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Gemini 2.5 Pro Preview 06-05 vs o3 Pro

Updated October 21, 2026. 3 benchmarks have a result for both. Coding is ranked on the Vibe Coding Index; every other board is shown as published.

Gemini 2.5 Pro Preview 06-05Google
Coding
83.1
Overall
No data
Output $/M
$10.00
0
o3 ProOpenAI
Coding
84.9
Overall
21.9
Output $/M
$80.00
3
vs boards won of 3 shared

Decision reading

Gemini 2.5 Pro Preview 06-05 and o3 Pro are level for coding, 83.1 against 84.9 on the Vibe Coding Index, so price and context decide.

Pick Gemini 2.5 Pro Preview 06-05 when output tokens cost 8.0x less, or when the context window is larger, 1.05M against 200K tokens. Pick o3 Pro when what matters is Aider polyglot or GPQA Diamond (Artificial Analysis run), where it leads.

Shared results
3
Gemini 2.5 Pro Preview 06-05 only
11
o3 Pro only
8
Like-for-like categories
3 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.

At a glance

Coding index
Gemini 2.5 Pro Preview 06-05 83.1 from 1 benchmark, o3 Pro 84.9 from 1 benchmark.
Widest category
General, 5.5 points apart on average over 1 shared benchmark.
Widest single gap
Fiction.LiveBench: Gemini 2.5 Pro Preview 06-05 91.7% against o3 Pro 97.2%, 5.5 points apart on a 0 to 100 scale.
Output price
Gemini 2.5 Pro Preview 06-05 $10.00 against o3 Pro $80.00 per million output tokens, 8.0x apart.
Context window
Gemini 2.5 Pro Preview 06-05 takes 1.05M tokens, o3 Pro 200K.

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.

Boards won, where both have a result
CategoryGemini 2.5 Pro Preview 06-05Barso3 ProTies
Coding01
Reasoning01
General01
All shared boards03
CodingLike-for-likeFour of these boards feed the Vibe Coding Index01
Coding benchmarks for Gemini 2.5 Pro Preview 06-05 and o3 Pro
BenchmarkGemini 2.5 Pro Preview 06-05o3 ProLeader
Aider polyglot83.1%84.9%o3 Pro
LiveCodeBench (Vals AI)79.2%Not measuredOnly Gemini 2.5 Pro Preview 06-05 measured
LiveCodeBench (Artificial Analysis run)77.8%Not measuredOnly Gemini 2.5 Pro Preview 06-05 measured
GSO-Bench3.9%Not measuredOnly Gemini 2.5 Pro Preview 06-05 measured
WeirdMLNot measured58.2%Only o3 Pro measured
Neither model has a result on the other 33 boards here
IntelligenceDirectional onlyPublic boards, shown as published, kept out of the index2 boards, none shared
Intelligence benchmarks for Gemini 2.5 Pro Preview 06-05 and o3 Pro
BenchmarkGemini 2.5 Pro Preview 06-05o3 ProLeader
AA Intelligence IndexNot measured21.9Only o3 Pro measured
Epoch Capabilities IndexNot measured147.3Only o3 Pro measured
Agentic workDirectional onlyPublic boards, shown as published, kept out of the index3 boards, none shared
Agentic work benchmarks for Gemini 2.5 Pro Preview 06-05 and o3 Pro
BenchmarkGemini 2.5 Pro Preview 06-05o3 ProLeader
METR time horizons55.4%Not measuredOnly Gemini 2.5 Pro Preview 06-05 measured
Remote Labor Index0.8%Not measuredOnly Gemini 2.5 Pro Preview 06-05 measured
DeepResearch Bench42.8%Not measuredOnly Gemini 2.5 Pro Preview 06-05 measured
Neither model has a result on the other 36 boards here
ReasoningLike-for-likePublic boards, shown as published, kept out of the index01
Reasoning benchmarks for Gemini 2.5 Pro Preview 06-05 and o3 Pro
BenchmarkGemini 2.5 Pro Preview 06-05o3 ProLeader
GPQA Diamond (Artificial Analysis run)83.6%84.5%o3 Pro
Humanity's Last Exam (Artificial Analysis run)19.9%Not measuredOnly Gemini 2.5 Pro Preview 06-05 measured
GPQA Diamond (Epoch AI run)84.8%Not measuredOnly Gemini 2.5 Pro Preview 06-05 measured
ARC-AGINot measured59.3%Only o3 Pro measured
ARC-AGI-2Not measured4.9%Only o3 Pro measured
SimpleBench62.4%Not measuredOnly Gemini 2.5 Pro Preview 06-05 measured
VPCT46.4%Not measuredOnly Gemini 2.5 Pro Preview 06-05 measured
Neither model has a result on the other 14 boards here
MathNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
Math benchmarks for Gemini 2.5 Pro Preview 06-05 and o3 Pro
BenchmarkGemini 2.5 Pro Preview 06-05o3 ProLeader
Neither model has a result on 13 boards here
KnowledgeDirectional onlyPublic boards, shown as published, kept out of the index1 board, none shared
Knowledge benchmarks for Gemini 2.5 Pro Preview 06-05 and o3 Pro
BenchmarkGemini 2.5 Pro Preview 06-05o3 ProLeader
MMLU Pro (Artificial Analysis run)85.8%Not measuredOnly Gemini 2.5 Pro Preview 06-05 measured
Neither model has a result on the other 16 boards here
Web designNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
Web design benchmarks for Gemini 2.5 Pro Preview 06-05 and o3 Pro
BenchmarkGemini 2.5 Pro Preview 06-05o3 ProLeader
Neither model has a result on 9 boards here
GeneralLike-for-likePublic boards, shown as published, kept out of the index01
General benchmarks for Gemini 2.5 Pro Preview 06-05 and o3 Pro
BenchmarkGemini 2.5 Pro Preview 06-05o3 ProLeader
DTBenchNot measured86.9%Only o3 Pro measured
LMCANot measured38.5%Only o3 Pro measured
Fiction.LiveBench91.7%97.2%o3 Pro
Creative writing (Lech Mazur)Not measured84.4%Only o3 Pro measured
Neither model has a result on the other 42 boards here
Image generationNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
Image generation benchmarks for Gemini 2.5 Pro Preview 06-05 and o3 Pro
BenchmarkGemini 2.5 Pro Preview 06-05o3 ProLeader
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$0.0063Fits in one request
o3 Pro$0.060Fits in one request

