Today's price · per 1M tokens
Input
$0.250
per 1M tokens
Output
$0.750
per 1M tokens
Blended
$0.375
blended $/1M — 3:1 weighted input:output
Cached input
$0.025
10% of input — prompt caching
How this price is scoped: Inception's own rate card at docs.inceptionlabs.ai/get-started/models prices Mercury Edit 2 at $0.25 input / $0.025 cached input / $0.75 output per 1M tokens, in a table headed "Input Price (1M Tokens)", so the per-1M basis is the one the vendor declares. Unlike the Mercury 2.5 row on the same card, this row carries no strikethrough and no discount marker: the 80%-off banner on that page names Mercury 2.5 only, so these are plain list prices and not a promotional rate. Inception's edit- and FIM-scoped model lists (api.inceptionlabs.ai/v1/edit/completions/models and /v1/fim/completions/models) state the same rate per token — prompt 0.00000025, completion 0.00000075, cache reads 0.000000025, cache writes free — which is $0.25 / $0.025 / $0.75 per 1M. The chat-scoped list at api.inceptionlabs.ai/v1/models does not carry this SKU (it lists Mercury 2 and Mercury 2.5 only), which reflects the endpoint it serves, not the model's availability. Checked 2026-09-11. Context window is the one field where the two surfaces disagree: the rate card prints "FIM: 32K / NextEdit: 32K" with 8,192 max output tokens, stated per endpoint, while the model-list JSON reports 128,000 context and 32,000 max output — figures that match Mercury 2's record rather than this model's — so we publish the rate card's per-endpoint figure. All three prices agree on both surfaces to the digit.
Price receipt
We read Inception's own pricing page on and found Mercury Edit 2 listed with a price on the same row — that read is where the number above comes from, recorded as a new model. We keep the page text we read; its content hash is ce0e61a51b.
Overview
Inception's diffusion code-editing model, sold on two endpoints rather than chat: fill-in-the-middle autocomplete and next-edit prediction. Like the rest of the Mercury family it generates by iterative denoising instead of left-to-right decoding, which is what buys the latency an inline IDE completion needs. 32K context on both endpoints, 8,192 max output tokens, no tool calling or structured outputs. $0.25 / $0.75 per 1M tokens, with cached input at $0.025.
Capabilities
struck through = not supportedSpecifications
- Provider
- Inception
- Context window
- 32K tokens
- Modality
- text
- Parameters
- Proprietary
- Open source
- No — proprietary
- Released
- Status
- Current
- Last updated
- Tags
Availability verified: — listed on Inception's own page