o1-pro Paid vs INMercury 2.5 Paid
o1-pro vs Mercury 2.5 compared — price per token, context window, multimodality, openness and which to choose. Full 2026 breakdown.
o1-pro — full profile › · Mercury 2.5 — 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)
$0.15 /M outputManaged API (no infra to run)
o1-pro vs Mercury 2.5 specs
| Spec | o1-pro | Mercury 2.5 | Winner |
|---|---|---|---|
| Maker | OpenAI | Inception | – |
| Type | Proprietary | Proprietary | – |
| Context window | 200K tokens | 260K tokens | INMercury 2.5 |
| Input price | $150/M | $0.04/M | INMercury 2.5 |
| Output price | $600/M | $0.15/M | INMercury 2.5 |
| Vision / multimodal | Yes | No | |
| Tool / function calling | No | Yes | INMercury 2.5 |
| Self-hostable | No (API only) | No (API only) | – |
| License | Proprietary | Proprietary | – |
Price gap & when to choose each
Mercury 2.5 is ~4,000× cheaper than o1-pro on output tokens ($0.15 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 260K context window
- You want the lower output price
- You value reliability & ecosystem
- You don't want to manage infrastructure
Feature comparison
| Capability | o1-pro | Mercury 2.5 |
|---|---|---|
| Open weights (downloadable) | ✗ | ✗ |
| Self-hostable | ✗ | ✗ |
| Runs fully offline | ✗ | ✗ |
| Vision / multimodal | ✓ | ✗ |
| Tool / function calling | ✗ | ✓ |
| 1M+ context window | ✗ | ✗ |
Benchmarks: o1-pro vs Mercury 2.5
Independent benchmark scores measured by Artificial Analysis. Higher is better (except latency).
Benchmark data by Artificial Analysis.
How o1-pro and Mercury 2.5 score
| Criterion | o1-pro | Mercury 2.5 |
|---|---|---|
| Cost-efficiency | 2.0 | 5.0 |
| Context window | 4.0 | 4.0 |
| Openness | 1.5 | 1.5 |
| Self-hosting | 1.0 | 1.0 |
| Multimodality | 3.5 | 3.5 |
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...
Mercury 2.5 Paid
Mercury 2.5 is the fastest reasoning LLM, and the latest diffusion LLM (dLLM) from Inception. Instead of generating tokens sequentially, Mercury 2.5 produces and refines multiple tokens in parallel, achieving...
Frequently asked questions
o1-pro vs Mercury 2.5 — which is cheaper?
Mercury 2.5 is cheaper on output ($0.15/M vs $600/M).
Which has the larger context window?
Mercury 2.5 offers the larger context window (260K tokens).
o1-pro vs Mercury 2.5 — which should I pick in 2026?
Choose Mercury 2.5 for the lower output price ($0.15/M vs $600/M). It also gives you the larger 260K context window.
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