GPT-5 Mini vs Mercury 2.5
GPT-5 Mini leads Mercury 2.5 on coding, 34.2 to 1.6 on the Vibe Coding Index, and Mercury 2.5 costs 13.3x less per output token ($0.15 vs $2.00 per million). Updated October 21, 2026; 9 benchmarks have a result for both.
GPT-5 Mini or Mercury 2.5: which to pick
Pick GPT-5 Mini for coding: it scores 34.2 on the Vibe Coding Index against 1.6 for Mercury 2.5.
Pick Mercury 2.5 for output tokens 13.3x cheaper ($0.15 vs $2.00 per million) and work measured by LegalBench (Vals AI), where it leads.
- Shared results
- 9
- GPT-5 Mini only
- 92
- Mercury 2.5 only
- 13
- 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 Mini
GPT-5 Mini scores 34.2 against 1.6.
2 benchmarks behind each score
Intelligence
AA Intelligence Index
GPT-5 Mini
GPT-5 Mini leads, 20.6 against 12.3.
Same board, both measured
Reasoning
GPQA Diamond
No call
Only GPT-5 Mini has a GPQA Diamond result, 80.3%.
Directional only
Math
AIME
No call
Only GPT-5 Mini has a AIME result, 91.5%.
Directional only
Knowledge
MMLU Pro
No call
Only GPT-5 Mini has a MMLU Pro result, 82.2%.
Directional only
Web design
Design Arena: websites
No call
Only GPT-5 Mini has a Design Arena: websites result, 1125.
Directional only
Long documents
Listed context window
GPT-5 Mini
GPT-5 Mini takes 400K tokens against 260K.
Listed by OpenRouter
Everyday cost
1K input + 500 output tokens
Mercury 2.5
GPT-5 Mini $0.0013, Mercury 2.5 $0.0001 per turn.
List prices
Cost per solved task
One SWE-bench Verified task, solved
No call
Only GPT-5 Mini has the number, $0.08.
Directional only
At a glance
- Coding index
- GPT-5 Mini 34.2 from 2 benchmarks, Mercury 2.5 1.6 from 2 benchmarks.
- Widest category
- General, 13.1 points apart on average over 2 shared benchmarks.
- Widest single gap
- MedScribe (Vals AI): GPT-5 Mini 80.6% against Mercury 2.5 55.1%, 25.5 points apart on a 0 to 100 scale.
- Output price
- GPT-5 Mini $2.00 against Mercury 2.5 $0.15 per million output tokens, 13.3x apart.
- Context window
- GPT-5 Mini 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 Mini | Bars | Mercury 2.5 | Ties |
|---|---|---|---|---|
| Coding | 2 | 0 | ||
| Intelligence | 1 | 0 | ||
| Reasoning | 1 | 0 | ||
| Math | 1 | 0 | ||
| Knowledge | 1 | 1 | ||
| General | 2 | 0 | ||
| All shared boards | 8 | 1 |
CodingLike-for-likeSix of these boards feed the Vibe Coding Index20
| Benchmark | GPT-5 Mini | Mercury 2.5 | Leader |
|---|---|---|---|
| SWE-bench Verified | 59.8% | Not measured | Only GPT-5 Mini measured |
| SWE-bench Multilingual | 39.7% | Not measured | Only GPT-5 Mini measured |
| LiveCodeBench (Vals AI) | 86.6% | Not measured | Only GPT-5 Mini measured |
| SWE-bench Verified (Vals AI) | 60.8% | Not measured | Only GPT-5 Mini measured |
| Terminal-Bench 4 (Vals AI) | Not measured | 0.0% | Only Mercury 2.5 measured |
| Vibe Code Bench (Vals AI) | 14.2% | 3.7% | GPT-5 Mini |
| Code migration (Vals AI) | Not measured | 4.5% | Only Mercury 2.5 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) | Not measured | 18.1% | Only Mercury 2.5 measured |
| CyberBench (Vals AI) | Not measured | 45.5% | Only Mercury 2.5 measured |
| LiveCodeBench (Artificial Analysis run) | 83.8% | Not measured | Only GPT-5 Mini measured |
| SciCode | 39.0% | 38.5% | GPT-5 Mini |
