Gemini 4 Argon (High) Intelligence, Performance & Price Analysis
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Proprietary model
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Released September 2026
Gemini 4 Argon (High) Intelligence, Performance & Price Analysis
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Model summary
#### IntelligenceUpdated
#8 / 223
53
Artificial Analysis Intelligence Index
4 out of 4 units for Intelligence.
#### Speed
N/A
Output tokens per second
Unknown out of 4 units for Speed.
#### Cost
#77 / 223
In $2.00Out $10.00Cache Discount 95%
$1.99
Cost per Intelligence Index task
3 out of 4 units for Cost.
#### Verbosity
#74 / 223
110M
Output tokens from Intelligence Index
3 out of 4 units for Verbosity.
Comparison Summary
Gemini 4 Argon (High) is amongst the leading models in intelligence and reasonably priced when comparing to other models of similar price. The model supports text and image input, outputs text, and has a 1M tokens context window.
Gemini 4 Argon (High) scores 53 on the Artificial Analysis Intelligence Index, placing it well above average among comparable models (median: 26). When evaluating the Intelligence Index, it generated 110M tokens, which is somewhat verbose in comparison to the median of 82M.
Pricing for Gemini 4 Argon (High) is $2.00 per 1M input tokens (moderately priced, median: $2.00) and $10.00 per 1M output tokens (moderately priced, median: $10.00). On average, it costs $1.99 per task to evaluate Gemini 4 Argon (High) on the Intelligence Index.
Technical specifications
| Reasoning | YesThis 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 |
223 models in this class
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:
Highlights
Updated
Intelligence
Artificial Analysis Intelligence Index · Higher is better
Not publicly available
Speed
Output tokens per second · Higher is better
Cost per Task
Weighted average cost (USD) per Intelligence Index task · Lower is better
Not publicly available
Prompt Options
IntelligenceUpdated
Artificial Analysis Intelligence Index
Artificial Analysis Intelligence Index v4.3.2 incorporates 10 evaluations: AA-Briefcase v1.1, GDPval-AA v2.1, AutomationBench-AA, Terminal-Bench 4.0, SciCode, Humanity's Last Exam, GDP.pdf, CritPt, AA-Omniscience, AA-LCR v1.1
25 of 687 models
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Not publicly available
###
Artificial Analysis Intelligence Index
Artificial Analysis Intelligence Index v4.3.2 includes: AA-Briefcase v1.1, GDPval-AA v2.1, AutomationBench-AA, Terminal-Bench 4.0, SciCode, Humanity's Last Exam, GDP.pdf, CritPt, AA-Omniscience, AA-LCR v1.1. See Intelligence Index methodology for further details, including a breakdown of each evaluation and how we run them.
Open Weights / ProprietaryReasoning / Non-ReasoningText Only / Multimodal Inputs
Artificial Analysis Intelligence Index by Open Weights / Proprietary
Artificial Analysis Intelligence Index v4.3.2 incorporates 10 evaluations: AA-Briefcase v1.1, GDPval-AA v2.1, AutomationBench-AA, Terminal-Bench 4.0, SciCode, Humanity's Last Exam, GDP.pdf, CritPt, AA-Omniscience, AA-LCR v1.1
25 of 687 models
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Not publicly available
ProprietaryOpen WeightsOpen Weights (Commercial Use Restricted)
###
Artificial Analysis Intelligence Index
Artificial Analysis Intelligence Index v4.3.2 includes: AA-Briefcase v1.1, GDPval-AA v2.1, AutomationBench-AA, Terminal-Bench 4.0, SciCode, Humanity's Last Exam, GDP.pdf, CritPt, AA-Omniscience, AA-LCR v1.1. See Intelligence Index methodology for further details, including a breakdown of each evaluation and how we run them.
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Open Weights
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.
