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ModelCap

Mercury 3

No linked weights6.9d #161 → #167

Inception Labs·#167 of 352 on the current board·cheaper than #163 Command A

Mercury 3 is a language model from Inception Labs. It ranks #167 of 352 on ModelCap's current board, with an Index score of 39.3, modeled from its measured predecessor. Its score range of 25.6–53.0 spans positions #111–#257. It is listed at $0.10 per million input tokens and $0.35 per million output tokens from one provider. It reads up to 1M tokens of context, with no downloadable weights linked in the current source data.

Figures as of 6 Nov 2026, 20:32 UTC · download the public dataset · methodology

ModelCap Index · Current board
39.3#167
Modeled from its measured predecessor · range 25.6–53.0
Market Gravity
33.1Increased by 0.2
Secondary market signal
Input
$0.10
per 1M tokens
Output
$0.35
per 1M tokens
Context
1M
tokens
Providers
1
endpoint

Providers

Uptime measured over the last 30 minutes
ProviderInputOutputContextQuantUptime
Inception$0.10$0.351M—100.0%

Other versions (3)

ModelCap Index · Current board

Methodology
39.3
Modeled from its measured predecessor
Current board
#167 of 352
Score range
25.6–53.0
Rank range
#111–#257
Technical details
Public rank basis
Modeled · succession (architecture)
Evidence label
Modeled · succession · global-corpus-prior over 210 held-out anchors (20%); opens from measured predecessor inception/mercury-2 (80%); shrunk 3.6 up toward the measured corpus
Index support
23.3% · limited
Identity binding
Exact catalogue product · inception/inception/mercury-3 · aggregates disclosed benchmark configurations · endpoint configuration not claimed
Index observations used
0
Qualified Index evidence point
39.3
How this position was produced · fused launch placement

No general-family board lists this model yet. Its point estimate is the precision-weighted mean of every channel that spoke for it; each channel’s share is the weight it carried. Independent measurements replace this placement as boards list the model.

Fused estimate
39.3 ± 10.7
Independent share
0%
Shrink toward corpus
+3.6
Optimism haircut
None applied
Method
precision-weighted-v1
Channels fused into this model’s launch placement
ChannelEstimateShare
Publisher corpus prior · not independent
global-corpus-prior over 210 held-out anchors
53.5 ± 23.820%
Family succession · not independent
opens from measured predecessor inception/mercury-2
35.7 ± 12.080%
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
—
Evidence status
No admitted measured evidence
General preference
—
Coding
—
Agents & tools
—
Reasoning
—
Evidence breadth
0%
Evidence coverage
0%
Market and catalogue signals · secondary, never the language Index rank
Usage (OpenRouter popularity)
22.6
Liquidity (providers × uptime)
34.4
Open reach (HF downloads)
—
Surface (context / tools / modalities)
85.0
Freshness
92.2
  • · OpenRouter popularity #91
  • · 1 live provider
  • · Catalogue: context 1000000, reasoning, tools
  • · First seen 2026-10-16

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

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.

Experimental capability estimate

Estimate policy
Estimator abstained

insufficient-artifact-metadata

Feature coverage
86%
Training support
220 models · 128 lineages

insufficient-artifact-metadata. This layer predicts from admitted evidence and safe metadata only. It never enters ModelCap Score or rank.

Deployment readiness

Metadata index
30.1
limited · 38% metadata coverage
Not capability
Artifact reproducibility
0.0
Access & legal clarity
30.3
Deployability
80.0
Evaluation provenance
0.0

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, admitted benchmark results, results across several capability areas, results from more than one source, a confident match to its benchmark entries, 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
33.1
OpenRouter weekly popularity
#91 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

No matched Arena rating

This model is visible because it is available in the live catalogue, but it has no trustworthy community result yet. ModelCap does not infer a quality score from price, features, or market activity.

Market Gravity breakdown

Usage55%
22.6

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%
92.2

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

Specification

Model ID
inception/mercury-3
Context window
1M tokens
Declared output cap
131K 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
$0.01 / 1M
First seen on OpenRouter
16 Oct 2026

Capabilities

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

Alternatives to Mercury 3, by the numbers

Ranked neighbours

Models within 3 places of #167 on the ModelCap Index.

Cheaper at a similar or higher Index

Index score within 3 points of, or above, this model's, with a lower listed blended price (3:1 input:output).

Mercury 3: common questions

How does Mercury 3 rank among AI models?

Mercury 3 holds ModelCap Index position #167 of 352 ranked language models as of 6 November 2026, with an Index score of 39.3 (interval 25.6–53.0); evidence: modeled · succession. The Index combines public benchmark boards with published uncertainty; the methodology page explains the weighting.

How much does Mercury 3 cost per 1M tokens?

Mercury 3 is listed at $0.10 per 1M input tokens and $0.35 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 $0.375 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 3?

Mercury 3 has a published context window of 1M tokens (1,000,000). The snapshot lists a 131,072 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 3 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 3?

One provider serves Mercury 3 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 3 been evaluated on?

Mercury 3's Index position rests on the evidence listed on this page; it has no result on the public boards ModelCap tracks as separate leaderboards as of 6 November 2026. The evidence panel names each source and its publication date.

When was Mercury 3 released?

Mercury 3 first appeared in the catalogue on 16 Oct 2026. It is the current version in its family. Rank and price movements since then are recorded on the site's changes feed.