Gemini 2.5 Pro vs GPT-5.4 Mini
GPT-5.4 Mini leads Gemini 2.5 Pro on coding, 35.8 to 19.1 on the Vibe Coding Index, and GPT-5.4 Mini costs 2.2x less per output token ($4.50 vs $10.00 per million). Updated October 22, 2026; 67 benchmarks have a result for both.
Gemini 2.5 Pro or GPT-5.4 Mini: which to pick
Pick GPT-5.4 Mini for coding: it scores 35.8 on the Vibe Coding Index against 19.1 for Gemini 2.5 Pro.
Pick Gemini 2.5 Pro for a lower cost per solved task ($0.64 against $0.70) and a larger context window (1.05M against 400K tokens).
- Shared results
- 67
- Gemini 2.5 Pro only
- 23
- GPT-5.4 Mini only
- 22
- 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 Mini
GPT-5.4 Mini scores 35.8 against 19.1.
3 and 5 benchmarks behind the scores
Intelligence
AA Intelligence Index
GPT-5.4 Mini
GPT-5.4 Mini leads, 24.1 against 16.1.
Same board, both measured
Agentic work
AA Agentic Index
GPT-5.4 Mini
GPT-5.4 Mini leads, 17.9 against 1.6.
Same board, both measured
Reasoning
GPQA Diamond
No call
Only GPT-5.4 Mini has a GPQA Diamond result, 83.1%.
Directional only
Math
AIME
No call
Only GPT-5.4 Mini has a AIME result, 95.6%.
Directional only
Knowledge
MMLU Pro
No call
Only GPT-5.4 Mini has a MMLU Pro result, 84.5%.
Directional only
Web design
Design Arena: websites
No call
Only Gemini 2.5 Pro has a Design Arena: websites result, 1167.
Directional only
Long documents
Listed context window
Gemini 2.5 Pro
Gemini 2.5 Pro takes 1.05M tokens against 400K.
Listed by OpenRouter
Everyday cost
1K input + 500 output tokens
GPT-5.4 Mini
Gemini 2.5 Pro $0.0063, GPT-5.4 Mini $0.0030 per turn.
List prices
Cost per solved task
One SWE-bench Verified task, solved
Gemini 2.5 Pro
Gemini 2.5 Pro $0.64, GPT-5.4 Mini $0.70.
Published attempt cost and pass rate
At a glance
- Coding index
- Gemini 2.5 Pro 19.1 from 3 benchmarks, GPT-5.4 Mini 35.8 from 5 benchmarks.
- Widest category
- Coding, 18.8 points apart on average over 10 shared benchmarks.
- Widest single gap
- Vibe Code Bench (Vals AI): Gemini 2.5 Pro 0.4% against GPT-5.4 Mini 48.0%, 47.6 points apart on a 0 to 100 scale.
- Output price
- Gemini 2.5 Pro $10.00 against GPT-5.4 Mini $4.50 per million output tokens, 2.2x apart.
- Context window
- Gemini 2.5 Pro takes 1.05M tokens, GPT-5.4 Mini 400K.
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 | Gemini 2.5 Pro | Bars | GPT-5.4 Mini | Ties |
|---|---|---|---|---|
| Coding | 2 | 8 | ||
| Intelligence | 0 | 2 | ||
| Agentic work | 1 | 2 | ||
| Reasoning | 5 | 6 | ||
| Math | 2 | 3 | ||
| Knowledge | 6 | 1 | ||
| General | 25 | 4 | ||
| All shared boards | 41 | 26 |
CodingLike-for-likeSix of these boards feed the Vibe Coding Index28
| Benchmark | Gemini 2.5 Pro | GPT-5.4 Mini | Leader |
|---|---|---|---|
| SWE-bench Verified | 53.6% | Not measured | Only Gemini 2.5 Pro measured |
| LMArena WebDev | 1226 | 1397 | GPT-5.4 Mini |
| AA Coding Index | 33.3 | 56.1 | GPT-5.4 Mini |
| LiveCodeBench (Vals AI) | Not measured | 81.5% | Only GPT-5.4 Mini measured |
| SWE-bench Verified (Vals AI) | 54.4% | 73.0% | GPT-5.4 Mini |
| Terminal-Bench 4 (Vals AI) | Not measured | 2.5% | Only GPT-5.4 Mini measured |
| Vibe Code Bench (Vals AI) | 0.4% | 48.0% | GPT-5.4 Mini |
| Code migration (Vals AI) | Not measured | 12.9% | Only GPT-5.4 Mini measured |
| ProgramBench (Vals AI) | Not measured | 0.0% | Only GPT-5.4 Mini measured |