Gemini 2.5 Pro Preview 06-05 costs less

Repository review

50K input + 3K output tokens

Gemini 2.5 Pro Preview 06-05$0.092Fits in one request
o3 Pro$1.24Fits in one request

Gemini 2.5 Pro Preview 06-05 costs less

Agent loop

200K input + 10K output tokens

Gemini 2.5 Pro Preview 06-05$0.350Fits in one request
o3 Pro$4.80Exceeds the context window

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.

Specifications of Gemini 2.5 Pro Preview 06-05 and o3 Pro
SpecificationGoogle Gemini 2.5 Pro Preview 06-05OpenAI o3 Pro
MakerGoogleOpenAI
WeightsNo public weights listedNo public weights listed
ReleasedJune 5, 2025June 10, 2025
Context window1.05M200K
Input $/Mtok$1.25$20.00
Output $/Mtok$10.00$80.00
Coding index83.184.9
Independent measurements behind it11
Cost per solved taskNot computableNot computable
SourceOpenRouter listingOpenRouter listing

Questions

Is Gemini 2.5 Pro Preview 06-05 better than o3 Pro for coding?

Gemini 2.5 Pro Preview 06-05 and o3 Pro are level for coding, 83.1 against 84.9 on the Vibe Coding Index, so price and context decide. Pick Gemini 2.5 Pro Preview 06-05 when output tokens cost 8.0x less, or when the context window is larger, 1.05M against 200K tokens. Pick o3 Pro when what matters is Aider polyglot or GPQA Diamond (Artificial Analysis run), where it leads.

Which is cheaper, Gemini 2.5 Pro Preview 06-05 or o3 Pro?

Gemini 2.5 Pro Preview 06-05 costs $1.25 per million input tokens and $10.00 per million output tokens; o3 Pro costs $20.00 and $80.00. Cost per solved task is known for neither of them.

Which has the bigger context window, Gemini 2.5 Pro Preview 06-05 or o3 Pro?

Gemini 2.5 Pro Preview 06-05, with 1.05M tokens against 200K.

How many benchmarks is the Gemini 2.5 Pro Preview 06-05 vs o3 Pro comparison based on?

3 benchmarks have a result for both models as of October 21, 2026. Gemini 2.5 Pro Preview 06-05's coding index rests on 1 independent benchmark and o3 Pro's on 1. Where only one model has a result, the page says so instead of naming a winner.

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