Gemini 3.8 Flash

GoogleKey gemini-3.8-flashAlso reported as google-antigravity/gemini-3.8-flash, auto/gemini-3.8-flash, google/gemini-3.8-flash, antigravity/gemini-3.8-flash, ag/gemini-3.8-flash, cursor/gemini-3.8-flash, github/gemini-3.8-flash, cline-free/gemini-3.8-flash, sub2api-gemini/gemini-3.8-flash, agy-cli/gemini-3.8-flash, mm0e-com/commandcode/google/gemini-3.8-flash, gemini/gemini-3.8-flash, hr-gl/gemini-3.8-flash, models/gemini-3.8-flash, router_client:unknown/models/gemini-3.8-flash, gh/gemini-3.8-flash, combo/gemini-3.8-flash, google-vertex-ai/google/gemini-3.8-flash

Rank
#30
by active users
Active users
66
Down 154 from 220 active users in the previous 30 days. vs previous 30 days
Adoption
6.9%
of 958 accounts
Tokens
37B
cache included
Est. cost
$4.7K
at public list prices
First seen
Aug 16, 2026
in any submission

Oct 14 – Nov 12, 2026 (UTC)958 accounts100% of tokens from an identified modelData through Nov 12, 2026, 00:36 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 3.8 Flash, Oct 14, 2026 to Nov 12, 2026. Peak 20. Use the left and right arrow keys to read each day.20100
Show daily values
Daily active users and tokens for Gemini 3.8 Flash
Date (UTC)Active usersTokens
Oct 14, 202620576M
Oct 15, 202613990.3M
Oct 16, 2026131.5B
Oct 17, 202613928.9M
Oct 18, 2026151.2B
Oct 19, 2026152.1B
Oct 20, 2026151.6B
Oct 21, 2026141.4B
Oct 22, 20269690M
Oct 23, 2026111.3B
Oct 24, 2026111.7B
Oct 25, 2026101.2B
Oct 26, 2026112.1B
Oct 27, 2026162.5B
Oct 28, 2026112.3B
Oct 29, 2026161.2B
Oct 30, 2026122.6B
Oct 31, 2026111.4B
Nov 1, 2026101.1B
Nov 2, 2026121.4B
Nov 3, 2026113.9B
Nov 4, 20265344.7M
Nov 5, 202611659M
Nov 6, 202612805.4M
Nov 7, 20266479.4M
Nov 8, 2026676.6M
Nov 9, 20268590.9M
Nov 10, 2026689.3M
Nov 11, 20263187M
Nov 12, 202600

Token mix

How the 37B tokens split. Cache reads are usually most of an agent's tokens and are priced far below input.

  • Input5.6%
  • Output0.3%
  • Cache read94%
  • Cache write0%
  • Reasoning<0.1%

Agents that carry Gemini 3.8 Flash

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

  1. Oh My Pi49% of this model's tokens16active users
  2. Pi30% of this model's tokens9active users
  3. Antigravity CLI8.8% of this model's tokens16active users
  4. DeepSeek Harness3.3% of this model's tokens2active users
  5. Senpi (OmO Native)3.1% of this model's tokens6active users
  6. Codex CLI1.6% of this model's tokens6active users
  7. ZCode1.4% of this model's tokens1active users
  8. OpenCode0.9% of this model's tokens10active users
  9. Claude Code0.5% of this model's tokens1active users
  10. Gajae Code0.4% of this model's tokens1active users
  11. Hermes Agent0.3% of this model's tokens6active users
  12. Antigravity<0.1% of this model's tokens2active users
  13. Junie<0.1% of this model's tokens1active users
  14. 9Router<0.1% of this model's tokens1active users
  15. Aside<0.1% of this model's tokens1active users
  16. Crush<0.1% of this model's tokens1active users
  17. Gemini CLI<0.1% of this model's tokens3active users
  18. Copilot<0.1% of this model's tokens1active users
  19. Synthetic<0.1% of this model's tokens1active users

Benchmarks

The best result for Gemini 3.8 Flash 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
    157.4
    Rank #20 of 160 matched modelsNo conditions reportedModel released Sep 2, 2026Source: epoch.ai (opens in a new tab)
  • Terminal-Bench 4.0Agentic coding · Terminal-Bench
    19.1%
    Rank #17 of 23 matched modelsHigh · mini-SWE-agentPublished Sep 3, 2026Source: tbench.ai (opens in a new tab)
  • CursorBenchAgentic coding · Cursor, collected by Epoch AI
    39.6%
    Rank #14 of 18 matched modelsHighModel released Sep 2, 2026Source: cursor.com (opens in a new tab)
    Show 1 more result with other run conditionsHide the other results
    • Listed as Gemini 3.8 Flash Medium
      37.3%
      MediumModel released Sep 2, 2026Source: cursor.com (opens in a new tab)
  • DeepSWEAgentic coding · Datacurve, collected by Epoch AI
    73.8%
    Rank #2 of 26 matched modelsHigh · mini-swe-agentModel released Sep 2, 2026Source: deepswe.datacurve.ai (opens in a new tab)
    Show 1 more result with other run conditionsHide the other results
    • Listed as gemini-3-8-flash (medium)
      71.0%
      Medium · mini-swe-agentModel released Sep 2, 2026Source: deepswe.datacurve.ai (opens in a new tab)
  • FrontierSWEAgentic coding · FrontierSWE, collected by Epoch AI
    19.6%
    Rank #16 of 21 matched modelsHigh · proximusModel released Sep 2, 2026Source: frontierswe.com (opens in a new tab)
  • WebDev ArenaWeb development · LMArena
    1,585
    Rank #31 of 110 matched modelsHighPublished Oct 19, 2026Source: huggingface.co (opens in a new tab)
  • Agent ArenaAgents · LMArena
    +0.04
    Rank #14 of 48 matched modelsHigh · Arena Agent ModePublished Oct 19, 2026Source: huggingface.co (opens in a new tab)
  • GPQA DiamondReasoning · Epoch AI
    95.4%
    Rank #5 of 151 matched modelsHighRun date Sep 2, 2026Source: epoch.ai (opens in a new tab)

