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ModelCap

Gemini 2.5 Pro

Arena #88No linked weights

Google·#102 of 504 in the all-versions archive

Gemini 2.5 Pro is a language model from Google. It ranks #102 of 504 in ModelCap's all-versions archive, with an Index score of 67.5, measured on 3 public benchmarks. Its score range of 62.8–72.2 spans positions #75–#125. It is listed at $1.25 per million input tokens and $10.00 per million output tokens from one provider. It reads up to 1M tokens of context, with no downloadable weights linked in the current source data.

Figures as of 6 Nov 2026, 13:52 UTC · download the public dataset · methodology

ModelCap Index · All-versions archive
67.5#102
Measured on 3 public benchmarks · range 62.8–72.2
Evidence as of 4 Nov 2026, 23:07 UTC
Market Gravity
41.6Increased by 0.1
Secondary market signal

Superseded by Gemini 3.1 Pro Preview. It no longer holds a current-board position; its all-versions archive rank is #102.

Input
$1.25
per 1M tokens
Output
$10.00
per 1M tokens
Context
1M
tokens
Providers
1
3 endpoints

Providers

Uptime measured over the last 30 minutes
ProviderInputOutputContextQuantUptime
Google AI StudioflexCheapest$0.625$5.001M—100.0%
Google AI Studio$1.25$10.001M—100.0%
Google AI Studiopriority$2.25$18.001M—100.0%

Other versions (3)

ModelCap Index · All-versions archive

Methodology
67.5
Measured on 3 public benchmarks
All-versions archive
#102 of 504
Score range
62.8–72.2
Rank range
#75–#125
Evidence as of
4 Nov 2026, 23:07 UTC
Benchmarks used
ARC-AGI-2 Verified, Arena Coding, Arena Overall
Technical details
Public rank basis
Measured (measured)
Evidence label
Measured · 3 public benchmark observations across 3 boards
Index support
65.7% · strong
Identity binding
Exact catalogue product · google/google/gemini-2.5-pro · aggregates disclosed benchmark configurations · endpoint configuration not claimed
Index observations used
3
Qualified Index evidence point
67.5
Bayesian Evidence Score · measured evidence input only

BES normalizes admitted public benchmark evidence for measured Index rows. Its legacy score and observables prior do not define the public language rank.

Observed capability
67.5
Evidence status
confirmed · 87% mass
General preference
69.7
Coding
57.4
Agents & tools
—
Reasoning
16.7
Evidence breadth
95%
Evidence coverage
66%
Market and catalogue signals · secondary, never the language Index rank
Usage (OpenRouter popularity)
17.1
Liquidity (providers × uptime)
95.8
Open reach (HF downloads)
—
Surface (context / tools / modalities)
100.0
Freshness
14.5
  • · OpenRouter popularity #125
  • · 1 live provider
  • · Catalogue: context 1048576, reasoning, tools, modalities Text/Image/File/Audio/Video
  • · First seen 2025-06-17

These adoption and deployment observations remain context only. They do not change this model's ModelCap Index score or rank.

BES evidence selected · measured input only

The bounded 0–100 capability score blends each source’s competitive placement with its published achievement, then combines capability families. Evidence breadth adds a modest uncertainty adjustment; price and popularity are not part of benchmark-led rank.

Deployment readiness

Metadata index
45.5
partial · 56% metadata coverage
Not capability
Artifact reproducibility
0.0
Access & legal clarity
30.3
Deployability
80.0
Evaluation provenance
77.1

Not yet published: a pinned repository revision, the architecture and model type, a parameter count, safetensors weight metadata, the base model it derives from, a declared licence, a link to the licence terms, pinned evaluation dataset versions.

A metadata completeness and deployability index—not a safety certification, quality grade, or production-readiness claim.

Market activity

Venue coverage
Market Gravity
41.6
OpenRouter weekly popularity
#125 of 339

Market Gravity uses OpenRouter’s full-catalogue popularity order. Sparse Vercel top-ten observations appear only when published and do not affect the score.

