Gemini 4 Argon

GoogleKey gemini-4-argonAlso reported as google-antigravity/gemini-4-argon, cursor/gemini-4-argon, openrouter/google/gemini-4-argon, google/gemini-4-argon, google/models/gemini-4-argon, ai-studio/gemini-4-argon, devin/gemini-4-argon, opencode-go/gemini-4-argon

Rank
#26
by active users
Active users
26
Down 13 from 39 active users in the previous 7 days. vs previous 7 days
Adoption
4.3%
of 609 accounts
Tokens
8B
cache included
Est. cost
$1.7K
at public list prices
First seen
Oct 10, 2026
in any submission

Nov 6–12, 2026 (UTC)609 accounts100% of tokens from an identified modelData through Nov 12, 2026, 07:50 UTCHow we count

Daily active users

Distinct accounts that used this model on each UTC day.

3 active users on Nov 12, 2026

Daily active users for Gemini 4 Argon, Nov 6, 2026 to Nov 12, 2026. Peak 13. Use the left and right arrow keys to read each day.1580
Show daily values
Daily active users and tokens for Gemini 4 Argon
Date (UTC)Active usersTokens
Nov 6, 2026121.2B
Nov 7, 20269683.6M
Nov 8, 202691.8B
Nov 9, 2026132.7B
Nov 10, 2026131.1B
Nov 11, 20267387.3M
Nov 12, 2026357.8M

Token mix

How the 8B tokens split. Cache reads are usually most of an agent's tokens and are priced far below input.

  • Input8.3%
  • Output0.4%
  • Cache read91%
  • Cache write0%
  • Reasoning0.3%

Agents that carry Gemini 4 Argon

Each agent's share of this model's tokens, and how many accounts used the model through it.

  1. Antigravity CLI40% of this model's tokens7active users
  2. Oh My Pi38% of this model's tokens3active users
  3. Antigravity16% of this model's tokens3active users
  4. Senpi (OmO Native)2.2% of this model's tokens5active users
  5. Pi2.0% of this model's tokens4active users
  6. Gajae Code0.6% of this model's tokens1active users
  7. Antigravity IDE Extension0.6% of this model's tokens3active users
  8. Claude Code0.1% of this model's tokens1active users
  9. DeepSeek Harness0.1% of this model's tokens1active users
  10. OpenCode<0.1% of this model's tokens2active users
  11. ZCode<0.1% of this model's tokens1active users

Benchmarks

The best result for Gemini 4 Argon in each benchmark Tokscale tracks. Each benchmark has its own unit, run conditions and source, so compare a score only with other models on the same benchmark. Rank is among the models Tokscale matched in that benchmark.

All benchmarks
  • Epoch Capabilities IndexOverall · Epoch AI
    166.5
    Rank #9 of 158 matched modelsNo conditions reportedModel released Sep 30, 2026Source: epoch.ai (opens in a new tab)
  • CursorBenchAgentic coding · Cursor, collected by Epoch AI
    52.9%
    Rank #5 of 21 matched modelsHighModel released Sep 30, 2026Source: cursor.com (opens in a new tab)
    Show 3 more results with other run conditionsHide the other results
    • Listed as Gemini 4 Argon Medium
      52.8%
      MediumModel released Sep 30, 2026Source: cursor.com (opens in a new tab)
    • Listed as Gemini 4 Argon Low
      50.6%
      LowModel released Sep 30, 2026Source: cursor.com (opens in a new tab)
    • Listed as Gemini 4 Argon Minimal
      48.8%
      MinimalModel released Sep 30, 2026Source: cursor.com (opens in a new tab)
  • FrontierSWEAgentic coding · FrontierSWE, collected by Epoch AI
    55.0%
    Rank #7 of 23 matched modelsHigh · proximusModel released Sep 30, 2026Source: frontierswe.com (opens in a new tab)
  • WebDev ArenaWeb development · LMArena
    1,678
    Rank #9 of 110 matched modelsHighPublished Oct 19, 2026Source: huggingface.co (opens in a new tab)
  • Agent ArenaAgents · LMArena
    +0.12
    Rank #6 of 48 matched modelsHigh · Arena Agent ModePublished Oct 19, 2026Source: huggingface.co (opens in a new tab)
  • GPQA DiamondReasoning · Epoch AI
    96.4%
    Rank #2 of 160 matched modelsHighRun date Oct 13, 2026Source: epoch.ai (opens in a new tab)

    Near its ceiling: the top score is 96.5%, and Epoch AI estimates the reachable maximum at 97%. Differences between top models are small.

  • FrontierMath Tiers 1–3 (v2)Reasoning · Epoch AI
    86.0%
    Rank #13 of 90 matched modelsHighRun date Oct 13, 2026Source: epoch.ai (opens in a new tab)

    Near its ceiling: the top score is 95.1%, and Epoch AI estimates the reachable maximum at 95%. Differences between top models are small.

  • SimpleQA VerifiedKnowledge · Epoch AI
    76.0%
    Rank #3 of 86 matched modelsHighRun date Oct 13, 2026Source: epoch.ai (opens in a new tab)

Pricing

List prices from models.dev in US dollars per 1M tokens, retrieved Nov 12, 2026. Google is the lab's own API and the reference price for the estimates below.

