Gemini 2.5 Pro Preview 06-05 vs GPT-5.2-Codex
Gemini 2.5 Pro Preview 06-05 costs 1.4x less per output token than GPT-5.2-Codex ($10.00 vs $14.00 per million). Updated October 22, 2026; 3 benchmarks have a result for both.
Gemini 2.5 Pro Preview 06-05 or GPT-5.2-Codex: which to pick
Only GPT-5.2-Codex has a coding score, 45.4 on the Vibe Coding Index; Gemini 2.5 Pro Preview 06-05 has none, so the two cannot be ranked on coding.
Pick Gemini 2.5 Pro Preview 06-05 for output tokens 1.4x cheaper ($10.00 vs $14.00 per million) and a larger context window (1.05M against 400K tokens).
- Shared results
- 3
- Gemini 2.5 Pro Preview 06-05 only
- 12
- GPT-5.2-Codex only
- 19
- Like-for-like categories
- 2 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
Only GPT-5.2-Codex has a coding score, so no call is made.
One side not measured
Intelligence
AA Intelligence Index
No call
Only GPT-5.2-Codex has a AA Intelligence Index result, 28.5.
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 400K.
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-5.2-Codex $0.0088 per turn.
List prices
Cost per solved task
One SWE-bench Verified task, solved
No call
Only GPT-5.2-Codex has the number, $0.43.
Directional only
At a glance
- Coding index
- Gemini 2.5 Pro Preview 06-05 not benchmarked, GPT-5.2-Codex 45.4 from 3 benchmarks.
- Widest category
- Reasoning, 11.1 points apart on average over 2 shared benchmarks.
- Widest single gap
- Humanity's Last Exam (Artificial Analysis run): Gemini 2.5 Pro Preview 06-05 19.9% against GPT-5.2-Codex 35.7%, 15.8 points apart on a 0 to 100 scale.
- Output price
- Gemini 2.5 Pro Preview 06-05 $10.00 against GPT-5.2-Codex $14.00 per million output tokens, 1.4x apart.
- Context window
- Gemini 2.5 Pro Preview 06-05 takes 1.05M tokens, GPT-5.2-Codex 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 Preview 06-05 | Bars | GPT-5.2-Codex | Ties |
|---|---|---|---|---|
| Coding | 0 | 1 | ||
| Reasoning | 0 | 2 | ||
| All shared boards | 0 | 3 |
CodingLike-for-likeSix of these boards feed the Vibe Coding Index01
| Benchmark | Gemini 2.5 Pro Preview 06-05 | GPT-5.2-Codex | Leader |
|---|---|---|---|
| Aider polyglot | 83.1% | Not measured | Only Gemini 2.5 Pro Preview 06-05 measured |
| SWE-bench Verified | Not measured | 72.8% | Only GPT-5.2-Codex measured |
| SWE-bench Multilingual | Not measured | 66.3% | Only GPT-5.2-Codex measured |
| LMArena WebDev | Not measured | 1339 | Only GPT-5.2-Codex measured |
| LiveCodeBench (Vals AI) | 79.2% | 88.0% | GPT-5.2-Codex |
| SWE-bench Verified (Vals AI) | Not measured | 72.4% | Only GPT-5.2-Codex measured |
| Vibe Code Bench (Vals AI) | Not measured | 37.9% | Only GPT-5.2-Codex measured |
| LiveCodeBench (Artificial Analysis run) | 77.8% | Not measured | Only Gemini 2.5 Pro Preview 06-05 measured |
| Terminal-Bench Hard (Artificial Analysis run) | Not measured | 37.1% | Only GPT-5.2-Codex measured |
| Terminal-Bench | Not measured | 66.5% | Only GPT-5.2-Codex measured |
| GSO-Bench | 3.9% | Not measured | Only Gemini 2.5 Pro Preview 06-05 measured |
| ALE-Bench | Not measured | 1299.9 | Only GPT-5.2-Codex measured |
| LMArena WebDev: React | Not measured | 1329 | Only GPT-5.2-Codex measured |
| LMArena WebDev: HTML | Not measured | 1348 | Only GPT-5.2-Codex measured |
| SciCode | 7.7% | Not measured | Only Gemini 2.5 Pro Preview 06-05 measured |
| Neither model has a result on the other 24 boards here | |||
IntelligenceDirectional onlyPublic boards, shown as published, kept out of the index1 board, none shared
| Benchmark | Gemini 2.5 Pro Preview 06-05 | GPT-5.2-Codex | Leader |
|---|---|---|---|
| AA Intelligence Index | Not measured | 28.5 | Only GPT-5.2-Codex measured |
| Neither model has a result on the other 1 board here | |||
Agentic workDirectional onlyPublic boards, shown as published, kept out of the index9 boards, none shared
