Gemini 2.5 Pro
GoogleKey gemini-2.5-proAlso reported as google/gemini-2.5-pro, models/gemini-2.5-pro, vertex/gemini-2.5-pro
- Rank
- #935
- by active users
- Active users
- 1
- Down 4 from 5 active users in the previous 30 days. vs previous 30 days
- Adoption
- 0.1%
- of 958 accounts
- Tokens
- 10.4K
- cache included
- Est. cost
- <$1
- at public list prices
- First seen
- Jul 10, 2025
- in any submission
Oct 14 – Nov 12, 2026 (UTC)958 accounts100% of tokens from an identified modelData through Nov 12, 2026, 01:19 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 |
|---|---|---|
| Oct 14, 2026 | 1 | 803 |
| Oct 15, 2026 | 1 | 803 |
| Oct 16, 2026 | 1 | 803 |
| Oct 17, 2026 | 1 | 803 |
| Oct 18, 2026 | 1 | 803 |
| Oct 19, 2026 | 1 | 803 |
| Oct 20, 2026 | 1 | 803 |
| Oct 21, 2026 | 1 | 803 |
| Oct 22, 2026 | 1 | 803 |
| Oct 23, 2026 | 1 | 803 |
| Oct 24, 2026 | 1 | 803 |
| Oct 25, 2026 | 1 | 803 |
| Oct 26, 2026 | 1 | 803 |
| Oct 27, 2026 | 0 | 0 |
| Oct 28, 2026 | 0 | 0 |
| Oct 29, 2026 | 0 | 0 |
| Oct 30, 2026 | 0 | 0 |
| Oct 31, 2026 | 0 | 0 |
| Nov 1, 2026 | 0 | 0 |
| Nov 2, 2026 | 0 | 0 |
| Nov 3, 2026 | 0 | 0 |
| Nov 4, 2026 | 0 | 0 |
| Nov 5, 2026 | 0 | 0 |
| Nov 6, 2026 | 0 | 0 |
| Nov 7, 2026 | 0 | 0 |
| Nov 8, 2026 | 0 | 0 |
| Nov 9, 2026 | 0 | 0 |
| Nov 10, 2026 | 0 | 0 |
| Nov 11, 2026 | 0 | 0 |
| Nov 12, 2026 | 0 | 0 |
Token mix
How the 10.4K tokens split. Cache reads are usually most of an agent's tokens and are priced far below input.
- Input94%
- Output5.7%
- Cache read0%
- Cache write0%
- Reasoning0%
Agents that carry Gemini 2.5 Pro
Each agent's share of this model's tokens, and how many accounts used the model through it.
Codex CLI100% of this model's tokens1active users
Benchmarks
The best result for Gemini 2.5 Pro 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 AI145.1
Epoch Capabilities Index: 145.1
- Model
- Gemini 2.5 Pro
- Listed as
- Gemini 2.5 Pro (Jun 2025)
- Conditions
- Not reported
- Interval
- 143.4–146.7
- Unit
- ECI
- Model released
- Jun 5, 2025
- Retrieved
- Oct 21, 2026
Source · Epoch AI, ‘Capabilities & benchmarking’, epoch.ai/benchmarks (CC BY 4.0)
Rank #88 of 160 matched modelsNo conditions reportedModel released Jun 5, 2025Source: epoch.ai (opens in a new tab) - WebDev ArenaWeb development · LMArena1,226
WebDev Arena: 1,226
- Model
- Gemini 2.5 Pro
- Listed as
- Gemini 2.5 Pro
- Conditions
- Not reported
- Interval
- 1210–1242
- 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
Rank #107 of 110 matched modelsNo conditions reportedPublished Oct 19, 2026Source: huggingface.co (opens in a new tab) - GPQA DiamondReasoning · Epoch AI85.3%
GPQA Diamond: 85.3%
- Model
- Gemini 2.5 Pro
- Listed as
- gemini-2.5-pro
- Conditions
- Not reported
- Unit
- % correct
- Run date
- Nov 16, 2025
- Retrieved
- Oct 21, 2026
Source · Epoch AI, ‘Capabilities & benchmarking’, epoch.ai/benchmarks (CC BY 4.0)
Rank #67 of 151 matched modelsNo conditions reportedRun date Nov 16, 2025Source: 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.
- FrontierMath Tiers 1–3 (v2)Reasoning · Epoch AI24.6%
FrontierMath Tiers 1–3 (v2): 24.6%
- Model
- Gemini 2.5 Pro
- Listed as
- gemini-2.5-pro
- Conditions
- Not reported
- Unit
- % solved
- Run date
- Jun 11, 2026
- Retrieved
- Oct 21, 2026
Source · Epoch AI, ‘Capabilities & benchmarking’, epoch.ai/benchmarks (CC BY 4.0)
Rank #71 of 86 matched modelsNo conditions reportedRun date Jun 11, 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.
- SWE-bench VerifiedHistory · Epoch AI57.6%
SWE-bench Verified: 57.6%
- Model
- Gemini 2.5 Pro
- Listed as
- gemini-2.5-pro
- Conditions
- Not reported
- Unit
- % resolved
- Run date
- Feb 13, 2026
- Retrieved
- Oct 21, 2026
Source · Epoch AI, ‘Capabilities & benchmarking’, epoch.ai/benchmarks (CC BY 4.0)
Rank #30 of 32 matched modelsNo conditions reportedRun date Feb 13, 2026Source: epoch.ai (opens in a new tab)History only. Newer agentic coding benchmarks are on the main board.
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
- $1.75
- Est. per 1M tokens
0% cache reads - At the community mix
- $0.20
- Est. per 1M tokens
96% cache reads - 3:1 input/output blend
- $3.44
- Per 1M tokens at list prices
No cache
Cache reads were 0% of Gemini 2.5 Pro 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 $1.25, output $10, cache read $0.13.
- 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
- GoogleReference
gemini-2.5-pro$1.25 input per 1M tokens$10 output per 1M tokens$0.13 cache read per 1M tokensCache write not listed1.05M tokens of context - Vertex
gemini-2.5-pro$1.25 input per 1M tokens$10 output per 1M tokens$0.13 cache read per 1M tokensCache write not listed1.05M tokens of context - OpenRouter
google/gemini-2.5-pro$1.25 input per 1M tokens$10 output per 1M tokens$0.13 cache read per 1M tokens$0.38 cache write per 1M tokens1.05M tokens of context - Vercel AI Gateway
google/gemini-2.5-pro$1.25 input per 1M tokens$10 output per 1M tokens$0.13 cache read per 1M tokensCache write not listed1.05M 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, Audio, Video, PDF
- Output
- Text
- Knowledge cutoff
- Jan 2025
- Release date
- Jun 17, 2025
- Open weights
- No
- Reasoning
- Yes
- Tool calling
- Yes
Top public profiles
Public profiles that used Gemini 2.5 Pro most in this period, by tokens. Hidden accounts are never listed.
- 1
Jakub Pánik@jak-pan10.4Ktokens<$1est. cost13active days<$1 est. cost · 13 active days
More from Google
Other Google models in the same period, by active users.
- Gemini 3.8 Flash N14% adoption138active users
- Gemini 4 Argon8.6% adoption82active users
- Gemini 4 Argon Trial7.7% adoption74active users
- Gemini 3.8 Flash6.9% adoption66active users
- Gemini 3.8 Flash Tiered3.7% adoption35active users
- Gemini 4 Argon High1.8% adoption17active 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.