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ModelCap

Gemini 4 Argon

NewNo linked weights

Google·#33 of 359 on the current board·cheaper than #27 GPT-5.6 Terra

Gemini 4 Argon is a language model from Google. It ranks #33 of 359 on ModelCap's current board, with an Index score of 73.0, modeled from the publisher's launch results against measured models. Its score range of 57.1–88.8 spans positions #1–#92. It is listed at $2.00 per million input tokens and $10.00 per million output tokens across 2 providers. It reads up to 1M tokens of context, with no downloadable weights linked in the current source data.

Figures as of 13 Oct 2026, 17:47 UTC · download the public dataset · methodology

ModelCap Index · Current board
73.0#33
Modeled from the publisher's launch results against measured models · range 57.1–88.8
Market Gravity
35.9
Secondary market signal
Input
$2.00
per 1M tokens
Output
$10.00
per 1M tokens
Context
1M
tokens
Providers
2
5 endpoints

Providers

Uptime measured over the last 30 minutes
ProviderInputOutputContextQuantUptime
Google AI StudioflexCheapest$1.00$5.001M—100.0%
Googleglobal$2.00$10.001M—100.0%
Google AI Studio$2.00$10.001M—100.0%
Googleglobal/priority$3.60$18.001M—100.0%
Google AI Studiopriority$3.60$18.001M—100.0%

ModelCap Index · Current board

Methodology
73.0
Modeled from the publisher's launch results against measured models
Current board
#33 of 359
Score range
57.1–88.8
Rank range
#1–#92
Technical details
Public rank basis
Modeled · peer benchmarks (architecture)
Evidence label
Modeled · peer benchmarks · 1 reported rows against measured corpus ladders (72%); publisher-corpus-prior over 211 held-out anchors (28%); shrunk 3.7 toward the measured corpus
Index support
11.8% · weak
Identity binding
Exact catalogue product · google/google/gemini-4-argon · aggregates disclosed benchmark configurations · endpoint configuration not claimed
Index observations used
0
Qualified Index evidence point
73.0
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
73.0 ± 12.4
Independent share
0%
Shrink toward corpus
-3.7
Optimism haircut
None applied
Method
precision-weighted-v1
Channels fused into this model’s launch placement
ChannelEstimateShare
Corpus ladder · not independent
1 reported rows against measured corpus ladders
76.7 ± 14.672%
Publisher corpus prior · not independent
publisher-corpus-prior over 211 held-out anchors
63.5 ± 23.428%
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)
7.3
Liquidity (providers × uptime)
77.8
Open reach (HF downloads)
—
Surface (context / tools / modalities)
100.0
Freshness
100.0
  • · OpenRouter popularity #220
  • · 2 live providers
  • · Catalogue: context 1048576, reasoning, tools, modalities Audio/File/Image/Text/Video
  • · First seen 2026-10-13

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 · 125 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
33.1
limited · 38% metadata coverage
Not capability
Artifact reproducibility
0.0
Access & legal clarity
30.3
Deployability
90.0
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
35.9
OpenRouter weekly popularity
#220 of 336

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%
7.3

OpenRouter weekly popularity across the full model catalogue.

Liquidity25%
77.8

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%
100.0

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

Specification

Model ID
google/gemini-4-argon
Context window
1M tokens
Declared output cap
66K 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
Audio, File, Image, Text, Video
Outputs
Text
Tokenizer
Gemini
Cached input tokens
$0.10 / 1M
First seen on OpenRouter
13 Oct 2026

Capabilities

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

Compare Gemini 4 Argon with

Pick any model

Benchmark leaderboards featuring Gemini 4 Argon

All leaderboards
Public benchmark boards on which Gemini 4 Argon has a published result
LeaderboardScoreSource rankConfigurationPublished
Artificial Analysis Intelligence IndexArtificial Analysis52.6#9 of 207High13 Oct 2026
Humanity's Last Exam (Artificial Analysis run)Artificial Analysis57.1%#5 of 657High13 Oct 2026

Alternatives to Gemini 4 Argon, by the numbers

Ranked neighbours

Models within 3 places of #33 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).

Other ranked Google models

The same publisher's other current models with a public Index position.

Gemini 4 Argon: common questions

How does Gemini 4 Argon rank among AI models?

Gemini 4 Argon holds ModelCap Index position #33 of 359 ranked language models as of 13 October 2026, with an Index score of 73.0 (interval 57.1–88.8); evidence: modeled · peer benchmarks. The Index combines public benchmark boards with published uncertainty; the methodology page explains the weighting.

How much does Gemini 4 Argon cost per 1M tokens?

Gemini 4 Argon is listed at $2.00 per 1M input tokens and $10.00 per 1M output tokens as of 13 October 2026; the lowest output price among 2 providers is $5.00 on Google AI Studio. 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 $9.00 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 Gemini 4 Argon?

Gemini 4 Argon has a published context window of 1M tokens (1,048,576). The snapshot lists a 65,536 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 Gemini 4 Argon 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 Gemini 4 Argon?

2 providers serve Gemini 4 Argon through OpenRouter as of 13 October 2026: Google AI Studio and Google. Each provider's price, context limit, quantization and measured uptime are in the providers table above.

Which benchmarks has Gemini 4 Argon been evaluated on?

Gemini 4 Argon has published results on 2 public boards tracked by ModelCap as of 13 October 2026: AA Intelligence Index 52.6 (#9 of 207) and AA Humanity's Last Exam 57.1% (#5 of 657). 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.

How does Gemini 4 Argon compare with Gemini 3.5 Flash Lite?

Gemini 4 Argon ranks #33 (Index 73.0) and Gemini 3.5 Flash Lite ranks #34 (Index 72.6) on the ModelCap Index as of 13 October 2026. The head-to-head page lines up their benchmarks, listed prices, context windows and provider counts side by side.

When was Gemini 4 Argon released?

Gemini 4 Argon first appeared in the catalogue on 13 Oct 2026. It is the current version in its family. Rank and price movements since then are recorded on the site's changes feed.