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Proprietary model

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Released November 2026

Agnes 2.5 Pro Theta Intelligence, Performance & Price Analysis

Name: Intelligence
Creator: Artificial Analysis
License: https://artificialanalysis.ai/docs/legal/Terms-of-Use.pdf

Try it out API Provider Benchmarks

Performance

N/A

Time per Intelligence Index task (minutes)

Cost

In $0.45Out $0.90Cache discount 90%

$2.46

Cost per Intelligence Index task

Verbosity

Input tokens 8.63BOutput/input 2.98%

257M

Output tokens from Intelligence Index

Agnes 2.5 Pro Theta is above average in intelligence, but somewhat expensive when comparing to other models of similar price. The model supports text and image input, outputs text, and has a 1M tokens context window.

Agnes 2.5 Pro Theta scores 24 on the Artificial Analysis Intelligence Index, placing it above average among comparable models (median: 24). When evaluating the Intelligence Index, it generated 257M tokens, which is very verbose in comparison to the median of 97M.

Pricing for Agnes 2.5 Pro Theta is $0.45 per 1M input tokens (expensive, median: $0.24) and $0.90 per 1M output tokens (somewhat expensive, median: $0.88). On average, it costs $2.46 per task to evaluate Agnes 2.5 Pro Theta on the Intelligence Index.

Reasoning	Yes This page shows the reasoning version of this model. A non-reasoning variant may also exist.
Input modality	Supports: text and image
Output modality	Supports: text
Context window	1M ~1500 A4 pages of size 12 Arial font

Metrics are compared against models of the same class:

Non-reasoning models → compared only with other non-reasoning models
Reasoning models → compared across both reasoning and non-reasoning
Open weights models → compared only with other open weights models of the same size class:

Tiny: ≤4B parameters
Small: 4B–40B parameters
Medium: 40B–150B parameters
Large: >150B parameters

Proprietary models → compared across proprietary and open weights models of the same price range, using a blended 3:1 input/output price ratio:

<$0.15 per 1M tokens
$0.15–$1 per 1M tokens
>$1 per 1M tokens

Updated

Intelligence

Artificial Analysis Intelligence Index · Higher is better

No publicly available API

Time per Task

Inference time (minutes) per Intelligence Index task · Lower is better

No publicly available API

Cost per Task

Weighted average cost (USD) per Intelligence Index task · Lower is better

No publicly available API

IntelligenceUpdated

Artificial Analysis Intelligence Index

Artificial Analysis Intelligence Index v5.0.1 incorporates 9 evaluations: AA-Briefcase v1.1, AutomationBench-AA, Terminal-Bench 4.0, FrontierCode 2.0, AA-Omniscience v1.1, GDP.pdf, HLE-Diamond, CritPt v2 (Hard Subset), and Terminal-Bench-Science 0.1

No publicly available API

Artificial Analysis Intelligence Index v5.0.1 includes: AA-Briefcase v1.1, AutomationBench-AA, Terminal-Bench 4.0, FrontierCode 2.0, AA-Omniscience v1.1, GDP.pdf, HLE-Diamond, CritPt v2 (Hard Subset), Terminal-Bench-Science 0.1. See Intelligence Index methodology for further details, including a breakdown of each evaluation and how we run them.

Artificial Analysis Intelligence Index by Open Weights / Proprietary

No publicly available API

Indicates whether the model weights are available. Models are labelled as 'Commercial Use Restricted' if commercial use is limited by conditions, and as 'Non-commercial' if the license prohibits commercial use.

Intelligence Index vs. Cost per Task

Artificial Analysis Intelligence Index · Weighted average cost (USD) per Artificial Analysis Intelligence Index task

Most attractive quadrant

Pareto line

Weighted average cost per Intelligence Index task. Each evaluation’s cost is calculated from input, cache hit, cache write, reasoning, and answer token prices, divided by task count, and weighted by its Intelligence Index weight.