| Terminal-Bench Hard (Artificial Analysis run) | 33.3% | Not measured | Only GPT-5 Mini measured |
| Terminal-Bench | 34.8% | Not measured | Only GPT-5 Mini measured |
| WeirdML | 52.7% | Not measured | Only GPT-5 Mini measured |
| ALE-Bench | Not measured | 301.6 | Only Mercury 2.5 measured |
| LMArena Text: coding | 1406 | Not measured | Only GPT-5 Mini measured |
| LMArena Text: software and IT | 1394 | Not measured | Only GPT-5 Mini measured |
| Neither model has a result on the other 20 boards here | |||
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index10
| Benchmark | GPT-5 Mini | Mercury 2.5 | Leader |
|---|---|---|---|
| AA Intelligence Index | 20.6 | 12.3 | GPT-5 Mini |
| Epoch Capabilities Index | 145.3 | Not measured | Only GPT-5 Mini measured |
Agentic workDirectional onlyPublic boards, shown as published, kept out of the index8 boards, none shared
| Benchmark | GPT-5 Mini | Mercury 2.5 | Leader |
|---|---|---|---|
| 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 | 71.1% | Not measured | Only GPT-5 Mini measured |
| Vending-Bench 2 | -$31 | Not measured | Only GPT-5 Mini measured |
| Berkeley Function Calling Leaderboard (BFCL) | 55.5% | Not measured | Only GPT-5 Mini measured |
| Neither model has a result on the other 33 boards here | |||
ReasoningLike-for-likePublic boards, shown as published, kept out of the index10
| Benchmark | GPT-5 Mini | Mercury 2.5 | Leader |
|---|---|---|---|
| GPQA Diamond | 80.3% | Not measured | Only GPT-5 Mini measured |
| MMMU Pro (Vals AI) | 78.9% | Not measured | Only GPT-5 Mini measured |
| GPQA Diamond (Artificial Analysis run) | 82.8% | Not measured | Only GPT-5 Mini measured |
| Humanity's Last Exam (Artificial Analysis run) | 21.5% | 11.8% | GPT-5 Mini |
| GPQA Diamond (Epoch AI run) | 75.0% | Not measured | Only GPT-5 Mini measured |
| ARC-AGI | 54.3% | Not measured | Only GPT-5 Mini measured |
| ARC-AGI-2 | 4.4% | Not measured | Only GPT-5 Mini measured |
| Chess puzzles | 24.0% | Not measured | Only GPT-5 Mini measured |
| Mystery game puzzles | 10.0% | Not measured | Only GPT-5 Mini measured |
| VPCT | 40.2% | Not measured | Only GPT-5 Mini measured |
| LMArena Text: hard prompts | 1380 | Not measured | Only GPT-5 Mini measured |
| LMArena Text: expert | 1379 | Not measured | Only GPT-5 Mini measured |
| LMArena Text: hard prompts in English | 1383 | Not measured | Only GPT-5 Mini measured |
| LMArena Vision: diagrams | 1202 | Not measured | Only GPT-5 Mini measured |
| LMArena Vision: homework | 1210 | Not measured | Only GPT-5 Mini measured |
| Kagi LLM Benchmark | 70.3% | Not measured | Only GPT-5 Mini 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 Mini | Mercury 2.5 | Leader |
|---|---|---|---|
| AIME | 91.5% | Not measured | Only GPT-5 Mini measured |
| MATH 500 (Vals AI) | 94.8% | Not measured | Only GPT-5 Mini measured |
| MGSM (Vals AI) | 92.6% | Not measured | Only GPT-5 Mini measured |
| AA Math Index | 90.7 | Not measured | Only GPT-5 Mini measured |
| AIME 2025 (Artificial Analysis run) | 90.7% | Not measured | Only GPT-5 Mini measured |
| OTIS Mock AIME | 86.7% | Not measured | Only GPT-5 Mini measured |
| FrontierMath, tiers 1 to 3 | 46.7% | Not measured | Only GPT-5 Mini measured |
| FrontierMath, tier 4 | 12.2% | Not measured | Only GPT-5 Mini measured |
| ProofBench | 9.0% | 3.0% | GPT-5 Mini |
