Gemini 2.5 Flash vs GPT-4o
Updated October 21, 2026. 21 benchmarks have a result for both. Coding is ranked on the Vibe Coding Index; every other board is shown as published.
Decision reading
Pick GPT-4o for coding: it scores 38.8 on the Vibe Coding Index against 28.7 for Gemini 2.5 Flash.
Pick Gemini 2.5 Flash when output tokens cost 4.0x less, or when the context window is larger, 1.05M against 128K tokens.
- Shared results
- 21
- Gemini 2.5 Flash only
- 48
- GPT-4o only
- 5
- Like-for-like categories
- 7 of 9
Shared results can support a head-to-head reading. Results only one model has describe coverage, not superiority.
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, four public coding benchmarks
GPT-4o
GPT-4o scores 38.8 against 28.7.
One benchmark behind each score
Intelligence
AA Intelligence Index
No call
Only Gemini 2.5 Flash has a AA Intelligence Index result, 15.5.
Directional only
Web design
Design Arena: websites
Gemini 2.5 Flash
Gemini 2.5 Flash leads, 1074 against 831.
Same board, both measured
Long documents
Listed context window
Gemini 2.5 Flash
Gemini 2.5 Flash takes 1.05M tokens against 128K.
Listed by OpenRouter
Everyday cost
1K input + 500 output tokens
Gemini 2.5 Flash
Gemini 2.5 Flash $0.0015, GPT-4o $0.0075 per turn.
List prices
Cost per solved task
One SWE-bench Verified task, solved
No call
Only Gemini 2.5 Flash has the number, $0.466.
Directional only
At a glance
- Coding index
- Gemini 2.5 Flash 28.7 from 1 benchmark, GPT-4o 38.8 from 1 benchmark.
- Widest category
- Math, 67.3 points apart on average over 2 shared benchmarks.
- Widest single gap
- AIME 2025 (Artificial Analysis run): Gemini 2.5 Flash 73.3% against GPT-4o 6.0%, 67.3 points apart on a 0 to 100 scale.
- Output price
- Gemini 2.5 Flash $2.50 against GPT-4o $10.00 per million output tokens, 4.0x apart.
- Context window
- Gemini 2.5 Flash takes 1.05M tokens, GPT-4o 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 | Gemini 2.5 Flash | Bars | GPT-4o | Ties |
|---|---|---|---|---|
| Coding | 2 | 1 | ||
| Agentic work | 1 | 0 | ||
| Reasoning | 4 | 0 | ||
| Math | 2 | 0 | ||
| Knowledge | 1 | 0 | ||
| Web design | 6 | 0 | ||
| General | 4 | 0 | ||
| All shared boards | 20 | 1 |
CodingLike-for-likeFour of these boards feed the Vibe Coding Index21
| Benchmark | Gemini 2.5 Flash | GPT-4o | Leader |
|---|---|---|---|
| SWE-bench Verified | 28.7% | 38.8% | GPT-4o |
| SWE-bench Lite | Not measured | 38.0% | Only GPT-4o measured |
| SWE-bench (full test set) | Not measured | 18.8% | Only GPT-4o measured |
| SWE-bench Multimodal | Not measured | 30.4% | Only GPT-4o measured |
| LiveCodeBench (Artificial Analysis run) | 69.5% | 30.9% | Gemini 2.5 Flash |
| Terminal-Bench Hard (Artificial Analysis run) | 13.6% | 8.3% | Gemini 2.5 Flash |
| Terminal-Bench | 17.1% | Not measured | Only Gemini 2.5 Flash measured |
| LMArena Text: coding | 1423 | Not measured | Only Gemini 2.5 Flash measured |
| LMArena Text: software and IT | 1425 | Not measured | Only Gemini 2.5 Flash 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 | Gemini 2.5 Flash | GPT-4o | Leader |
|---|---|---|---|
| AA Intelligence Index | 15.5 | Not measured | Only Gemini 2.5 Flash measured |
| Epoch Capabilities Index | 142.9 | Not measured | Only Gemini 2.5 Flash measured |
Agentic workLike-for-likePublic boards, shown as published, kept out of the index10
| Benchmark | Gemini 2.5 Flash | GPT-4o | Leader |
|---|---|---|---|
| τ²-Bench Telecom | 31.6% | 25.1% | Gemini 2.5 Flash |
| GDPval | Not measured | 9.9% | Only GPT-4o measured |
| BALROG | 33.5% | Not measured | Only Gemini 2.5 Flash measured |
| Vending-Bench 2 | $549 | Not measured | Only Gemini 2.5 Flash measured |