Capability Indexes

Measures the performance of models on specific capabilities and industries

Artificial Analysis Finance & Accounting Index

Incorporates 5 evaluations: AA-Briefcase v1.1, AA-Omniscience v1.1, HLE-Diamond, AutomationBench-AA, GDP.pdf · Higher is better

No publicly available API

Benchmarks

Evaluations

Evaluations measured independently by Artificial Analysis · AA-PersonalityBench scores are percentile ranks from 1 to 100

No publicly available API

AA-Briefcase v1.1

Agentic knowledge work, Elo

AA-Omniscience v1.1 AccuracyUpdated

Knowledge

AA-Omniscience v1.1 Non-Hallucination RateUpdated

1 - hallucination rate

AutomationBench-AA

Agentic SaaS workflows

Terminal-Bench-Science 0.1New

Agentic scientific research workflows in a terminal

FrontierCode 2.0New

Agentic software engineering in open-source repositories

HLE-DiamondNew

Reasoning & knowledge

GDP.pdf

Professional document reasoning, All-pass

Terminal-Bench 4.0

Agentic coding & terminal use

CritPt v2 (Hard Subset)

Physics reasoning

AA-AnalystAgent

Quantitative analysis on spreadsheets & documents

Harvey LAB-AA v1.1Updated

Legal agentic work, Hallucination-Gated All-Pass Rate

EnterpriseOps-Gym-AA

Agentic business operations

GDPval-AA v2.1

Agentic real-world work tasks, Elo

AA-3DNew

Agentic interactive 3D experiences, Elo

Code2Video-AANew

Product and brand videos designed in code, Elo

ITBench-AA

Kubernetes incident root-cause analysis

MLCR-AAUpdated

Medical long context reasoning

MMMU-Pro

Visual reasoning

AA-PersonalityBench: Expressiveness ScoreNew

Rich, varied, well-crafted language

AA-PersonalityBench: Organization ScoreNew

Well-structured, scannable, answer-first

AA-PersonalityBench: Transparency ScoreNew

Truthful, acknowledges uncertainty, non-sycophantic

AA-PersonalityBench: Slop ScoreNew

Use of filler and generic language

While model intelligence generally translates across use cases, specific evaluations may be more relevant for certain use cases.

AA-Briefcase v1.1

AA-Briefcase Elo

AA-Briefcase v1.1 is an agentic knowledge work benchmark developed by Artificial Analysis. AA-Briefcase Elo is a combined metric that aggregates rubric pass rate, analytical quality Elo and presentation Elo · Higher is better

No publicly available API

AA-Briefcase Elo is a combined metric that aggregates analytical quality Elo, presentation Elo, and rubric pass rate, with rubric performance converted into Elo via synthetic head-to-head matches. Elo and 95% confidence interval bounds are clamped at 0.

AA-Omniscience v1.1

AA-Omniscience Net Score

AA-Omniscience v1.1 Net Score (higher is better) measures knowledge reliability and hallucination. It rewards correct answers, penalizes hallucinations, and has no penalty for refusing to answer. Scores range from -100 to 100, where 0 means as many correct as incorrect answers, and negative scores mean more incorrect than correct.

No publicly available API

Token Use

Output Tokens per Intelligence Index Task

Weighted average number of output tokens used to run one task in the Artificial Analysis Intelligence Index

No publicly available API

The number of tokens required per Intelligence Index task. This is calculated by multiplying the output tokens per eval by the relative weights of each benchmark in the Intelligence Index, then dividing by task count (excluding repeats).

Cost

Cost per Intelligence Index Task

Weighted average cost (USD) per Intelligence Index task · Segmented by token type · Lower is better

No publicly available API

Cost to Run Artificial Analysis Intelligence Index

Cost (USD) to run all evaluations in the Artificial Analysis Intelligence Index

No publicly available API

The cost to run the evaluations in the Artificial Analysis Intelligence Index, calculated using the model's input, cache hit, cache write, reasoning, and answer token prices and the number of tokens used across evaluations (excluding repeats).

Pricing: Cache Hit, Input, and Output

Price (USD per M Tokens)

No publicly available API

Price per token for cached prompts (previously processed), typically offering a significant discount compared to regular input price, represented as USD per million tokens. The values shown here are the cache hit price; cache write and cache storage are billed separately and vary by provider — see "Cache pricing by provider" for detail.

Context Window

Context window: tokens limit · Higher is better

No publicly available API

Larger context windows are relevant to RAG (Retrieval Augmented Generation) LLM workflows which typically involve reasoning and information retrieval of large amounts of data.

Maximum number of combined input & output tokens. Output tokens commonly have a significantly lower limit (varied by model).

Frequently Asked Questions

Common questions about Agnes 2.5 Pro Theta

Agnes 2.5 Pro Theta was released on November 7, 2026.