| Terminal-Bench 2.1 (Vals AI) | Not measured | 54.7% | Only GPT-5.4 Mini measured |
| LiveCodeBench (Artificial Analysis run) | 80.1% | Not measured | Only Gemini 2.5 Pro measured |
| SciCode | 46.3% | 52.1% | GPT-5.4 Mini |
| Terminal-Bench Hard (Artificial Analysis run) | 26.5% | 52.3% | GPT-5.4 Mini |
| Terminal-Bench | 32.6% | Not measured | Only Gemini 2.5 Pro measured |
| FrontierCode | Not measured | 27.0% | Only GPT-5.4 Mini measured |
| GSO-Bench | 3.9% | Not measured | Only Gemini 2.5 Pro measured |
| WeirdML | 54.0% | 60.3% | GPT-5.4 Mini |
| ALE-Bench | Not measured | 1188.6 | Only GPT-5.4 Mini measured |
| LMArena Text: coding | 1452 | 1438 | Gemini 2.5 Pro |
| LMArena Text: software and IT | 1459 | 1436 | Gemini 2.5 Pro |
| LMArena WebDev: React | Not measured | 1386 | Only GPT-5.4 Mini measured |
| LMArena WebDev: HTML | 1235 | 1419 | GPT-5.4 Mini |
| LMArena WebDev: from an image | 1285 | Not measured | Only Gemini 2.5 Pro measured |
| Neither model has a result on the other 16 boards here | |||
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index02
| Benchmark | Gemini 2.5 Pro | GPT-5.4 Mini | Leader |
|---|---|---|---|
| AA Intelligence Index | 16.1 | 24.1 | GPT-5.4 Mini |
| Epoch Capabilities Index | 145.1 | 148.7 | GPT-5.4 Mini |
Agentic workLike-for-likePublic boards, shown as published, kept out of the index12
| Benchmark | Gemini 2.5 Pro | GPT-5.4 Mini | Leader |
|---|---|---|---|
| AA Agentic Index | 1.6 | 17.9 | GPT-5.4 Mini |
| Finance Agent (Vals AI) | Not measured | 45.4% | Only GPT-5.4 Mini measured |
| Tax Agent Bench (Vals AI) | Not measured | 8.8% | Only GPT-5.4 Mini measured |
| Legal Research Bench (Vals AI) | Not measured | 12.5% | Only GPT-5.4 Mini measured |
| Excel Modeling Benchmark (Vals AI) | Not measured | 45.4% | Only GPT-5.4 Mini measured |
| τ²-Bench Telecom | 54.1% | 83.3% | GPT-5.4 Mini |
| GDPval | 23.3% | Not measured | Only Gemini 2.5 Pro measured |
| DeepResearch Bench | 41.5% | 36.3% | Gemini 2.5 Pro |
| Vending-Bench 2 | $574 | Not measured | Only Gemini 2.5 Pro measured |
| BrowseComp-Plus | 29.5% | Not measured | Only Gemini 2.5 Pro measured |
| Neither model has a result on the other 31 boards here | |||
ReasoningLike-for-likePublic boards, shown as published, kept out of the index56
| Benchmark | Gemini 2.5 Pro | GPT-5.4 Mini | Leader |
|---|---|---|---|
| GPQA Diamond | Not measured | 83.1% | Only GPT-5.4 Mini measured |
| MMMU Pro (Vals AI) | Not measured | 79.3% | Only GPT-5.4 Mini measured |
| GPQA Diamond (Artificial Analysis run) | 84.4% | 87.5% | GPT-5.4 Mini |
| Humanity's Last Exam (Artificial Analysis run) | 22.5% | 28.1% | GPT-5.4 Mini |
| GPQA Diamond (Epoch AI run) | 85.3% | 86.9% | GPT-5.4 Mini |
| ARC-AGI | 41.0% | 63.7% | GPT-5.4 Mini |
| ARC-AGI-2 | 4.9% | 18.9% | GPT-5.4 Mini |
| Chess puzzles | Not measured | 23.0% | Only GPT-5.4 Mini measured |
| Mystery game puzzles | Not measured | 11.0% | Only GPT-5.4 Mini measured |
| LMArena Text: hard prompts | 1455 | 1424 | Gemini 2.5 Pro |
| LMArena Text: expert | 1452 | 1435 | Gemini 2.5 Pro |
| LMArena Text: hard prompts in English | 1453 | 1420 | Gemini 2.5 Pro |
| LMArena Vision: diagrams | 1274 | 1266 | Gemini 2.5 Pro |
| LMArena Vision: homework | 1281 | 1285 | GPT-5.4 Mini |
| Kagi LLM Benchmark | 70.3% | 37.9% | Gemini 2.5 Pro |
| Neither model has a result on the other 7 boards here | |||
