 |
| Coding index | 44.8 | 1.6 |
| Independent measurements behind it | 2 | 2 |
| Cost per solved task | $0.14 | Not computable |
| Source | OpenRouter listing | OpenRouter listing |
Questions
Is GPT-5.4 Nano better than Mercury 2.5 for coding?
Pick GPT-5.4 Nano for coding: it scores 44.8 on the Vibe Coding Index against 1.6 for Mercury 2.5. Pick Mercury 2.5 for output tokens 8.3x cheaper ($0.15 vs $1.25 per million) and work measured by LegalBench (Vals AI), where it leads.
Which is cheaper, GPT-5.4 Nano or Mercury 2.5?
GPT-5.4 Nano costs $0.20 per million input tokens and $1.25 per million output tokens; Mercury 2.5 costs $0.04 and $0.15. Cost per solved task is known for GPT-5.4 Nano only.
Which has the bigger context window, GPT-5.4 Nano or Mercury 2.5?
GPT-5.4 Nano, with 400K tokens against 260K.
How many benchmarks is the GPT-5.4 Nano vs Mercury 2.5 comparison based on?
16 benchmarks have a result for both models as of October 22, 2026. GPT-5.4 Nano's coding index rests on 2 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.