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
- #29
- by active users
- Active users
- 17
- Down 13 from 30 active users in the previous 7 days. vs previous 7 days
- Adoption
- 2.8%
- of 609 accounts
- Tokens
- 2.2B
- cache included
- Est. cost
- $313
- at public list prices
- First seen
- Aug 16, 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.
0 active users on Nov 12, 2026
Show daily values
| Date (UTC) | Active users | Tokens |
|---|---|---|
| Nov 6, 2026 | 12 | 805.4M |
| Nov 7, 2026 | 6 | 479.4M |
| Nov 8, 2026 | 6 | 76.6M |
| Nov 9, 2026 | 8 | 590.9M |
| Nov 10, 2026 | 6 | 89.3M |
| Nov 11, 2026 | 3 | 187M |
| Nov 12, 2026 | 0 | 0 |
Token mix
How the 2.2B tokens split. Cache reads are usually most of an agent's tokens and are priced far below input.
- Input6.5%
- Output0.8%
- Cache read93%
- 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.
Oh My Pi51% of this model's tokens5active users
ZCode24% of this model's tokens1active users
Claude Code7.9% of this model's tokens1active users
Gajae Code7.4% of this model's tokens1active users
Antigravity CLI5.2% of this model's tokens2active users
Hermes Agent2.0% of this model's tokens3active users
Pi1.2% of this model's tokens2active users
Antigravity0.9% of this model's tokens1active users
Codex CLI<0.1% of this model's tokens1active users
OpenCode<0.1% of this model's tokens2active users
Gemini CLI<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.
- Epoch Capabilities IndexOverall · Epoch AI158.8
Epoch Capabilities Index: 158.8
- Model
- Gemini 3.8 Flash
- Listed as
- Gemini 3.8 Flash
- Conditions
- Not reported
- Interval
- 156.8–160.9
- Unit
- ECI
- Model released
- Sep 2, 2026
- Retrieved
- Nov 12, 2026
Source · Epoch AI, ‘Capabilities & benchmarking’, epoch.ai/benchmarks (CC BY 4.0)
Rank #23 of 158 matched modelsNo conditions reportedModel released Sep 2, 2026Source: epoch.ai (opens in a new tab) - Terminal-Bench 4.1Agentic coding · Terminal-Bench18.2%
Terminal-Bench 4.1: 18.2%
- Model
- Gemini 3.8 Flash
- Listed as
- Gemini 3.8 Flash
- Conditions
- High · mini-SWE-agent
- Interval
- 14.8–21.5%
- Unit
- % resolved
- Published
- Nov 3, 2026
- Retrieved
- Nov 12, 2026
Source · Terminal-Bench 4.1 official leaderboard, tbench.ai
Rank #17 of 23 matched modelsHigh · mini-SWE-agentPublished Nov 3, 2026Source: tbench.ai (opens in a new tab) - CursorBenchAgentic coding · Cursor, collected by Epoch AI39.6%
CursorBench: 39.6%
- Model
- Gemini 3.8 Flash
- Listed as
- Gemini 3.8 Flash High
- Conditions
- High
- Unit
- score
- Model released
- Sep 2, 2026
- Retrieved
- Nov 12, 2026
Best of 2 reported results for this model.
Source · CursorBench results by Cursor, collected by Epoch AI, ‘Capabilities & benchmarking’, epoch.ai/benchmarks (CC BY 4.0)
Show 1 more result with other run conditionsHide the other results
- Listed as Gemini 3.8 Flash Medium37.3%
CursorBench: 37.3%
- Model
- Gemini 3.8 Flash
- Listed as
- Gemini 3.8 Flash Medium
- Conditions
- Medium
- Unit
- score
- Model released
- Sep 2, 2026
- Retrieved
- Nov 12, 2026
Source · CursorBench results by Cursor, collected by Epoch AI, ‘Capabilities & benchmarking’, epoch.ai/benchmarks (CC BY 4.0)
- DeepSWEAgentic coding · Datacurve, collected by Epoch AI73.8%
DeepSWE: 73.8%
- Model
- Gemini 3.8 Flash
- Listed as
- gemini-3-8-flash (high)
- Conditions
- High · mini-swe-agent
- Interval
- 72.4–75.2%
- Unit
- pass@1
- Model released
- Sep 2, 2026
- Retrieved
- Nov 12, 2026
Best of 2 reported results for this model.