MathLike-for-likePublic boards, shown as published, kept out of the index23
| Benchmark | Gemini 2.5 Pro | GPT-5.4 Mini | Leader |
|---|---|---|---|
| AIME | Not measured | 95.6% | Only GPT-5.4 Mini measured |
| AA Math Index | 87.7 | Not measured | Only Gemini 2.5 Pro measured |
| AIME 2025 (Artificial Analysis run) | 87.7% | Not measured | Only Gemini 2.5 Pro measured |
| OTIS Mock AIME | 84.7% | 88.9% | GPT-5.4 Mini |
| FrontierMath, tiers 1 to 3 | 24.6% | 51.2% | GPT-5.4 Mini |
| FrontierMath, tier 4 | 0.0% | 9.8% | GPT-5.4 Mini |
| ProofBench | Not measured | 21.0% | Only GPT-5.4 Mini measured |
| LMArena Text: math | 1450 | 1418 | Gemini 2.5 Pro |
| LMArena Text: mathematical work | 1454 | 1429 | Gemini 2.5 Pro |
| Neither model has a result on the other 4 boards here | |||
KnowledgeLike-for-likePublic boards, shown as published, kept out of the index61
| Benchmark | Gemini 2.5 Pro | GPT-5.4 Mini | Leader |
|---|---|---|---|
| MMLU Pro | Not measured | 84.5% | Only GPT-5.4 Mini measured |
| CaseLaw (Vals AI) | 63.9% | 51.7% | Gemini 2.5 Pro |
| CorpFin (Vals AI) | 60.8% | 60.9% | GPT-5.4 Mini |
| TaxEval (Vals AI) | Not measured | 71.2% | Only GPT-5.4 Mini measured |
| MortgageTax (Vals AI) | 68.9% | 63.5% | Gemini 2.5 Pro |
| MedCode (Vals AI) | 50.6% | Not measured | Only Gemini 2.5 Pro measured |
| MMLU Pro (Artificial Analysis run) | 86.2% | Not measured | Only Gemini 2.5 Pro measured |
| SimpleQA Verified | Not measured | 29.4% | Only GPT-5.4 Mini measured |
| LMArena Text: science | 1480 | 1417 | Gemini 2.5 Pro |
| LMArena Text: medicine and healthcare | 1476 | 1395 | Gemini 2.5 Pro |
| LMArena Text: legal and government | 1480 | 1414 | Gemini 2.5 Pro |
| LMArena Text: business and finance | 1439 | 1418 | Gemini 2.5 Pro |
| FACTS Benchmark Suite | 61.5% | Not measured | Only Gemini 2.5 Pro measured |
| Neither model has a result on the other 5 boards here | |||
Web designDirectional onlyPublic boards, shown as published, kept out of the index6 boards, none shared
| Benchmark | Gemini 2.5 Pro | GPT-5.4 Mini | Leader |
|---|---|---|---|
| Design Arena: websites | 1167 | Not measured | Only Gemini 2.5 Pro measured |
| Design Arena: UI components | 1137 | Not measured | Only Gemini 2.5 Pro measured |
| Design Arena: game dev | 1111 | Not measured | Only Gemini 2.5 Pro measured |
| Design Arena: data viz | 1222 | Not measured | Only Gemini 2.5 Pro measured |
| Design Arena: 3D | 1080 | Not measured | Only Gemini 2.5 Pro measured |
| Design Arena: all code categories | 1152 | Not measured | Only Gemini 2.5 Pro measured |
| Neither model has a result on the other 3 boards here | |||
GeneralLike-for-likePublic boards, shown as published, kept out of the index254
| Benchmark | Gemini 2.5 Pro | GPT-5.4 Mini | Leader |
|---|---|---|---|
| SAGE (Vals AI) | 41.9% | 50.8% | GPT-5.4 Mini |
| MedScribe (Vals AI) | 73.5% | Not measured | Only Gemini 2.5 Pro measured |
| Vals Multimodal Index | Not measured | 54.2% | Only GPT-5.4 Mini measured |
| IFBench | 48.7% | 73.3% | GPT-5.4 Mini |
| Long context reasoning (AA-LCR) | 69.0% | 77.0% | GPT-5.4 Mini |
| DTBench | 82.4% | 80.0% | Gemini 2.5 Pro |
| LMCA | 34.8% | 40.8% | GPT-5.4 Mini |
| Creative writing (Lech Mazur) | 83.8% | Not measured | Only Gemini 2.5 Pro measured |
| LMArena Text | 1458 | 1412 | Gemini 2.5 Pro |
