Mercury 2
Last refreshed 2026-05-22. Next refresh: weekly.
Mercury 2 is worth evaluating for rag, long context, and classification when its provider route and context window match the workload.
Decision context: RAG task fit, 2 tracked provider routes, and research from 2026-05-19.
Use it for
- Teams evaluating rag, long context, and classification
- Workloads that can use a 131k context window
- Buyers comparing 2 tracked provider routes
Do not use it for
- Vision or document-understanding workloads
Cheapest output
$0.750
OpenRouter per 1M tokens
Provider routes
2
Tracked API hosts
Quality / dollar
Unknown
No task benchmark coverage yet
Freshness
2026-05-19
Researched 14d ago
Top use-case fit
RAG
Included by capability and metadata signals in the decision map.
Long context
Included by capability and metadata signals in the decision map.
Classification
Included by capability and metadata signals in the decision map.
Provider price ladder
Compare all 2| Provider | Input / 1M | Output / 1M | Cache | Route |
|---|---|---|---|---|
| OpenRouter | $0.250 | $0.750 | - | Serverless |
| Vercel AI Gateway | $0.250 | $0.750 | read $0.025 | Serverless |
Benchmark peer barsfor RAG
No task-mapped benchmark peers are available for this model yet.
Migration checks
No linked migration route is available for this model yet.
About
Inception Labs' Mercury 2 is a commercial-scale diffusion-based language model (dLLM) released February 2026. Unlike autoregressive transformers, Mercury uses a diffusion architecture for faster inference. Designed for code generation, reasoning, and analysis tasks. Proprietary, available via the Inception API.
Mercury 2 is a proprietary model in the Mercury family. The structured metadata tracks a 131k-token context window and structured outputs. This page tracks provider routes through OpenRouter and Vercel AI Gateway, with the cheapest tracked route listed at $0.25 input and $0.75 output per 1M tokens. No headline benchmark score is tracked for Mercury 2 yet.