Compare

O3 vs Gemini 2.5 Pro

Pricing per million tokens, context window, capabilities — pulled from each provider's public docs. All 2 are available via the same AIgateway OpenAI-compatible endpoint; flip the model string to switch.

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O3
openai/o3
Gemini 2.5 Pro
google/gemini-2.5-pro
Provider
OpenAI
Google
Family
o-series
Modality
text
text
Context window
200,000 tok
1,000,000 tok
Max output
100,000 tok
65,536 tok
Released
2026-05-22
2026-05-22
License
Open-weight
Proprietary
Input price
$2.00 /1M
$1.25 /1M
Output price
$8.00 /1M
$10.00 /1M
Tools
Streaming
yes
yes
Vision
yes
JSON mode
Reasoning
Prompt caching
Batch API
Try it
Open in playground →
Open in playground →
O3
openai/o3
Full spec →

o3 is OpenAI’s general-purpose reasoning model, balancing strong analytical performance with reasonable latency and cost.

Strengths
  • General-purpose chat
  • Long context
  • Tool use
Use cases
ChatbotsContent generationAgentic workflows
Gemini 2.5 Pro
google/gemini-2.5-pro
Full spec →

Google's most capable Gemini 2.5 model with strong reasoning, thinking support, and a 1M token context window.

Strengths
  • General-purpose chat
  • Long context
  • Tool use
Use cases
ChatbotsContent generationAgentic workflows

Compare with another

Claude Opus 4.8 vs O3
anthropic/claude-opus-4.8 · openai/o3
Claude Opus 4.8 vs Gemini 2.5 Pro
anthropic/claude-opus-4.8 · google/gemini-2.5-pro
MiniMax M3 vs O3
minimax/m3 · openai/o3
MiniMax M3 vs Gemini 2.5 Pro
minimax/m3 · google/gemini-2.5-pro
Gemini 3.1 Pro vs O3
google/gemini-3.1-pro · openai/o3
Gemini 3.1 Pro vs Gemini 2.5 Pro
google/gemini-3.1-pro · google/gemini-2.5-pro
Claude Sonnet 4.6 vs O3
anthropic/claude-sonnet-4.6 · openai/o3
Claude Sonnet 4.6 vs Gemini 2.5 Pro
anthropic/claude-sonnet-4.6 · google/gemini-2.5-pro
GPT-5.5 vs O3
openai/gpt-5.5 · openai/o3
SWITCH BETWEEN THEM

One key, all 2, one line different.

from openai import OpenAI

client = OpenAI(
    base_url="https://api.aigateway.sh/v1",
    api_key="sk-aig-...",
)

# O3
client.chat.completions.create(
    model="openai/o3",
    messages=[{"role":"user","content":"hello"}],
)

# Gemini 2.5 Pro
client.chat.completions.create(
    model="google/gemini-2.5-pro",
    messages=[{"role":"user","content":"hello"}],
)
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