| LMArena Text: instruction following | 1437 | 1405 | Gemini 2.5 Pro |
| LMArena Text: creative writing | 1454 | 1370 | Gemini 2.5 Pro |
| LMArena Vision | 1263 | 1245 | Gemini 2.5 Pro |
| LMArena Text: English | 1458 | 1412 | Gemini 2.5 Pro |
| LMArena Text: non-English | 1452 | 1405 | Gemini 2.5 Pro |
| LMArena Text: Chinese | 1507 | 1446 | Gemini 2.5 Pro |
| LMArena Text: German | 1487 | 1408 | Gemini 2.5 Pro |
| LMArena Text: Japanese | 1461 | 1375 | Gemini 2.5 Pro |
| LMArena Text: Korean | 1434 | 1370 | Gemini 2.5 Pro |
| LMArena Text: French | 1473 | 1441 | Gemini 2.5 Pro |
| LMArena Text: Spanish | 1474 | 1405 | Gemini 2.5 Pro |
| LMArena Text: Russian | 1461 | 1417 | Gemini 2.5 Pro |
| LMArena Text: Polish | 1479 | 1415 | Gemini 2.5 Pro |
| LMArena Text: multi-turn | 1453 | 1429 | Gemini 2.5 Pro |
| LMArena Text: longer queries | 1449 | 1408 | Gemini 2.5 Pro |
| LMArena Text: writing and language | 1454 | 1393 | Gemini 2.5 Pro |
| LMArena Text: entertainment and media | 1441 | 1373 | Gemini 2.5 Pro |
| LMArena Vision: English | 1261 | 1244 | Gemini 2.5 Pro |
| LMArena Vision: Chinese | 1300 | 1286 | Gemini 2.5 Pro |
| LMArena Vision: reading text | 1270 | 1253 | Gemini 2.5 Pro |
| LMArena Vision: humor | 1262 | 1235 | Gemini 2.5 Pro |
| LMArena Vision: captioning | 1304 | Not measured | Only Gemini 2.5 Pro measured |
| LMArena Vision: recognizing things | 1283 | 1218 | Gemini 2.5 Pro |
| LMArena Vision: creative writing | 1265 | 1222 | Gemini 2.5 Pro |
| LMArena Document | 1421 | Not measured | Only Gemini 2.5 Pro 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 | Gemini 2.5 Pro | GPT-5.4 Mini | 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
GPT-5.4 Mini costs less
Repository review
50K input + 3K output tokens
GPT-5.4 Mini costs less
Agent loop
200K input + 10K output tokens
GPT-5.4 Mini 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 | Google Gemini 2.5 Pro | OpenAI GPT-5.4 Mini |
|---|---|---|
| Maker | OpenAI | |
| Weights | No public weights listed | No public weights listed |
| Released | June 17, 2025 | March 17, 2026 |
| Context window | 1.05M | 400K |
| Input $/Mtok | $1.25 | $0.75 |
| Output $/Mtok | $10.00 | $4.50 |
| Coding index | 19.1 | 35.8 |
| Independent measurements behind it | 3 | 5 |
| Cost per solved task | $0.64 | $0.70 |
| Source | OpenRouter listing | OpenRouter listing |
Questions
Is Gemini 2.5 Pro better than GPT-5.4 Mini for coding?
Pick GPT-5.4 Mini for coding: it scores 35.8 on the Vibe Coding Index against 19.1 for Gemini 2.5 Pro. Pick Gemini 2.5 Pro for a lower cost per solved task ($0.64 against $0.70) and a larger context window (1.05M against 400K tokens).
Which is cheaper, Gemini 2.5 Pro or GPT-5.4 Mini?
Gemini 2.5 Pro costs $1.25 per million input tokens and $10.00 per million output tokens; GPT-5.4 Mini costs $0.75 and $4.50. Per solved SWE-bench Verified task, Gemini 2.5 Pro costs $0.64 and GPT-5.4 Mini $0.70.
Which has the bigger context window, Gemini 2.5 Pro or GPT-5.4 Mini?
Gemini 2.5 Pro, with 1.05M tokens against 400K.
How many benchmarks is the Gemini 2.5 Pro vs GPT-5.4 Mini comparison based on?
67 benchmarks have a result for both models as of October 22, 2026. Gemini 2.5 Pro's coding index rests on 3 independent benchmarks and GPT-5.4 Mini's on 5. Where only one model has a result, the page says so instead of naming a winner.