Gemini 2.5 Pro Preview 06-05 vs GPT-4 Turbo
Gemini 2.5 Pro Preview 06-05 costs 3.0x less per output token than GPT-4 Turbo ($10.00 vs $30.00 per million). Updated October 22, 2026; 3 benchmarks have a result for both.
Gemini 2.5 Pro Preview 06-05 or GPT-4 Turbo: which to pick
Neither model has a coding score yet, so the two cannot be ranked on coding.
Pick Gemini 2.5 Pro Preview 06-05 for output tokens 3.0x cheaper ($10.00 vs $30.00 per million) and a larger context window (1.05M against 128K tokens).
- Shared results
- 3
- Gemini 2.5 Pro Preview 06-05 only
- 12
- GPT-4 Turbo only
- 39
- Like-for-like categories
- 3 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
No call
Neither has a coding score yet.
One side not measured
Intelligence
AA Intelligence Index
No call
Only GPT-4 Turbo has a AA Intelligence Index result, 7.0.
Directional only
Long documents
Listed context window
Gemini 2.5 Pro Preview 06-05
Gemini 2.5 Pro Preview 06-05 takes 1.05M tokens against 128K.
Listed by OpenRouter
Everyday cost
1K input + 500 output tokens
Gemini 2.5 Pro Preview 06-05
Gemini 2.5 Pro Preview 06-05 $0.0063, GPT-4 Turbo $0.025 per turn.
List prices
At a glance
- Coding index
- Gemini 2.5 Pro Preview 06-05 not benchmarked, GPT-4 Turbo not benchmarked.
- Widest category
- Coding, 48.7 points apart on average over 1 shared benchmark.
- Widest single gap
- LiveCodeBench (Artificial Analysis run): Gemini 2.5 Pro Preview 06-05 77.8% against GPT-4 Turbo 29.1%, 48.7 points apart on a 0 to 100 scale.
- Output price
- Gemini 2.5 Pro Preview 06-05 $10.00 against GPT-4 Turbo $30.00 per million output tokens, 3.0x apart.
- Context window
- Gemini 2.5 Pro Preview 06-05 takes 1.05M tokens, GPT-4 Turbo 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 Pro Preview 06-05 | Bars | GPT-4 Turbo | Ties |
|---|---|---|---|---|
| Coding | 1 | 0 | ||
| Reasoning | 1 | 0 | ||
| Knowledge | 1 | 0 | ||
| All shared boards | 3 | 0 |
CodingLike-for-likeSix of these boards feed the Vibe Coding Index10
| Benchmark | Gemini 2.5 Pro Preview 06-05 | GPT-4 Turbo | Leader |
|---|---|---|---|
| Aider polyglot | 83.1% | Not measured | Only Gemini 2.5 Pro Preview 06-05 measured |
| AA Coding Index | Not measured | 21.5 | Only GPT-4 Turbo measured |
| LiveCodeBench (Vals AI) | 79.2% | Not measured | Only Gemini 2.5 Pro Preview 06-05 measured |
| LiveCodeBench (Artificial Analysis run) | 77.8% | 29.1% | Gemini 2.5 Pro Preview 06-05 |
| GSO-Bench | 3.9% | Not measured | Only Gemini 2.5 Pro Preview 06-05 measured |
| LMArena Text: coding | Not measured | 1268 | Only GPT-4 Turbo measured |
| LMArena Text: software and IT | Not measured | 1267 | Only GPT-4 Turbo measured |
| SciCode | 7.7% | Not measured | Only Gemini 2.5 Pro Preview 06-05 measured |
| Neither model has a result on the other 35 boards here | |||
IntelligenceDirectional onlyPublic boards, shown as published, kept out of the index2 boards, none shared
| Benchmark | Gemini 2.5 Pro Preview 06-05 | GPT-4 Turbo | Leader |
|---|---|---|---|
| AA Intelligence Index | Not measured | 7.0 | Only GPT-4 Turbo measured |
| Epoch Capabilities Index | Not measured | 127.3 | Only GPT-4 Turbo measured |
Agentic workDirectional onlyPublic boards, shown as published, kept out of the index3 boards, none shared
| Benchmark | Gemini 2.5 Pro Preview 06-05 | GPT-4 Turbo | Leader |
|---|---|---|---|