Arena preference

Status
Ranked
Source
LMArena
Official rank
#88 of 419
Rating
1445.4
95% confidence interval
1443–1448
Votes
125K
Source published at
28 Oct 2026, 00:00 UTC
Category
overall
Identity match confidence
100%

Market Gravity breakdown

Usage55%
17.1

OpenRouter weekly popularity across the full model catalogue.

Liquidity25%
95.8

Independent providers versus the model's open or closed cohort, weighted by uptime.

Open reach15%
50.0

Hugging Face 30-day downloads for open models; neutral for closed models.

Freshness5%
14.5

Time since first public availability, on a six-month half-life.

Specification

Model ID
google/gemini-2.5-pro
Context window
1M tokens
Declared output cap
66K tokens

OpenRouter catalogue or provider-endpoint declaration. Limits can vary by provider and prompt length; a model-wide maximum has not been independently verified. OpenRouter metadata

Inputs
Text, Image, File, Audio, Video
Outputs
Text
Tokenizer
Gemini
Cached input tokens
$0.125 / 1M
First seen on OpenRouter
17 Jun 2025
Knowledge cutoff
2025-01-31

Capabilities

  • Supported: Reasoning
  • Supported: Tool use
  • Supported: Structured output
  • Supported: Response format
  • Not supported: Moderated

Benchmark leaderboards featuring Gemini 2.5 Pro

All leaderboards
Public benchmark boards on which Gemini 2.5 Pro has a published result
LeaderboardScoreSource rankConfigurationPublished
Arena text leaderboardArena (LMArena)14451443–1448#88 of 419Not reported28 Oct 2026
Arena coding leaderboardArena (LMArena)14641460–1468#135 of 414Default28 Oct 2026
ARC-AGI-2 leaderboardARC Prize Foundation4.9%#186 of 280Thinking4 Nov 2026
SWE-bench leaderboardSWE-bench (Princeton / SWE-agent team)53.6%#34 of 47Default26 Jul 2025

Gemini 2.5 Pro: common questions

How does Gemini 2.5 Pro rank among AI models?

Gemini 2.5 Pro is a superseded version and is not on the current board as of 6 November 2026. Its archive position, where one exists, is shown on the page; the newer version carries the current rank.

How much does Gemini 2.5 Pro cost per 1M tokens?

Gemini 2.5 Pro is listed at $1.25 per 1M input tokens and $10.00 per 1M output tokens as of 6 November 2026. Prices come from the OpenRouter catalogue and re-observe on every refresh. For 1,000 requests using 2,000 input and 500 output tokens each, the listed rates imply $7.50 total (2M input + 0.5M output). This excludes caching, batch discounts, prompt-length tiers, tool charges and retries; verify the chosen endpoint's rate and limits before budgeting.

What is the context window of Gemini 2.5 Pro?

Gemini 2.5 Pro has a published context window of 1M tokens (1,048,576). The snapshot lists a 65,536 token catalogue-declared route output cap. OpenRouter catalogue or provider-endpoint declaration. Limits can vary by provider and prompt length; a model-wide maximum has not been independently verified. The providers table lists each endpoint's context limit.

Is Gemini 2.5 Pro open-weight?

No linked weights. No downloadable model weights are linked in the current source data. This does not identify every API or chat product that offers the model.

Which API providers serve Gemini 2.5 Pro?

One provider serves Gemini 2.5 Pro through OpenRouter as of 6 November 2026: Google AI Studio. Each provider's price, context limit, quantization and measured uptime are in the providers table above.

Which benchmarks has Gemini 2.5 Pro been evaluated on?

Gemini 2.5 Pro has published results on 4 public boards tracked by ModelCap as of 6 November 2026: Arena text 1445 (#88 of 419), Arena coding 1464 (#135 of 414), ARC-AGI-2 4.9% (#186 of 280) and SWE-bench 53.6% (#34 of 47). Each board page ranks every tracked model on that benchmark. The ModelCap Index scores the results its methodology admits, with published uncertainty, and shows reference boards without scoring them.

When was Gemini 2.5 Pro released?

Gemini 2.5 Pro first appeared in the catalogue on 17 Jun 2025, with a published knowledge cutoff of 2025-01-31. It has since been superseded by Gemini 3.1 Pro Preview. Rank and price movements since then are recorded on the site's changes feed.