Inception: Mercury 2.5 pricing
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… Inception: Mercury 2.5 from OpenRouter costs $0.040 per 1M input tokens and $0.150 per 1M output tokens. Cached input is $0.004 per 1M. Context window 260,000 tokens.
API id inception/mercury-2.5 · OpenRouter · source · updated 2026-09-25 · general-purpose
$0.040
Input / 1M tokens
$0.150
Output / 1M tokens
$0.004
Cached input / 1M
260K
Context window
Inception: Mercury 2.5 specifications
- Provider
- OpenRouter
- API id
inception/mercury-2.5- Model type
- general-purpose
- Context window
- 260K tokens
- Max output
- 66K tokens
- Currency
- USD
- Price source
- Provider API
- Last checked
- 2026-09-25
What Inception: Mercury 2.5 costs in practice
| Workload | Input tokens | Output tokens | Estimated cost |
|---|---|---|---|
| Short chat turn | 1,000 | 500 | $0.0001 |
| Document summary | 50,000 | 2,000 | $0.0023 |
| 1M tokens in, 200K out | 1,000,000 | 200,000 | $0.07 |
Estimates use the standard tier and ignore caching discounts, so real bills with repeated prompt prefixes are typically lower.
Common questions
- How much does Inception: Mercury 2.5 cost per 1M tokens?
- Inception: Mercury 2.5 costs $0.040 per 1M input tokens and $0.150 per 1M output tokens on the standard tier. Cached input is $0.004 per 1M.
- What is Inception: Mercury 2.5's context window?
- Inception: Mercury 2.5 accepts up to 260,000 tokens in a single request, and can return up to 65,536 output tokens.
- Is there a cheaper OpenRouter model than Inception: Mercury 2.5?
- Yes. Mistral: Mistral Nemo is $0.019 per 1M input tokens versus $0.040 for Inception: Mercury 2.5, with a 131,072 token context window.
- Where does this Inception: Mercury 2.5 price come from?
- From the OpenRouter catalogue, because OpenRouter does not publish machine-readable pricing. OpenRouter is a reseller, so its rate can differ from OpenRouter's own — verify before committing spend.
Head-to-head comparisons
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