| METR time horizons | 55.4% | Not measured | Only Gemini 2.5 Pro Preview 06-05 measured |
| Remote Labor Index | 0.8% | Not measured | Only Gemini 2.5 Pro Preview 06-05 measured |
| DeepResearch Bench | 42.8% | Not measured | Only Gemini 2.5 Pro Preview 06-05 measured |
| Neither model has a result on the other 39 boards here | |||
ReasoningLike-for-likePublic boards, shown as published, kept out of the index10
| Benchmark | Gemini 2.5 Pro Preview 06-05 | GPT-4 Turbo | Leader |
|---|---|---|---|
| GPQA Diamond (Artificial Analysis run) | 83.6% | Not measured | Only Gemini 2.5 Pro Preview 06-05 measured |
| Humanity's Last Exam (Artificial Analysis run) | 19.9% | 3.1% | Gemini 2.5 Pro Preview 06-05 |
| GPQA Diamond (Epoch AI run) | 84.8% | Not measured | Only Gemini 2.5 Pro Preview 06-05 measured |
| SimpleBench | 62.4% | Not measured | Only Gemini 2.5 Pro Preview 06-05 measured |
| VPCT | 46.4% | Not measured | Only Gemini 2.5 Pro Preview 06-05 measured |
| LMArena Text: hard prompts | Not measured | 1251 | Only GPT-4 Turbo measured |
| LMArena Text: expert | Not measured | 1223 | Only GPT-4 Turbo measured |
| LMArena Text: hard prompts in English | Not measured | 1266 | Only GPT-4 Turbo measured |
| Neither model has a result on the other 15 boards here | |||
MathDirectional onlyPublic boards, shown as published, kept out of the index2 boards, none shared
| Benchmark | Gemini 2.5 Pro Preview 06-05 | GPT-4 Turbo | Leader |
|---|---|---|---|
| LMArena Text: math | Not measured | 1272 | Only GPT-4 Turbo measured |
| LMArena Text: mathematical work | Not measured | 1268 | Only GPT-4 Turbo measured |
| Neither model has a result on the other 12 boards here | |||
KnowledgeLike-for-likePublic boards, shown as published, kept out of the index10
| Benchmark | Gemini 2.5 Pro Preview 06-05 | GPT-4 Turbo | Leader |
|---|---|---|---|
| LegalBench (Vals AI) | Not measured | 80.5% | Only GPT-4 Turbo measured |
| MedQA (Vals AI) | Not measured | 82.0% | Only GPT-4 Turbo measured |
| MMLU Pro (Artificial Analysis run) | 85.8% | 69.4% | Gemini 2.5 Pro Preview 06-05 |
| MMLU | Not measured | 81.3% | Only GPT-4 Turbo measured |
| LMArena Text: science | Not measured | 1256 | Only GPT-4 Turbo measured |
| LMArena Text: medicine and healthcare | Not measured | 1239 | Only GPT-4 Turbo measured |
| LMArena Text: legal and government | Not measured | 1265 | Only GPT-4 Turbo measured |
| LMArena Text: business and finance | Not measured | 1222 | Only GPT-4 Turbo measured |
| Neither model has a result on the other 12 boards here | |||
Web designNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
| Benchmark | Gemini 2.5 Pro Preview 06-05 | GPT-4 Turbo | Leader |
|---|---|---|---|
| Neither model has a result on 9 boards here | |||
GeneralDirectional onlyPublic boards, shown as published, kept out of the index23 boards, none shared
| Benchmark | Gemini 2.5 Pro Preview 06-05 | GPT-4 Turbo | Leader |
|---|---|---|---|
| DTBench | Not measured | 61.6% | Only GPT-4 Turbo measured |
| LMCA | Not measured | 9.8% | Only GPT-4 Turbo measured |
| Fiction.LiveBench | 91.7% | Not measured | Only Gemini 2.5 Pro Preview 06-05 measured |
| LMArena Text | Not measured | 1272 | Only GPT-4 Turbo measured |
| LMArena Text: instruction following | Not measured | 1249 | Only GPT-4 Turbo measured |
| LMArena Text: creative writing | Not measured | 1268 | Only GPT-4 Turbo measured |