Price at real agent usageEstimate at list prices

What 1M tokens cost at the reference list price when they split into input, output and cache the way Tokscale users' agents used them. It is not what anyone paid.

At this model's mix
$0.32
Est. per 1M tokens
91% cache reads
At the community mix
$0.20
Est. per 1M tokens
96% cache reads
3:1 input/output blend
$4
Per 1M tokens at list prices
No cache

Cache reads were 91% of Gemini 4 Argon tokens in the last 7 days and 96% of all tokens. The 3:1 blend, (3 × input + output) ÷ 4, is the usual comparison and ignores cache.

Assumptions

  • Google list prices per 1M tokens: input $2, output $10, cache read $0.10.
  • This model's mix is its own input, output, cache and reasoning tokens in the last 7 days.
  • The community mix is the tokens of every identified model in the last 7 days.
  • This is an estimate at list prices, not what anyone paid.
  • Reasoning tokens are priced as output.
  • Long-context tiers, batch pricing and discounts are not applied.
  • Token mixes come from public Tokscale submissions. Hidden accounts are excluded.
  • No cache-write price is listed, so cache writes are priced as input.

List prices by provider

  • GoogleReferencegemini-4-argon
    $2 input per 1M tokens$10 output per 1M tokens$0.10 cache read per 1M tokensCache write not listed1.05M tokens of context
  • Vertexgemini-4-argon
    $2 input per 1M tokens$10 output per 1M tokens$0.10 cache read per 1M tokensCache write not listed1.05M tokens of context
  • OpenRoutergoogle/gemini-4-argon
    $2 input per 1M tokens$10 output per 1M tokens$0.10 cache read per 1M tokens$0.19 cache write per 1M tokens1.05M tokens of context
  • Vercel AI Gatewaygoogle/gemini-4-argon
    $2 input per 1M tokens$10 output per 1M tokens$0.10 cache read per 1M tokensCache write not listed1M tokens of context

Specs

From models.dev (MIT), retrieved Nov 12, 2026, as the lab or the first listed provider reports them. A dash means models.dev does not list the value.

Context window
1.05M tokens
Max output
33K tokens
Input
Text, Image, Video, Audio, PDF
Output
Text
Knowledge cutoff
Mar 2026
Release date
Oct 13, 2026
Open weights
No
Reasoning
Yes
Tool calling
Yes

Top public profiles

Public profiles that used Gemini 4 Argon most in this period, by tokens. Hidden accounts are never listed.

  1. 1Brad Lishman@bradlishman2.5Btokens—est. cost7active daysno price · 7 active days
  2. 2KIM SUNGMIN@trinity-mathslab1.6Btokens$470est. cost4active days$470 est. cost · 4 active days
  3. 3Nehr@AgileInnov8tor1.5Btokens$345est. cost6active days$345 est. cost · 6 active days
  4. 4WONJUN SEO@ownuun1.1Btokens$475est. cost5active days$475 est. cost · 5 active days
  5. 5meyad-g@meyad-g500.7Mtokens$185est. cost5active days$185 est. cost · 5 active days
  6. 6WooRaZil-Boy@WooRaZil-Boy244.6Mtokens$75est. cost2active days$75 est. cost · 2 active days
  7. 7Wade Choi@minsubb13214.3Mtokens$88est. cost2active days$88 est. cost · 2 active days
  8. 8Minseo Choi@trac3r00128.8Mtokens—est. cost1active daysno price · 1 active days
  9. 9崔鹏飞 Cui Pengfei@cuipengfei87.7Mtokens$28est. cost4active days$28 est. cost · 4 active days
  10. 10sousoul@sousouliao66.1Mtokens—est. cost5active daysno price · 5 active days

Other Google models in the same period, by active users.

  1. Gemini 3.8 Flash N5.7% adoption35active users
  2. Gemini 4 Argon Trial3.8% adoption23active users
  3. Gemini 3.8 Flash2.8% adoption17active users
  4. Gemini 4 Carbon1.5% adoption9active users
  5. Gemini 3.8 Flash Tiered1.1% adoption7active users
  6. Gemini 4 Argon High1.1% adoption7active users
All models

Sources and attribution

Each score keeps its own source, unit and run conditions. Tokscale does not combine benchmarks into one score, and a missing score means the model was not evaluated, not that it scored zero.

  • Epoch AIEpoch Capabilities Index, Epoch's own runs and the external results it collects.CC BY 4.0 · Retrieved Nov 12, 2026 · Data through Nov 9, 2026Epoch AI, ‘Capabilities & benchmarking’. Published online at epoch.ai. Retrieved from https://epoch.ai/benchmarks.
  • LMArenaWebDev Arena and Agent Arena leaderboards.CC BY 4.0 · Retrieved Oct 21, 2026 · Data through Oct 19, 2026LMArena leaderboard dataset (lmarena-ai/leaderboard-dataset), Hugging Face.
  • models.devSpecs and list prices per provider.MIT · Retrieved Nov 12, 2026models.dev, an open catalog of AI models (github.com/anomalyco/models.dev).
  • TokscaleActive users, tokens and token mix from public Tokscale submissions. Hidden accounts are excluded.How we count