o1-pro Paid vs 
Gemini 4 Argon Paid
o1-pro vs Gemini 4 Argon compared — price per token, context window, multimodality, openness and which to choose. Full 2026 breakdown.
o1-pro — full profile › · Gemini 4 Argon — full profile ›
Prices & specs refreshed from live data · olud.ai
Open-model prices = cheapest provider via OpenRouter; official maker rates may be higher.
$600 /M outputManaged API (no infra to run)
$10 /M outputManaged API (no infra to run)
o1-pro vs Gemini 4 Argon specs
| Spec | o1-pro | Gemini 4 Argon | Winner |
|---|---|---|---|
| Maker | OpenAI | – | |
| Type | Proprietary | Proprietary | – |
| Context window | 200K tokens | 1M tokens | |
| Input price | $150/M | $2/M | |
| Output price | $600/M | $10/M | |
| Vision / multimodal | Yes | Yes | = Tie |
| Tool / function calling | No | Yes | |
| Self-hostable | No (API only) | No (API only) | – |
| License | Proprietary | Proprietary | – |
Price gap & when to choose each
Gemini 4 Argon is ~60× cheaper than o1-pro on output tokens ($10 vs $600 per M tokens).
- You want frontier performance through a managed API
- You value reliability & ecosystem
- You don't want to manage infrastructure
- You want frontier performance through a managed API
- You need the longer 1M context window
- You want the lower output price
- You value reliability & ecosystem
- You don't want to manage infrastructure
Feature comparison
| Capability | o1-pro | Gemini 4 Argon |
|---|---|---|
| Open weights (downloadable) | ✗ | ✗ |
| Self-hostable | ✗ | ✗ |
| Runs fully offline | ✗ | ✗ |
| Vision / multimodal | ✓ | ✓ |
| Tool / function calling | ✗ | ✓ |
| 1M+ context window | ✗ | ✓ |
Benchmarks: o1-pro vs Gemini 4 Argon
Independent benchmark scores measured by Artificial Analysis. Higher is better (except latency).
Benchmark data by Artificial Analysis.
How o1-pro and Gemini 4 Argon score
| Criterion | o1-pro | Gemini 4 Argon |
|---|---|---|
| Cost-efficiency | 2.0 | 3.5 |
| Context window | 4.0 | 5.0 |
| Openness | 1.5 | 1.5 |
| Self-hosting | 1.0 | 1.0 |
| Multimodality | 3.5 | 5.0 |
Scores come from live data — output price (cost), context length, open vs closed weights (openness & self-hosting) and vision/tool support (multimodality). Raw task quality isn't scored here; it depends on your benchmark — see the verdict.
What each model is
o1-pro Paid
The o1 series of models are trained with reinforcement learning to think before they answer and perform complex reasoning. The o1-pro model uses more compute to think harder and provide...
Gemini 4 Argon Paid
Gemini 4 Argon is Google's flagship reasoning model, built for complex software engineering, deep mathematical and scientific problem solving, and autonomous multi-step agents. Google trained it to keep context across...
Other models in these families
These variants are tracked but not compared here — one page per family keeps the comparison readable.
Frequently asked questions
o1-pro vs Gemini 4 Argon — which is cheaper?
Gemini 4 Argon is cheaper on output ($10/M vs $600/M).
Which has the larger context window?
Gemini 4 Argon offers the larger context window (1M tokens).
o1-pro vs Gemini 4 Argon — which should I pick in 2026?
Choose Gemini 4 Argon for the lower output price ($10/M vs $600/M). It also gives you the larger 1M context window.
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