Agnes 2.5 Pro Theta was created by Sapiens AI.

Agnes 2.5 Pro Theta scores 24 on the Artificial Analysis Intelligence Index, placing it above average among other models in a similar price tier (median: 24).

Agnes 2.5 Pro Theta costs $0.45 per 1M input tokens (at the higher end, median: $0.24) and $0.90 per 1M output tokens (somewhat higher than average, median: $0.88), based on the median across providers serving the model.

Agnes 2.5 Pro Theta costs $0.45 per 1M input tokens and $0.90 per 1M output tokens (based on the median across providers serving the model). For a blended rate (7:2:1 cache hit/input/output ratio), this is $0.21 per 1M tokens. Pricing may vary by provider. Compare provider pricing

When evaluated on the Intelligence Index, Agnes 2.5 Pro Theta generated 257M output tokens, which is at the higher end compared to other models in a similar price tier (median: 97M).

Yes, Agnes 2.5 Pro Theta is a reasoning model. It uses extended thinking or chain-of-thought reasoning to work through complex problems before providing an answer.

Agnes 2.5 Pro Theta supports text and image input.

Agnes 2.5 Pro Theta supports text output.

Yes, Agnes 2.5 Pro Theta supports image input and can analyze, describe, and answer questions about images.

Yes, Agnes 2.5 Pro Theta is multimodal. It can process text and image input and generate text output.

Agnes 2.5 Pro Theta has a context window of 1M tokens. This determines how much text and conversation history the model can process in a single request.

No, Agnes 2.5 Pro Theta is proprietary. The model weights are not publicly available.

Agnes 2.5 Pro Theta is a proprietary model and Sapiens AI has not disclosed the model size or parameter count.

Agnes 2.5 Pro Theta achieves a score of 24 on the Artificial Analysis Intelligence Index. This composite benchmark evaluates models across knowledge work, coding, science, and general knowledge.

Yes, Agnes 2.5 Pro Theta is available via API through 1 provider. Compare API providers

Agnes 2.5 Pro Theta is available through 1 API provider. Compare providers

Agnes 2.5 Pro Theta Intelligence, Performance & Price Analysis

Model summary

IntelligenceUpdated

Performance

Comparison Summary

Technical specifications

168 models in this class

Time per Task

IntelligenceUpdated

Artificial Analysis Intelligence Index

Artificial Analysis Intelligence Index by Open Weights / Proprietary

Artificial Analysis Intelligence Index

Open Weights

Intelligence Index vs. Cost per Task

Cost per Intelligence Index Task

Artificial Analysis Intelligence Index

Evaluations

Intelligence Evaluation Relevance

Artificial Analysis Intelligence Index

AA-Briefcase v1.1

AA-Briefcase Elo

AA-Briefcase Elo

AA-Omniscience v1.1

AA-Omniscience Net Score

AA-Omniscience Net Score

Token Use

Output Tokens per Intelligence Index Task

Output Tokens per Intelligence Index Task

Cost

Cost per Intelligence Index Task

Cost per Intelligence Index Task

Cost to Run Artificial Analysis Intelligence Index

Cost to Run Artificial Analysis Intelligence Index

Pricing: Cache Hit, Input, and Output

Cache Hit

Context Window

Context Window

Context Window for RAG

Context Window

Frequently Asked Questions

When was Agnes 2.5 Pro Theta released?

Who created Agnes 2.5 Pro Theta?

How intelligent is Agnes 2.5 Pro Theta?

How much does Agnes 2.5 Pro Theta cost?

What is Agnes 2.5 Pro Theta API pricing?

How verbose is Agnes 2.5 Pro Theta?

Is Agnes 2.5 Pro Theta a reasoning model?

What input modalities does Agnes 2.5 Pro Theta support?

What output modalities does Agnes 2.5 Pro Theta support?

Can Agnes 2.5 Pro Theta process images?

Is Agnes 2.5 Pro Theta multimodal?

What is the context window of Agnes 2.5 Pro Theta?

Is Agnes 2.5 Pro Theta open source?

How many parameters does Agnes 2.5 Pro Theta have?

How does Agnes 2.5 Pro Theta perform on benchmarks?

Is Agnes 2.5 Pro Theta available via API?

Where can I use Agnes 2.5 Pro Theta?