Capability Indexes
Measures the performance of models on specific capabilities and industries
Finance & AccountingStrategy & OpsLegalEngineeringEconomics
Artificial Analysis Finance & Accounting Index
Incorporates 7 evaluations: AA-Omniscience, GDPval-AA v2.1, AA-Briefcase v1.1, Humanity's Last Exam, AutomationBench-AA, AA-LCR v1.1, GDP.pdf · Higher is better
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Not publicly available
Benchmarks
Intelligence Evaluations
Intelligence evaluations measured independently by Artificial Analysis · Higher is better
CodingAgenticTool UsePrivate DatasetUser InteractionFinanceMedicalLegalIntelligence IndexLong ContextMultimodalInstruction FollowingFaithfulnessWritingBusinessSee more
18 of 27 evaluations
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AA-Briefcase v1.1Updated
Agentic knowledge work, (Elo-500)/2000
GDPval-AA v2.1Updated
Agentic real-world work tasks, (Elo-500)/2000
AutomationBench-AAUpdated
Agentic SaaS workflows
Agentic coding & terminal use
SciCodeUnder review
Coding
Reasoning & knowledge
GDP.pdfNew
Professional document reasoning, All-pass
CritPtUnder review
Physics reasoning
Knowledge
AA-Omniscience Non-Hallucination Rate
1 - hallucination rate
Long context reasoning
Legal agentic work, criterion pass rate
Agentic business operations
Agentic scientific research workflows in a terminal
Quantitative analysis on spreadsheets & documents
Kubernetes incident root-cause analysis
Visual reasoning
Medical long context reasoning
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Intelligence Evaluation Relevance
While model intelligence generally translates across use cases, specific evaluations may be more relevant for certain use cases.
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Artificial Analysis Intelligence Index
Artificial Analysis Intelligence Index v4.3.2 includes: AA-Briefcase v1.1, GDPval-AA v2.1, AutomationBench-AA, Terminal-Bench 4.0, SciCode, Humanity's Last Exam, GDP.pdf, CritPt, AA-Omniscience, AA-LCR v1.1. See Intelligence Index methodology for further details, including a breakdown of each evaluation and how we run them.
AA-Briefcase v1.1Updated
AA-Briefcase EloAA-Briefcase Rubric Score (%)Analytical Quality & Presentation Elo
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
25 of 211 models
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###
AA-Briefcase Elo
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
AA-Omniscience IndexAA-Omniscience AccuracyAA-Omniscience Hallucination Rate
AA-Omniscience Index
AA-Omniscience Index (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.
25 of 562 models
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###
AA-Omniscience Index
AA-Omniscience Index (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.
Intelligence Index Comparisons
Intelligence Index vs. Cost per TaskIntelligence Index vs. Time per TaskIntelligence Index vs. Output SpeedIntelligence Index vs. End-to-End Response Time
Intelligence Index vs. Cost per Intelligence Index Task
Artificial Analysis Intelligence Index · Weighted average cost (USD) per Artificial Analysis Intelligence Index task
25 of 687 models
Most attractive quadrant
Pareto line
GoogleXiaomiOpenAIAnthropicSpaceXAIMetaZ AIDeepSeek
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Cost per Intelligence Index Task
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.
###
Artificial Analysis Intelligence Index
Artificial Analysis Intelligence Index v4.3.2 includes: AA-Briefcase v1.1, GDPval-AA v2.1, AutomationBench-AA, Terminal-Bench 4.0, SciCode, Humanity's Last Exam, GDP.pdf, CritPt, AA-Omniscience, AA-LCR v1.1. See Intelligence Index methodology for further details, including a breakdown of each evaluation and how we run them.
Token Use
Output Tokens per TaskIntelligence Index vs. Output Tokens per TaskIntelligence Index Token UseIntelligence Index vs. 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
25 of 687 models
Not publicly available
AnswerReasoning
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Output Tokens per Intelligence Index Task
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 TaskIntelligence Index vs. Cost per TaskEvaluation Breakdown
Cost per Intelligence Index Task
Weighted average cost (USD) per Artificial Analysis Intelligence Index task, segmented by token type. Lower is better
25 of 687 models
Not publicly available
AnswerReasoningCache WriteCache HitInput
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Cost per Intelligence Index Task
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.