| Neither model has a result on the other 35 boards here | |||
ReasoningLike-for-likePublic boards, shown as published, kept out of the index40
| Benchmark | Gemini 2.5 Flash | GPT-4o | Leader |
|---|---|---|---|
| GPQA Diamond (Artificial Analysis run) | 79.0% | 54.3% | Gemini 2.5 Flash |
| Humanity's Last Exam (Artificial Analysis run) | 12.1% | 2.4% | Gemini 2.5 Flash |
| ARC-AGI | 33.3% | 4.5% | Gemini 2.5 Flash |
| ARC-AGI-2 | 2.5% | 0.0% | Gemini 2.5 Flash |
| SimpleBench | 41.2% | Not measured | Only Gemini 2.5 Flash measured |
| LMArena Text: hard prompts | 1422 | Not measured | Only Gemini 2.5 Flash measured |
| LMArena Text: expert | 1426 | Not measured | Only Gemini 2.5 Flash measured |
| LMArena Text: hard prompts in English | 1420 | Not measured | Only Gemini 2.5 Flash measured |
| LMArena Vision: diagrams | 1245 | Not measured | Only Gemini 2.5 Flash measured |
| LMArena Vision: homework | 1244 | Not measured | Only Gemini 2.5 Flash measured |
| Neither model has a result on the other 11 boards here | |||
MathLike-for-likePublic boards, shown as published, kept out of the index20
| Benchmark | Gemini 2.5 Flash | GPT-4o | Leader |
|---|---|---|---|
| AA Math Index | 73.3 | 6.0 | Gemini 2.5 Flash |
| AIME 2025 (Artificial Analysis run) | 73.3% | 6.0% | Gemini 2.5 Flash |
| LMArena Text: math | 1411 | Not measured | Only Gemini 2.5 Flash measured |
| LMArena Text: mathematical work | 1422 | Not measured | Only Gemini 2.5 Flash measured |
| Neither model has a result on the other 9 boards here | |||
KnowledgeLike-for-likePublic boards, shown as published, kept out of the index10
| Benchmark | Gemini 2.5 Flash | GPT-4o | Leader |
|---|---|---|---|
| MedCode (Vals AI) | 40.4% | Not measured | Only Gemini 2.5 Flash measured |
| MMLU Pro (Artificial Analysis run) | 83.2% | 74.8% | Gemini 2.5 Flash |
| MMLU | Not measured | 88.1% | Only GPT-4o measured |
| LMArena Text: science | 1433 | Not measured | Only Gemini 2.5 Flash measured |
| LMArena Text: medicine and healthcare | 1428 | Not measured | Only Gemini 2.5 Flash measured |
| LMArena Text: legal and government | 1430 | Not measured | Only Gemini 2.5 Flash measured |
| LMArena Text: business and finance | 1404 | Not measured | Only Gemini 2.5 Flash measured |
| Neither model has a result on the other 10 boards here | |||
Web designLike-for-likePublic boards, shown as published, kept out of the index60
| Benchmark | Gemini 2.5 Flash | GPT-4o | Leader |
|---|---|---|---|
| Design Arena: websites | 1074 | 831 | Gemini 2.5 Flash |
| Design Arena: UI components | 1005 | 885 | Gemini 2.5 Flash |
| Design Arena: game dev | 1005 | 906 | Gemini 2.5 Flash |
| Design Arena: data viz | 1060 | 858 | Gemini 2.5 Flash |
| Design Arena: 3D | 1021 | 869 | Gemini 2.5 Flash |
| Design Arena: all code categories | 1059 | 861 | Gemini 2.5 Flash |
| Design Arena: SVG | 1018 | Not measured | Only Gemini 2.5 Flash measured |
| Neither model has a result on the other 2 boards here | |||
GeneralLike-for-likePublic boards, shown as published, kept out of the index40
| Benchmark | Gemini 2.5 Flash | GPT-4o | Leader |
|---|---|---|---|
| SAGE (Vals AI) | 44.8% | Not measured | Only Gemini 2.5 Flash measured |
| MedScribe (Vals AI) | 83.0% | Not measured | Only Gemini 2.5 Flash measured |
| IFBench | 50.3% | 34.3% | Gemini 2.5 Flash |
| Long context reasoning (AA-LCR) | 65.3% | 49.3% | Gemini 2.5 Flash |
| DTBench | 76.5% | 64.5% | Gemini 2.5 Flash |
| LMCA | 27.5% | 16.6% | Gemini 2.5 Flash |
| LMArena Text | 1417 | Not measured | Only Gemini 2.5 Flash measured |
| LMArena Text: instruction following | 1405 | Not measured | Only Gemini 2.5 Flash measured |
| LMArena Text: creative writing | 1400 | Not measured | Only Gemini 2.5 Flash measured |