    Near its ceiling: the top score is 96.4%, and Epoch AI estimates the reachable maximum at 97%. Differences between top models are small.

  • Humanity's Last ExamReasoning · Center for AI Safety and Scale AI, collected by Epoch AI
    44.5%
    Rank #5 of 40 matched modelsNo conditions reportedModel released Sep 2, 2026Source: lastexam.ai (opens in a new tab)
  • FrontierMath Tiers 1–3 (v2)Reasoning · Epoch AI
    68.4%
    Rank #29 of 86 matched modelsHighRun date Sep 2, 2026Source: epoch.ai (opens in a new tab)

    Near its ceiling: the top score is 93.7%, and Epoch AI estimates the reachable maximum at 95%. Differences between top models are small.

  • SimpleQA VerifiedKnowledge · Epoch AI
    69.7%
    Rank #8 of 80 matched modelsHighRun date Sep 2, 2026Source: epoch.ai (opens in a new tab)

Pricing

List prices from models.dev in US dollars per 1M tokens, retrieved Oct 21, 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
$0.13
Est. per 1M tokens
94% cache reads
At the community mix
$0.11
Est. per 1M tokens
96% cache reads
3:1 input/output blend
$1.50
Per 1M tokens at list prices
No cache

Cache reads were 94% of Gemini 3.8 Flash 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 $0.75, output $3.75, cache read $0.07.
  • 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-3.8-flash
    $0.75 input per 1M tokens$3.75 output per 1M tokens$0.07 cache read per 1M tokensCache write not listed1.05M tokens of context
  • Vertexgemini-3.8-flash
    $0.75 input per 1M tokens$3.75 output per 1M tokens$0.07 cache read per 1M tokensCache write not listed1.05M tokens of context
  • OpenRoutergoogle/gemini-3.8-flash
    $0.82 input per 1M tokens$4.13 output per 1M tokens$0.08 cache read per 1M tokens$0.04 cache write per 1M tokens1.05M tokens of context
  • Vercel AI Gatewaygoogle/gemini-3.8-flash
    $0.75 input per 1M tokens$3.75 output per 1M tokens$0.07 cache read per 1M tokensCache write not listed1M tokens of context

Specs

From models.dev (MIT), retrieved Oct 21, 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
— not listed
Release date
Sep 2, 2026
Open weights
No
Reasoning
Yes
Tool calling
Yes

Top public profiles

Public profiles that used Gemini 3.8 Flash most in this period, by tokens. Hidden accounts are never listed.

  1. 1Nehr@AgileInnov8tor16.1Btokens$2Kest. cost29active days$2K est. cost · 29 active days
  2. 2rizkyathoriq19@rizkyathoriq194Btokens$414est. cost14active days$414 est. cost · 14 active days
  3. 3vlun1ua@vlun1ua3.1Btokens$292est. cost23active days$292 est. cost · 23 active days
  4. 4Joosung Park@hyperlapse1222.9Btokens$475est. cost14active days$475 est. cost · 14 active days
  5. 5LinYU@rinchao07211.8Btokens$186est. cost9active days$186 est. cost · 9 active days
  6. 6Lion Chen@LionChenA1.7Btokens$194est. cost16active days$194 est. cost · 16 active days
  7. 7Kevin Anugerah Faza@HeavenlySpectre1.4Btokens$267est. cost15active days$267 est. cost · 15 active days
  8. 8luzhnan@luzhnan1.2Btokens$146est. cost14active days$146 est. cost · 14 active days
  9. 9Woonggi Min@minpeter967.9Mtokens$98est. cost4active days$98 est. cost · 4 active days
  10. 10raizo@iraizo843.5Mtokens$84est. cost7active days$84 est. cost · 7 active days

More from Google

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

  1. Gemini 3.8 Flash N14% adoption138active users
  2. Gemini 4 Argon8.6% adoption82active users
  3. Gemini 4 Argon Trial7.7% adoption74active users
  4. Gemini 3.8 Flash Tiered3.7% adoption35active users
  5. Gemini 4 Argon High1.8% adoption17active users
  6. Gemini 3.8 Flash High1.6% adoption15active 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 Oct 21, 2026 · Data through Oct 15, 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.
  • Terminal-BenchTerminal-Bench 4.0 official leaderboard rows (results only, no task content).Terms not stated · Retrieved Oct 21, 2026 · Data through Oct 6, 2026Terminal-Bench 4.0 leaderboard, tbench.ai. Every score links back to the leaderboard.
  • models.devSpecs and list prices per provider.MIT · Retrieved Oct 21, 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