| MATH level 5 | 97.8% | Not measured | Only GPT-5 Mini measured |
| LMArena Text: math | 1378 | Not measured | Only GPT-5 Mini measured |
| LMArena Text: mathematical work | 1380 | Not measured | Only GPT-5 Mini measured |
| Neither model has a result on the other 1 board here | |||
KnowledgeLike-for-likePublic boards, shown as published, kept out of the index11
| Benchmark | GPT-5 Mini | Mercury 2.5 | Leader |
|---|---|---|---|
| MMLU Pro | 82.2% | Not measured | Only GPT-5 Mini measured |
| LegalBench (Vals AI) | 81.8% | 83.1% | Mercury 2.5 |
| CaseLaw (Vals AI) | 68.5% | Not measured | Only GPT-5 Mini measured |
| CorpFin (Vals AI) | 60.2% | Not measured | Only GPT-5 Mini measured |
| TaxEval (Vals AI) | 75.2% | Not measured | Only GPT-5 Mini measured |
| MortgageTax (Vals AI) | 66.9% | Not measured | Only GPT-5 Mini measured |
| MedQA (Vals AI) | 96.1% | Not measured | Only GPT-5 Mini measured |
| MedCode (Vals AI) | 43.0% | 31.3% | GPT-5 Mini |
| MMLU Pro (Artificial Analysis run) | 83.7% | Not measured | Only GPT-5 Mini measured |
| SimpleQA Verified | 21.6% | Not measured | Only GPT-5 Mini measured |
| LMArena Text: science | 1371 | Not measured | Only GPT-5 Mini measured |
| LMArena Text: medicine and healthcare | 1380 | Not measured | Only GPT-5 Mini measured |
| LMArena Text: legal and government | 1375 | Not measured | Only GPT-5 Mini measured |
| LMArena Text: business and finance | 1358 | Not measured | Only GPT-5 Mini measured |
| FACTS Benchmark Suite | 38.6% | Not measured | Only GPT-5 Mini measured |
| Neither model has a result on the other 3 boards here | |||
Web designDirectional onlyPublic boards, shown as published, kept out of the index8 boards, none shared
| Benchmark | GPT-5 Mini | Mercury 2.5 | Leader |
|---|---|---|---|
| Design Arena: websites | 1125 | Not measured | Only GPT-5 Mini measured |
| Design Arena: UI components | 1106 | Not measured | Only GPT-5 Mini measured |
| Design Arena: game dev | 1130 | Not measured | Only GPT-5 Mini measured |
| Design Arena: data viz | 1130 | Not measured | Only GPT-5 Mini measured |
| Design Arena: 3D | 1037 | Not measured | Only GPT-5 Mini measured |
| Design Arena: all code categories | 1115 | Not measured | Only GPT-5 Mini measured |
| Design Arena: SVG | 1091 | Not measured | Only GPT-5 Mini measured |
| Design Arena: ASCII art | 1125 | Not measured | Only GPT-5 Mini 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 Mini | Mercury 2.5 | Leader |
|---|---|---|---|
| Public Benefits Bench (Vals AI) | Not measured | 45.3% | Only Mercury 2.5 measured |
| SAGE (Vals AI) | 43.0% | Not measured | Only GPT-5 Mini measured |
| MedScribe (Vals AI) | 80.6% | 55.1% | GPT-5 Mini |
| IFBench | 75.4% | Not measured | Only GPT-5 Mini measured |
| Long context reasoning (AA-LCR) | 72.3% | 71.7% | GPT-5 Mini |
| DTBench | 80.5% | Not measured | Only GPT-5 Mini measured |
| LMCA | 34.2% | Not measured | Only GPT-5 Mini measured |
| Fiction.LiveBench | 69.4% | Not measured | Only GPT-5 Mini measured |
| Creative writing (Lech Mazur) | 83.1% | Not measured | Only GPT-5 Mini measured |
| LMArena Text | 1373 | Not measured | Only GPT-5 Mini measured |
| LMArena Text: instruction following | 1357 | Not measured | Only GPT-5 Mini measured |