Source · DeepSWE results by Datacurve, collected by Epoch AI, ‘Capabilities & benchmarking’, epoch.ai/benchmarks (CC BY 4.0)
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%
DeepSWE: 71.0%
- Model
- Gemini 3.8 Flash
- Listed as
- gemini-3-8-flash (medium)
- Conditions
- Medium · mini-swe-agent
- Interval
- 68.7–73.3%
- Unit
- pass@1
- Model released
- Sep 2, 2026
- Retrieved
- Nov 12, 2026
Source · DeepSWE results by Datacurve, collected by Epoch AI, ‘Capabilities & benchmarking’, epoch.ai/benchmarks (CC BY 4.0)
- FrontierSWEAgentic coding · FrontierSWE, collected by Epoch AI19.6%
FrontierSWE: 19.6%
- Model
- Gemini 3.8 Flash
- Listed as
- Gemini 3.8 Flash
- Conditions
- High · proximus
- Unit
- mean@5
- Model released
- Sep 2, 2026
- Retrieved
- Nov 12, 2026
Source · FrontierSWE results, collected by Epoch AI, ‘Capabilities & benchmarking’, epoch.ai/benchmarks (CC BY 4.0)
Rank #18 of 23 matched modelsHigh · proximusModel released Sep 2, 2026Source: frontierswe.com (opens in a new tab) - WebDev ArenaWeb development · LMArena1,585
WebDev Arena: 1,585
- Model
- Gemini 3.8 Flash
- Listed as
- Gemini 3.8 Flash (High)
- Conditions
- High
- Interval
- 1577–1592
- Unit
- Arena score
- Published
- Oct 19, 2026
- Retrieved
- Oct 21, 2026
Source · LMArena leaderboard dataset (lmarena-ai/leaderboard-dataset on Hugging Face), CC BY 4.0
- Agent ArenaAgents · LMArena+0.04
Agent Arena: +0.04
- Model
- Gemini 3.8 Flash
- Listed as
- Gemini 3.8 Flash (High)
- Conditions
- High · Arena Agent Mode
- Interval
- 0.03 to 0.05
- Unit
- net improvement
- Published
- Oct 19, 2026
- Retrieved
- Oct 21, 2026
Source · LMArena leaderboard dataset (lmarena-ai/leaderboard-dataset on Hugging Face), CC BY 4.0
Rank #14 of 48 matched modelsHigh · Arena Agent ModePublished Oct 19, 2026Source: huggingface.co (opens in a new tab) - GPQA DiamondReasoning · Epoch AI95.4%
GPQA Diamond: 95.4%
- Model
- Gemini 3.8 Flash
- Listed as
- gemini-3.8-flash_high
- Conditions
- High
- Unit
- % correct
- Run date
- Sep 2, 2026
- Retrieved
- Nov 12, 2026
Source · Epoch AI, ‘Capabilities & benchmarking’, epoch.ai/benchmarks (CC BY 4.0)
Near its ceiling: the top score is 96.5%, 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 AI44.5%
Humanity's Last Exam: 44.5%
- Model
- Gemini 3.8 Flash
- Listed as
- Gemini 3.8 Flash
- Conditions
- Not reported
- Unit
- % correct
- Model released
- Sep 2, 2026
- Retrieved
- Nov 12, 2026
Source · Humanity's Last Exam results, collected by Epoch AI, ‘Capabilities & benchmarking’, epoch.ai/benchmarks (CC BY 4.0)
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 AI68.4%
FrontierMath Tiers 1–3 (v2): 68.4%
- Model
- Gemini 3.8 Flash
- Listed as
- gemini-3.8-flash_high
- Conditions
- High
- Unit
- % solved
- Run date
- Sep 2, 2026
- Retrieved
- Nov 12, 2026
Source · Epoch AI, ‘Capabilities & benchmarking’, epoch.ai/benchmarks (CC BY 4.0)
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 AI69.7%
SimpleQA Verified: 69.7%
- Model
- Gemini 3.8 Flash
- Listed as
- gemini-3.8-flash_high
- Conditions
- High
- Unit
- % correct
- Run date
- Sep 2, 2026
- Retrieved
- Nov 12, 2026
Source · Epoch AI, ‘Capabilities & benchmarking’, epoch.ai/benchmarks (CC BY 4.0)
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
- $0.15
- Est. per 1M tokens
93% 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 93% of Gemini 3.8 Flash 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 $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 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
- GoogleReference
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 listed1.05M tokens of context - Vertex
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 listed1.05M tokens of context - OpenRouter
google/gemini-3.8-flash$0.75 input per 1M tokens$3.75 output per 1M tokens$0.07 cache read per 1M tokens$0.04 cache write per 1M tokens1.05M tokens of context - Vercel AI Gateway
google/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 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
- — 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
Kevin Anugerah Faza@HeavenlySpectre691.9Mtokens$132est. cost2active days$132 est. cost · 2 active days
- 2
LinYU@rinchao0721534.5Mtokens$52est. cost4active days$52 est. cost · 4 active days
- 3
Twot@twotnguyen195.3Mtokens$25est. cost6active days$25 est. cost · 6 active days
- 4
Nehr@AgileInnov8tor179.6Mtokens$25est. cost6active days$25 est. cost · 6 active days
- 5
Christopher Butler@techsaint176.9Mtokens$40est. cost5active days$40 est. cost · 5 active days
- 6
Lee SaYah@yazzang-homelab166.1Mtokens<$1est. cost3active days<$1 est. cost · 3 active days
- 7
vlun1ua@vlun1ua114.2Mtokens$11est. cost1active days$11 est. cost · 1 active days
- 8
chamdom@tmdry453069.2Mtokens$11est. cost1active days$11 est. cost · 1 active days
- 9
Han_tiv@Han-tiv34Mtokens—est. cost3active daysno price · 3 active days
- 10
Soo Hyeon Kim@kimgooneya25.8Mtokens$4est. cost2active days$4 est. cost · 2 active days
More from Google
Other Google models in the same period, by active users.
- Gemini 3.8 Flash N5.7% adoption35active users
- Gemini 4 Argon4.3% adoption26active users
- Gemini 4 Argon Trial3.8% adoption23active users
- Gemini 4 Carbon1.5% adoption9active users
- Gemini 3.8 Flash Tiered1.1% adoption7active users
- Gemini 4 Argon High1.1% adoption7active users
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.