Intelligence Index Total CostIntelligence Index vs. Total Cost
Cost to Run Artificial Analysis Intelligence Index
Cost (USD) to run all evaluations in the Artificial Analysis Intelligence Index
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OutputReasoningCache WriteCache ReadNon-Cache Input
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Cost to Run Artificial Analysis Intelligence Index
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).
Cache Hit, Input, and Output PricingBlended PriceBlended Price (Stacked)Cache DiscountIntelligence Index vs. PriceIntelligence Index vs. Price (Log, Inverted)Image Input Pricing
Pricing: Cache Hit, Input, and Output
Price (USD per M Tokens)
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Cache HitInputOutput
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Cache Hit
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.
4 more notes
Context Window
Context WindowIntelligence Index vs. Context Window
Context Window
Context window: tokens limit · Higher is better
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Not publicly available
###
Context Window for RAG
Larger context windows are relevant to RAG (Retrieval Augmented Generation) LLM workflows which typically involve reasoning and information retrieval of large amounts of data.
###
Context Window
Maximum number of combined input & output tokens. Output tokens commonly have a significantly lower limit (varied by model).
Frequently Asked Questions
Common questions about Gemini 4 Argon (High)
When was Gemini 4 Argon (High) released?
Gemini 4 Argon (High) was released on September 30, 2026.
Who created Gemini 4 Argon (High)?
Gemini 4 Argon (High) was created by Google.
How intelligent is Gemini 4 Argon (High)?
Gemini 4 Argon (High) scores 53 on the Artificial Analysis Intelligence Index, placing it well above average among other reasoning models in a similar price tier (median: 26).
How much does Gemini 4 Argon (High) cost?
Gemini 4 Argon (High) costs $2.00 per 1M input tokens (better than average, median: $2.00) and $10.00 per 1M output tokens (better than average, median: $10.00), based on Google's API.
What is Gemini 4 Argon (High) API pricing?
Gemini 4 Argon (High) costs $2.00 per 1M input tokens and $10.00 per 1M output tokens (based on Google's API). For a blended rate (7:2:1 cache hit/input/output ratio), this is $1.47 per 1M tokens. Pricing may vary by provider. Compare provider pricing
How verbose is Gemini 4 Argon (High)?
When evaluated on the Intelligence Index, Gemini 4 Argon (High) generated 110M output tokens, which is somewhat higher than average compared to other reasoning models in a similar price tier (median: 82M).
Is Gemini 4 Argon (High) a reasoning model?
Yes, Gemini 4 Argon (High) is a reasoning model. It uses extended thinking or chain-of-thought reasoning to work through complex problems before providing an answer.
What input modalities does Gemini 4 Argon (High) support?
Gemini 4 Argon (High) supports text and image input.
What output modalities does Gemini 4 Argon (High) support?
Gemini 4 Argon (High) supports text output.
Can Gemini 4 Argon (High) process images?
Yes, Gemini 4 Argon (High) supports image input and can analyze, describe, and answer questions about images.
Is Gemini 4 Argon (High) multimodal?
Yes, Gemini 4 Argon (High) is multimodal. It can process text and image input and generate text output.
What is the context window of Gemini 4 Argon (High)?
Gemini 4 Argon (High) has a context window of 1.0M tokens. This determines how much text and conversation history the model can process in a single request.
Is Gemini 4 Argon (High) open source?
No, Gemini 4 Argon (High) is proprietary. The model weights are not publicly available.
How many parameters does Gemini 4 Argon (High) have?
Gemini 4 Argon (High) is a proprietary model and Google has not disclosed the model size or parameter count.
How does Gemini 4 Argon (High) perform on benchmarks?
Gemini 4 Argon (High) achieves a score of 53 on the Artificial Analysis Intelligence Index. This composite benchmark evaluates models across reasoning, knowledge, mathematics, and coding.
Is Gemini 4 Argon (High) available via API?
Yes, Gemini 4 Argon (High) is available via API through 1 provider. Compare API providers
Where can I use Gemini 4 Argon (High)?
Gemini 4 Argon (High) is available through 1 API provider. Compare providers