Gemini 3.1 Pro Preview Customtools

GoogleKey gemini-3.1-pro-preview-customtoolsAlso reported as google/gemini-3.1-pro-preview-customtools

Rank
#794
by active users
Active users
1
No change from 1 active users in the previous 30 days. vs previous 30 days
Adoption
0.1%
of 961 accounts
Tokens
137K
cache included
Est. cost
<$1
at public list prices
First seen
Feb 20, 2026
in any submission

Oct 14 – Nov 12, 2026 (UTC)961 accounts100% of tokens from an identified modelData through Nov 12, 2026, 06:36 UTCHow we count

Daily active users

Distinct accounts that used this model on each UTC day.

0 active users on Nov 12, 2026

Daily active users for Gemini 3.1 Pro Preview Customtools, Oct 14, 2026 to Nov 12, 2026. Peak 1. Use the left and right arrow keys to read each day.110
Show daily values
Daily active users and tokens for Gemini 3.1 Pro Preview Customtools
Date (UTC)Active usersTokens
Oct 14, 202600
Oct 15, 202600
Oct 16, 202600
Oct 17, 202600
Oct 18, 202600
Oct 19, 202600
Oct 20, 202600
Oct 21, 202600
Oct 22, 202600
Oct 23, 202600
Oct 24, 202600
Oct 25, 202600
Oct 26, 202600
Oct 27, 202600
Oct 28, 20261137K
Oct 29, 202600
Oct 30, 202600
Oct 31, 202600
Nov 1, 202600
Nov 2, 202600
Nov 3, 202600
Nov 4, 202600
Nov 5, 202600
Nov 6, 202600
Nov 7, 202600
Nov 8, 202600
Nov 9, 202600
Nov 10, 202600
Nov 11, 202600
Nov 12, 202600

Token mix

How the 137K tokens split. Cache reads are usually most of an agent's tokens and are priced far below input.

  • Input74%
  • Output0.6%
  • Cache read23%
  • Cache write0%
  • Reasoning1.7%

Agents that carry Gemini 3.1 Pro Preview Customtools

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

  1. Gemini CLI100% of this model's tokens1active users

Benchmarks

The best result for Gemini 3.1 Pro Preview Customtools 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
  • SWE-bench VerifiedHistory · Epoch AI
    75.6%
    Rank #12 of 32 matched modelsNo conditions reportedRun date Feb 24, 2026Source: epoch.ai (opens in a new tab)

    History only. Newer agentic coding benchmarks are on the main board.

Not evaluated: Epoch Capabilities Index, GPQA Diamond, Humanity's Last Exam, FrontierMath Tiers 1–3 (v2), SimpleQA Verified, Terminal-Bench 4.1, CursorBench, DeepSWE, FrontierSWE, Agent Arena, WebDev Arena. A missing result is not a score of zero.

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
$1.82
Est. per 1M tokens
23% cache reads
At the community mix
$0.30
Est. per 1M tokens
96% cache reads
3:1 input/output blend
$4.50
Per 1M tokens at list prices
No cache

Cache reads were 23% of Gemini 3.1 Pro Preview Customtools tokens in the last 30 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 $12, cache read $0.20.
  • This model's mix is its own input, output, cache and reasoning tokens in the last 30 days.
  • The community mix is the tokens of every identified model in the last 30 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-3.1-pro-preview-customtools
    $2 input per 1M tokens$12 output per 1M tokens$0.20 cache read per 1M tokensCache write not listed1.05M tokens of context
  • Vertexgemini-3.1-pro-preview-customtools
    $2 input per 1M tokens$12 output per 1M tokens$0.20 cache read per 1M tokensCache write not listed1.05M tokens of context
  • OpenRoutergoogle/gemini-3.1-pro-preview-customtools
    $2 input per 1M tokens$12 output per 1M tokens$0.20 cache read per 1M tokens$0.38 cache write per 1M tokens1.05M 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
66K tokens
Input
Text, Image, Video, Audio, PDF
Output
Text
Knowledge cutoff
Jan 2025
Release date
Feb 19, 2026
Open weights
No
Reasoning
Yes
Tool calling
Yes

Top public profiles

Public profiles that used Gemini 3.1 Pro Preview Customtools most in this period, by tokens. Hidden accounts are never listed.

  1. 1Journey Hwang@journeyWorker137Ktokens<$1est. cost1active days<$1 est. cost · 1 active days

More from Google

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

  1. Gemini 3.8 Flash N15% adoption140active users
  2. Gemini 4 Argon8.5% adoption82active users
  3. Gemini 4 Argon Trial7.9% adoption76active users
  4. Gemini 3.8 Flash6.9% adoption66active users
  5. Gemini 3.8 Flash Tiered3.7% adoption36active users
  6. Gemini 4 Argon High1.8% adoption17active 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.
  • 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