Mercury 2 API Pricing
Mercury 2 costs $0.25 per 1M input tokens and $0.75 per 1M output tokens on US (Other)'s API. Cached input is billed at $0.025 per 1M tokens. Prices are provider list prices in USD, refreshed as sources update; see the Mercury 2 model profile for capability scores.
Price List
| Rate | Price (USD) | Notes |
|---|---|---|
| Input | $0.25 | per 1M tokens |
| Output | $0.75 | per 1M tokens |
| Cached input (read) | $0.025 | per 1M tokens |
| Blended input + output | $1.00 | 1M in + 1M out at list price |
| Context window | 128K tokens |
What a Workload Costs
Computed straight from the list prices above — token counts are illustrative workload sizes, not measurements of Mercury 2.
| Workload | Cost | Tokens |
|---|---|---|
| Short chat turn | $0.00063 | 1K in / 500 out |
| Summarize a long document | $0.026 | 100K in / 2K out |
| Agentic coding session | $0.200 | 500K in / 100K out |
| 1M input + 1M output tokens | $1.00 | 1M in / 1M out |
Effective Cost
In AI IQ's scoring, Mercury 2's list price is adjusted by a token-usage multiplier of 0.746, giving an effective cost of $0.7457 per 1M input + output tokens. That places it #18 of 117 models on the effective-cost ranking (lower is cheaper). Some models spend far more tokens than others on the same task, so effective cost compares what a unit of work really costs. Method details are on the methodology page; see all models on the cost charts and the falling cost of intelligence over time.
Cheaper Alternatives at Similar Capability
Models with a lower effective cost that score within a few IQ points of Mercury 2 (IQ 100), or better.
| Model | Provider | IQ | Effective Cost / 1M |
|---|---|---|---|
| mimo-v2-flash | Xiaomi | 105 | $0.6716 |
| gemma-4-31b | 101 | $0.3359 | |
| gemini-3.1-flash-lite | 101 | $0.5906 | |
| gpt-oss-20b | OpenAI | 100 | $0.1937 |
| gemma-4-12b | 98 | $0.2859 |