| LMArena Text: creative writing | 1325 | Not measured | Only GPT-5 Mini measured |
| LMArena Vision | 1202 | Not measured | Only GPT-5 Mini measured |
| LMArena Text: English | 1379 | Not measured | Only GPT-5 Mini measured |
| LMArena Text: non-English | 1363 | Not measured | Only GPT-5 Mini measured |
| LMArena Text: Chinese | 1386 | Not measured | Only GPT-5 Mini measured |
| LMArena Text: German | 1366 | Not measured | Only GPT-5 Mini measured |
| LMArena Text: Japanese | 1341 | Not measured | Only GPT-5 Mini measured |
| LMArena Text: Korean | 1308 | Not measured | Only GPT-5 Mini measured |
| LMArena Text: French | 1386 | Not measured | Only GPT-5 Mini measured |
| LMArena Text: Spanish | 1354 | Not measured | Only GPT-5 Mini measured |
| LMArena Text: Russian | 1362 | Not measured | Only GPT-5 Mini measured |
| LMArena Text: Polish | 1378 | Not measured | Only GPT-5 Mini measured |
| LMArena Text: multi-turn | 1363 | Not measured | Only GPT-5 Mini measured |
| LMArena Text: longer queries | 1355 | Not measured | Only GPT-5 Mini measured |
| LMArena Text: writing and language | 1344 | Not measured | Only GPT-5 Mini measured |
| LMArena Text: entertainment and media | 1340 | Not measured | Only GPT-5 Mini measured |
| LMArena Vision: English | 1216 | Not measured | Only GPT-5 Mini measured |
| LMArena Vision: Chinese | 1214 | Not measured | Only GPT-5 Mini measured |
| LMArena Vision: reading text | 1199 | Not measured | Only GPT-5 Mini measured |
| LMArena Vision: humor | 1205 | Not measured | Only GPT-5 Mini measured |
| LMArena Vision: captioning | 1217 | Not measured | Only GPT-5 Mini measured |
| LMArena Vision: recognizing things | 1226 | Not measured | Only GPT-5 Mini measured |
| LMArena Vision: creative writing | 1181 | Not measured | Only GPT-5 Mini measured |
| Neither model has a result on the other 12 boards here | |||
Image generationNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
| Benchmark | GPT-5 Mini | 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 Mini | Inception Mercury 2.5 |
|---|---|---|
| Maker | OpenAI | Inception |
| Weights | No public weights listed | No public weights listed |
| Released | August 7, 2025 | September 8, 2026 |
| Context window | 400K | 260K |
| Input $/Mtok | $0.25 | $0.04 |
| Output $/Mtok | $2.00 | $0.15 |
| Coding index | 34.2 | 1.6 |
| Independent measurements behind it | 2 | 2 |
| Cost per solved task | $0.08 | Not computable |
| Source | OpenRouter listing | OpenRouter listing |
Questions
Is GPT-5 Mini better than Mercury 2.5 for coding?
Pick GPT-5 Mini for coding: it scores 34.2 on the Vibe Coding Index against 1.6 for Mercury 2.5. Pick Mercury 2.5 for output tokens 13.3x cheaper ($0.15 vs $2.00 per million) and work measured by LegalBench (Vals AI), where it leads.
Which is cheaper, GPT-5 Mini or Mercury 2.5?
GPT-5 Mini costs $0.25 per million input tokens and $2.00 per million output tokens; Mercury 2.5 costs $0.04 and $0.15. Cost per solved task is known for GPT-5 Mini only.
Which has the bigger context window, GPT-5 Mini or Mercury 2.5?
GPT-5 Mini, with 400K tokens against 260K.
How many benchmarks is the GPT-5 Mini vs Mercury 2.5 comparison based on?
9 benchmarks have a result for both models as of October 21, 2026. GPT-5 Mini'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.