| Benchmark | Gemini 2.5 Pro Preview 06-05 | GPT-5.2-Codex | Leader |
|---|---|---|---|
| Design Arena: agents building web apps | Not measured | 1051 | Only GPT-5.2-Codex measured |
| Design Arena: agents building full-stack apps | Not measured | 993 | Only GPT-5.2-Codex measured |
| Design Arena: agents building mobile apps | Not measured | 1090 | Only GPT-5.2-Codex measured |
| Design Arena: agents building Android apps | Not measured | 1176 | Only GPT-5.2-Codex measured |
| Design Arena: agents building Godot games | Not measured | 1142 | Only GPT-5.2-Codex measured |
| τ²-Bench Telecom | Not measured | 92.1% | Only GPT-5.2-Codex measured |
| 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 32 boards here | |||
ReasoningLike-for-likePublic boards, shown as published, kept out of the index02
| Benchmark | Gemini 2.5 Pro Preview 06-05 | GPT-5.2-Codex | Leader |
|---|---|---|---|
| GPQA Diamond (Artificial Analysis run) | 83.6% | 89.9% | GPT-5.2-Codex |
| Humanity's Last Exam (Artificial Analysis run) | 19.9% | 35.7% | GPT-5.2-Codex |
| 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 |
| Neither model has a result on the other 17 boards here | |||
MathNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
| Benchmark | Gemini 2.5 Pro Preview 06-05 | GPT-5.2-Codex | Leader |
|---|---|---|---|
| Neither model has a result on 13 boards here | |||
KnowledgeDirectional onlyPublic boards, shown as published, kept out of the index1 board, none shared
| Benchmark | Gemini 2.5 Pro Preview 06-05 | GPT-5.2-Codex | Leader |
|---|---|---|---|
| MMLU Pro (Artificial Analysis run) | 85.8% | Not measured | Only Gemini 2.5 Pro Preview 06-05 measured |
| Neither model has a result on the other 17 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-5.2-Codex | Leader |
|---|---|---|---|
| Neither model has a result on 9 boards here | |||
GeneralDirectional onlyPublic boards, shown as published, kept out of the index3 boards, none shared
| Benchmark | Gemini 2.5 Pro Preview 06-05 | GPT-5.2-Codex | Leader |
|---|---|---|---|
| IFBench | Not measured | 77.6% | Only GPT-5.2-Codex measured |
| Long context reasoning (AA-LCR) | Not measured | 82.3% | Only GPT-5.2-Codex measured |
| Fiction.LiveBench | 91.7% | Not measured | Only Gemini 2.5 Pro Preview 06-05 measured |
| Neither model has a result on the other 43 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-5.2-Codex | 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-5.2-Codex |
|---|---|---|
| Maker | OpenAI | |
| Weights | No public weights listed | No public weights listed |
| Released | June 5, 2025 | January 14, 2026 |
| Context window | 1.05M | 400K |
| Input $/Mtok | $1.25 | $1.75 |
| Output $/Mtok | $10.00 | $14.00 |
| Coding index | Not benchmarked | 45.4 |
| Independent measurements behind it | 0 | 3 |
| Cost per solved task | Not computable | $0.43 |
| Source | OpenRouter listing | OpenRouter listing |
Questions
Is Gemini 2.5 Pro Preview 06-05 better than GPT-5.2-Codex for coding?
Only GPT-5.2-Codex has a coding score, 45.4 on the Vibe Coding Index; Gemini 2.5 Pro Preview 06-05 has none, so the two cannot be ranked on coding. Pick Gemini 2.5 Pro Preview 06-05 for output tokens 1.4x cheaper ($10.00 vs $14.00 per million) and a larger context window (1.05M against 400K tokens).
Which is cheaper, Gemini 2.5 Pro Preview 06-05 or GPT-5.2-Codex?
Gemini 2.5 Pro Preview 06-05 costs $1.25 per million input tokens and $10.00 per million output tokens; GPT-5.2-Codex costs $1.75 and $14.00. Cost per solved task is known for GPT-5.2-Codex only.
Which has the bigger context window, Gemini 2.5 Pro Preview 06-05 or GPT-5.2-Codex?
Gemini 2.5 Pro Preview 06-05, with 1.05M tokens against 400K.
How many benchmarks is the Gemini 2.5 Pro Preview 06-05 vs GPT-5.2-Codex 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-5.2-Codex's on 3. Where only one model has a result, the page says so instead of naming a winner.