| LMArena Vision | 1235 | Not measured | Only Gemini 2.5 Flash measured |
| LMArena Text: English | 1418 | Not measured | Only Gemini 2.5 Flash measured |
| LMArena Text: non-English | 1409 | Not measured | Only Gemini 2.5 Flash measured |
| LMArena Text: Chinese | 1449 | Not measured | Only Gemini 2.5 Flash measured |
| LMArena Text: German | 1417 | Not measured | Only Gemini 2.5 Flash measured |
| LMArena Text: Japanese | 1396 | Not measured | Only Gemini 2.5 Flash measured |
| LMArena Text: Korean | 1385 | Not measured | Only Gemini 2.5 Flash measured |
| LMArena Text: French | 1432 | Not measured | Only Gemini 2.5 Flash measured |
| LMArena Text: Spanish | 1422 | Not measured | Only Gemini 2.5 Flash measured |
| LMArena Text: Russian | 1415 | Not measured | Only Gemini 2.5 Flash measured |
| LMArena Text: Polish | 1413 | Not measured | Only Gemini 2.5 Flash measured |
| LMArena Text: multi-turn | 1408 | Not measured | Only Gemini 2.5 Flash measured |
| LMArena Text: longer queries | 1419 | Not measured | Only Gemini 2.5 Flash measured |
| LMArena Text: writing and language | 1405 | Not measured | Only Gemini 2.5 Flash measured |
| LMArena Text: entertainment and media | 1393 | Not measured | Only Gemini 2.5 Flash measured |
| LMArena Vision: English | 1239 | Not measured | Only Gemini 2.5 Flash measured |
| LMArena Vision: Chinese | 1284 | Not measured | Only Gemini 2.5 Flash measured |
| LMArena Vision: reading text | 1237 | Not measured | Only Gemini 2.5 Flash measured |
| LMArena Vision: humor | 1225 | Not measured | Only Gemini 2.5 Flash measured |
| LMArena Vision: captioning | 1277 | Not measured | Only Gemini 2.5 Flash measured |
| LMArena Vision: recognizing things | 1252 | Not measured | Only Gemini 2.5 Flash measured |
| LMArena Vision: creative writing | 1241 | Not measured | Only Gemini 2.5 Flash measured |
| Neither model has a result on the other 15 boards here | |||
Image generationNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
| Benchmark | Gemini 2.5 Flash | GPT-4o | 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
Gemini 2.5 Flash costs less
Repository review
50K input + 3K output tokens
Gemini 2.5 Flash costs less
Agent loop
200K input + 10K output tokens
Gemini 2.5 Flash 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 Flash | OpenAI GPT-4o |
|---|---|---|
| Maker | OpenAI | |
| Weights | No public weights listed | No public weights listed |
| Released | June 17, 2025 | May 13, 2024 |
| Context window | 1.05M | 128K |
| Input $/Mtok | $0.30 | $2.50 |
| Output $/Mtok | $2.50 | $10.00 |
| Coding index | 28.7 | 38.8 |
| Independent measurements behind it | 1 | 1 |
| Cost per solved task | $0.466 | Not computable |
| Source | OpenRouter listing | OpenRouter listing |
Questions
Is Gemini 2.5 Flash better than GPT-4o for coding?
Pick GPT-4o for coding: it scores 38.8 on the Vibe Coding Index against 28.7 for Gemini 2.5 Flash. Pick Gemini 2.5 Flash when output tokens cost 4.0x less, or when the context window is larger, 1.05M against 128K tokens.
Which is cheaper, Gemini 2.5 Flash or GPT-4o?
Gemini 2.5 Flash costs $0.30 per million input tokens and $2.50 per million output tokens; GPT-4o costs $2.50 and $10.00. Cost per solved task is known for Gemini 2.5 Flash only.
Which has the bigger context window, Gemini 2.5 Flash or GPT-4o?
Gemini 2.5 Flash, with 1.05M tokens against 128K.
How many benchmarks is the Gemini 2.5 Flash vs GPT-4o comparison based on?
21 benchmarks have a result for both models as of October 21, 2026. Gemini 2.5 Flash's coding index rests on 1 independent benchmark and GPT-4o's on 1. Where only one model has a result, the page says so instead of naming a winner.