| LMArena Vision | Not measured | 1090 | Only GPT-4 Turbo measured |
| LMArena Text: English | Not measured | 1291 | Only GPT-4 Turbo measured |
| LMArena Text: non-English | Not measured | 1245 | Only GPT-4 Turbo measured |
| LMArena Text: Chinese | Not measured | 1242 | Only GPT-4 Turbo measured |
| LMArena Text: German | Not measured | 1259 | Only GPT-4 Turbo measured |
| LMArena Text: Japanese | Not measured | 1194 | Only GPT-4 Turbo measured |
| LMArena Text: Korean | Not measured | 1187 | Only GPT-4 Turbo measured |
| LMArena Text: French | Not measured | 1276 | Only GPT-4 Turbo measured |
| LMArena Text: Spanish | Not measured | 1260 | Only GPT-4 Turbo measured |
| LMArena Text: Russian | Not measured | 1259 | Only GPT-4 Turbo measured |
| LMArena Text: Polish | Not measured | 1302 | Only GPT-4 Turbo measured |
| LMArena Text: multi-turn | Not measured | 1267 | Only GPT-4 Turbo measured |
| LMArena Text: longer queries | Not measured | 1254 | Only GPT-4 Turbo measured |
| LMArena Text: writing and language | Not measured | 1279 | Only GPT-4 Turbo measured |
| LMArena Text: entertainment and media | Not measured | 1258 | Only GPT-4 Turbo measured |
| LMArena Vision: English | Not measured | 1097 | Only GPT-4 Turbo measured |
| LMArena Vision: Chinese | Not measured | 1045 | Only GPT-4 Turbo measured |
| Neither model has a result on the other 25 boards here | |||
Image generationNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
| Benchmark | Gemini 2.5 Pro Preview 06-05 | GPT-4 Turbo | 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 Pro Preview 06-05 costs less
Repository review
50K input + 3K output tokens
Gemini 2.5 Pro Preview 06-05 costs less
Agent loop
200K input + 10K output tokens
Gemini 2.5 Pro Preview 06-05 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 Preview 06-05 | OpenAI GPT-4 Turbo |
|---|---|---|
| Maker | OpenAI | |
| Weights | No public weights listed | No public weights listed |
| Released | June 5, 2025 | April 9, 2024 |
| Context window | 1.05M | 128K |
| Input $/Mtok | $1.25 | $10.00 |
| Output $/Mtok | $10.00 | $30.00 |
| Coding index | Not benchmarked | Not benchmarked |
| Independent measurements behind it | 0 | 0 |
| Cost per solved task | Not computable | Not computable |
| Source | OpenRouter listing | OpenRouter listing |
Questions
Is Gemini 2.5 Pro Preview 06-05 better than GPT-4 Turbo for coding?
Neither model has a coding score yet, so the two cannot be ranked on coding. Pick Gemini 2.5 Pro Preview 06-05 for output tokens 3.0x cheaper ($10.00 vs $30.00 per million) and a larger context window (1.05M against 128K tokens).
Which is cheaper, Gemini 2.5 Pro Preview 06-05 or GPT-4 Turbo?
Gemini 2.5 Pro Preview 06-05 costs $1.25 per million input tokens and $10.00 per million output tokens; GPT-4 Turbo costs $10.00 and $30.00. Cost per solved task is known for neither of them.
Which has the bigger context window, Gemini 2.5 Pro Preview 06-05 or GPT-4 Turbo?
Gemini 2.5 Pro Preview 06-05, with 1.05M tokens against 128K.
How many benchmarks is the Gemini 2.5 Pro Preview 06-05 vs GPT-4 Turbo comparison based on?
3 benchmarks have a result for both models as of October 22, 2026. Gemini 2.5 Pro Preview 06-05's coding index rests on 0 independent benchmarks and GPT-4 Turbo's on 0. Where only one model has a result, the page says so instead of naming a winner.