Tasks and inputs
Mercury 2.5 is listed for Text generation, Coding & Code Generation. It accepts text and produces text. Use the publisher’s input format and preprocessing for your chosen deployment.
Mercury 2.5 is Inception’s diffusion language model for reasoning, coding and tool workflows, with a roughly 260K context and promotional API rates.
Pricing conditions: The current models page advertises 80%-off rates of $0.04/M input, $0.004/M cached input and $0.15/M output. Regular rates shown alongside them are $0.20, $0.02 and $0.75. No promotion end date is established here; confirm the rate on your account.
Recorded modality support shows what this model can accept and produce. An undocumented modality is shown as unknown rather than assumed to be unsupported.
Accepts
Produces
Inception released Mercury 2.5 on 8 September 2026 for reasoning, coding and agent workflows. The diffusion architecture produces text through a different generation process from ordinary autoregressive models, while the hosted interface remains compatible with familiar chat-completion clients. Publisher throughput claims are not treated as latency measurements for your account.
Use mercury-2.5 on the Inception API. Tool use and structured output are listed in the current model catalog. The publisher advertises roughly 260K context; the registry records 262,144 tokens. A separate publisher-confirmed maximum output allowance has not been established for this profile, so that field stays empty. Test the complete tool loop and response handling before migration.
The models page currently displays an 80% promotion: $0.04 per million input tokens, $0.004 for cached input and $0.15 for output. The corresponding regular rates are also shown. Without a confirmed promotion end date, keep the date and account’s billing terms with a cost estimate. Compare accepted runs including retries, rather than treating a published throughput figure as a universal speed guarantee.
Build a small evaluation set from the work your application actually handles. Include incomplete information, contradictory inputs and a case that should stop for clarification. Define an acceptable deliverable before running the model, then inspect failures as carefully as successful examples. Keep input material, tools and effort settings consistent when comparing candidates.
Record the exact model identifier, deployment route and request settings with each result. Count complete runs, including rejected outputs, retries and tool calls. When the workflow creates files or code, open the files or execute the existing checks before accepting the result. A plausible first response can hide an incomplete final deliverable.
The specifications describe supported interfaces and request capacity. They do not establish a measured quality ranking or a latency guarantee for your account. SyncDev has not independently benchmarked this model. Choose a deployment after testing the languages, input formats and operating conditions that matter to your users.
Explore inception models, browse model tasks, or compare two models with the same acceptance criteria.
Compare the model on the work you need to complete.
Mercury 2.5 is listed for Text generation, Coding & Code Generation. It accepts text and produces text. Use the publisher’s input format and preprocessing for your chosen deployment.
Documented limits: 260K context. The listed route has starting rates of $0.04 input and $0.15 output per million tokens. Measure a completed task using the prompts, documents and tools your application will use. Include reasoning and retries in the result.
Use the model identifier and account requirements for the selected API route. Confirm its request limits and output format with one complete task before connecting a larger workflow.
These records share a directory category. Check the source card, output type and deployment requirements before treating a model as a replacement.
Anthropic
Claude’s small model for high-volume extraction, classification and routing, with adaptive thinking and a 1M-token context window.
Mistral AI
Mistral Large 4 is an open-weight multimodal model released in public preview on the publisher’s announced release, for general reasoning, coding and agent applications.
OpenAI
GPT-6.1 Sol is OpenAI's updated Sol model for coding and professional tasks. It accepts text and images and returns text.
inclusionAI
Ling 3.1 Flash is inclusionAI’s hybrid reasoning model for coding and tool agents, available through a hosted AI Gateway route.
Anthropic
Claude Sonnet 5.5 is an Anthropic language model that accepts text and images and returns text.
MiniMax
MiniMax M3.1 Flash Preview is a multimodal reasoning model for code and agent workflows, accessed through eligible MiniMax plans and tools.