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ModelCap

Mercury 2

Arena #234No linked weights

Inception Labs·#281 of 504 in the all-versions archive

Mercury 2 is a language model from Inception Labs. It ranks #281 of 504 in ModelCap's all-versions archive, with an Index score of 38.7, measured on 2 public benchmarks. Its score range of 32.4–45.0 spans positions #240–#339. It is listed at $0.25 per million input tokens and $0.75 per million output tokens from one provider. It reads up to 128K tokens of context, with no downloadable weights linked in the current source data.

Figures as of 6 Nov 2026, 13:52 UTC · download the public dataset · methodology

ModelCap Index · All-versions archive
38.7#281
Measured on 2 public benchmarks · range 32.4–45.0
Evidence as of 28 Oct 2026, 00:00 UTC
Market Gravity
21.1
Secondary market signal

Superseded by Mercury 3. It no longer holds a current-board position; its all-versions archive rank is #281.

Input
$0.25
per 1M tokens
Output
$0.75
per 1M tokens
Context
128K
tokens
Providers
1
endpoint

Providers

Uptime measured over the last 30 minutes
ProviderInputOutputContextQuantUptime
Inception$0.25$0.75128K—100.0%

Other versions (3)

ModelCap Index · All-versions archive

Methodology
38.7
Measured on 2 public benchmarks
All-versions archive
#281 of 504
Score range
32.4–45.0
Rank range
#240–#339
Evidence as of
28 Oct 2026, 00:00 UTC
Benchmarks used
Arena Coding, Arena Overall
Technical details
Public rank basis
Measured (measured)
Evidence label
Measured · 2 public benchmark observations across 2 boards
Index support
46.6% · moderate
Identity binding
Exact catalogue product · inception/inception/mercury-2 · aggregates disclosed benchmark configurations · endpoint configuration not claimed
Index observations used
2
Qualified Index evidence point
38.7
Bayesian Evidence Score · measured evidence input only

BES normalizes admitted public benchmark evidence for measured Index rows. Its legacy score and observables prior do not define the public language rank.

Observed capability
38.7
Evidence status
confirmed · 72% mass
General preference
38.7
Coding
39.2
Agents & tools
—
Reasoning
—
Evidence breadth
92%
Evidence coverage
47%
Market and catalogue signals · secondary, never the language Index rank
Usage (OpenRouter popularity)
5.5
Liquidity (providers × uptime)
34.4
Open reach (HF downloads)
—
Surface (context / tools / modalities)
70.0
Freshness
39.0
  • · OpenRouter popularity #246
  • · 1 live provider
  • · Catalogue: context 128000, reasoning, tools
  • · First seen 2026-03-04

These adoption and deployment observations remain context only. They do not change this model's ModelCap Index score or rank.

BES evidence selected · measured input only

The bounded 0–100 capability score blends each source’s competitive placement with its published achievement, then combines capability families. Evidence breadth adds a modest uncertainty adjustment; price and popularity are not part of benchmark-led rank.

Deployment readiness

Metadata index
39.7
limited · 56% metadata coverage
Not capability
Artifact reproducibility
0.0
Access & legal clarity
30.3
Deployability
80.0
Evaluation provenance
48.1

Not yet published: a pinned repository revision, the architecture and model type, a parameter count, safetensors weight metadata, the base model it derives from, a declared licence, a link to the licence terms, pinned evaluation dataset versions.

A metadata completeness and deployability index—not a safety certification, quality grade, or production-readiness claim.

Market activity

Venue coverage
Market Gravity
21.1
OpenRouter weekly popularity
#246 of 339

Market Gravity uses OpenRouter’s full-catalogue popularity order. Sparse Vercel top-ten observations appear only when published and do not affect the score.

Arena preference

Status
Ranked
Source
LMArena
Official rank
#234 of 419
Rating
1342.8
95% confidence interval
1332–1353
Votes
3K
Source published at
28 Oct 2026, 00:00 UTC
Category
overall
Identity match confidence
100%

Market Gravity breakdown

Usage55%
5.5

OpenRouter weekly popularity across the full model catalogue.

Liquidity25%
34.4

Independent providers versus the model's open or closed cohort, weighted by uptime.

Open reach15%
50.0

Hugging Face 30-day downloads for open models; neutral for closed models.

Freshness5%
39.0

Time since first public availability, on a six-month half-life.

Specification

Model ID
inception/mercury-2
Context window
128K tokens
Declared output cap
50K tokens

OpenRouter catalogue or provider-endpoint declaration. Limits can vary by provider and prompt length; a model-wide maximum has not been independently verified. OpenRouter metadata

Inputs
Text
Outputs
Text
Tokenizer
Other
Cached input tokens
$0.025 / 1M
First seen on OpenRouter
4 Mar 2026

Capabilities

  • Supported: Reasoning
  • Supported: Tool use
  • Supported: Structured output
  • Supported: Response format
  • Not supported: Moderated

Benchmark leaderboards featuring Mercury 2

All leaderboards
Public benchmark boards on which Mercury 2 has a published result
LeaderboardScoreSource rankConfigurationPublished
Arena text leaderboardArena (LMArena)13431332–1353#234 of 419Not reported28 Oct 2026
Arena coding leaderboardArena (LMArena)13921371–1412#222 of 414Default28 Oct 2026

Mercury 2: common questions

How does Mercury 2 rank among AI models?

Mercury 2 is a superseded version and is not on the current board as of 6 November 2026. Its archive position, where one exists, is shown on the page; the newer version carries the current rank.

How much does Mercury 2 cost per 1M tokens?

Mercury 2 is listed at $0.25 per 1M input tokens and $0.75 per 1M output tokens as of 6 November 2026. Prices come from the OpenRouter catalogue and re-observe on every refresh. For 1,000 requests using 2,000 input and 500 output tokens each, the listed rates imply $0.875 total (2M input + 0.5M output). This excludes caching, batch discounts, prompt-length tiers, tool charges and retries; verify the chosen endpoint's rate and limits before budgeting.

What is the context window of Mercury 2?

Mercury 2 has a published context window of 128K tokens (128,000). The snapshot lists a 50,000 token catalogue-declared route output cap. OpenRouter catalogue or provider-endpoint declaration. Limits can vary by provider and prompt length; a model-wide maximum has not been independently verified. The providers table lists each endpoint's context limit.

Is Mercury 2 open-weight?

No linked weights. No downloadable model weights are linked in the current source data. This does not identify every API or chat product that offers the model.

Which API providers serve Mercury 2?

One provider serves Mercury 2 through OpenRouter as of 6 November 2026: Inception. Each provider's price, context limit, quantization and measured uptime are in the providers table above.

Which benchmarks has Mercury 2 been evaluated on?

Mercury 2 has published results on 2 public boards tracked by ModelCap as of 6 November 2026: Arena text 1343 (#234 of 419) and Arena coding 1392 (#222 of 414). Each board page ranks every tracked model on that benchmark. The ModelCap Index scores the results its methodology admits, with published uncertainty, and shows reference boards without scoring them.

When was Mercury 2 released?

Mercury 2 first appeared in the catalogue on 4 Mar 2026. It has since been superseded by Mercury 3. Rank and price movements since then are recorded on the site's changes feed.