Artificial Intelligence5 min read

Gemini 4 Argon (High): Intelligence, Performance and Price Analysis

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In short

The model achieves an Artificial Analysis Intelligence Index score of 50, placing it ahead of the industry median of 42. It processes both text and image inputs across an expansive 1-million-token context window that can handle about 1,500 A4 pages. However, evaluation expenses average $7.68 per task due to high token pricing and a verbose output total of 110 million tokens. Latency remains another major hurdle, evidenced by a prolonged initial response delay through Google's API.

Key points

  • Superior intelligence index scores are offset by double the median costs for input and ou…: Superior intelligence index scores are offset by double the median costs for input and output tokens.
  • Initial latency reaches nearly 45 seconds, substantially lagging behind the typical 3.72-…: Initial latency reaches nearly 45 seconds, substantially lagging behind the typical 3.72-second standard.
  • Verbose generation tendencies drive evaluation costs higher by producing 110 million toke…: Verbose generation tendencies drive evaluation costs higher by producing 110 million tokens during testing.

Sources checked by our analysis pipeline: 1

Gemini 4 Argon (High) Intelligence, Performance & Price Analysis

Model summary

Gemini 4 Argon (High) is amongst the leading models in intelligence, but somewhat expensive when comparing to other models of similar price. It's also slower than average and somewhat verbose. The model supports text and image input, outputs text, and has a 1M tokens context window.

Gemini 4 Argon (High) scores 50 on the Artificial Analysis Intelligence Index, placing it well above average among comparable models (median: 42). When evaluating the Intelligence Index, it generated 110M tokens, which is somewhat verbose in comparison to the median of 64M.

Pricing for Gemini 4 Argon (High) is $4.00 per 1M input tokens (somewhat expensive, median: $2.00) and $20.00 per 1M output tokens (expensive, median: $10.00). On average, it costs $7.68 per task to evaluate Gemini 4 Argon (High) on the Intelligence Index.

At 82 tokens per second, Gemini 4 Argon (High) is slower than average (85).

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

Intelligence

Artificial Analysis Intelligence Index

Artificial Analysis Intelligence Index by Open Weights / Proprietary

Intelligence Index vs. Cost per Task

Measures the performance of models on specific capabilities and industries

Artificial Analysis Finance & Accounting Index

Evaluations

Agentic knowledge work, Elo

Knowledge

1 - hallucination rate

Agentic SaaS workflows

Agentic scientific research workflows in a terminal

Agentic software engineering in open-source repositories

Reasoning & knowledge

Professional document reasoning, All-pass

Agentic coding & terminal use

Physics reasoning

Quantitative analysis on spreadsheets & documents

Legal agentic work, Hallucination-Gated All-Pass Rate

Agentic business operations

Agentic real-world work tasks, Elo

Agentic interactive 3D experiences, Elo

Product and brand videos designed in code, Elo

Kubernetes incident root-cause analysis

Medical long context reasoning

Visual reasoning

Rich, varied, well-crafted language

Well-structured, scannable, answer-first

Truthful, acknowledges uncertainty, non-sycophantic

Use of filler and generic language

AA-Briefcase v1.1

AA-Briefcase Elo

AA-Omniscience v1.1

AA-Omniscience Index

AA-PersonalityBench

Personality Indexes

Intelligence Index Comparisons

Intelligence Index vs. Cost per Task

Token Use

Output Tokens per Intelligence Index Task

Cost

Cost per Intelligence Index Task

Cost to Run Artificial Analysis Intelligence Index

Pricing: Cache Hit, Input, and Output

Context Window

Context Window

Speed

Measured by Output Speed (tokens per second)

Output Speed

Time per Intelligence Index Task

Latency

Measured by Time (seconds) to First Token

Latency: Time To First Answer Token

End-to-End Response Time

Seconds to output 500 tokens, calculated based on time to first token, 'thinking' time for reasoning models, and output speed

End-to-End Response Time

Frequently Asked Questions

Common questions about Gemini 4 Argon (High)

Gemini 4 Argon (High) was released on September 30, 2026.

Gemini 4 Argon (High) was created by Google.

Gemini 4 Argon (High) scores 50 on the Artificial Analysis Intelligence Index, placing it well above average among other models in a similar price tier (median: 42).

Gemini 4 Argon (High) generates output at 82.4 tokens per second (based on Google's API), which is below average compared to other models in a similar price tier (median: 85.4 t/s).

Gemini 4 Argon (High) has a time to first token (TTFT) of 44.96s (based on Google's API), which is at the higher end compared to other models in a similar price tier (median: 3.72s).

Gemini 4 Argon (High) costs $4.00 per 1M input tokens (somewhat higher than average, median: $2.00) and $20.00 per 1M output tokens (at the higher end, median: $10.00), based on Google's API.

Gemini 4 Argon (High) costs $4.00 per 1M input tokens and $20.00 per 1M output tokens (based on Google's API). For a blended rate (7:2:1 cache hit/input/output ratio), this is $2.94 per 1M tokens. Pricing may vary by provider. Compare provider pricing

When evaluated on the Intelligence Index, Gemini 4 Argon (High) generated 110M output tokens, which is somewhat higher than average compared to other models in a similar price tier (median: 64M).

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.

Gemini 4 Argon (High) supports text and image input.

Gemini 4 Argon (High) supports text output.

Yes, Gemini 4 Argon (High) supports image input and can analyze, describe, and answer questions about images.

Yes, Gemini 4 Argon (High) is multimodal. It can process text and image input and generate text output.

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.

No, Gemini 4 Argon (High) is proprietary. The model weights are not publicly available.

Gemini 4 Argon (High) is a proprietary model and Google has not disclosed the model size or parameter count.

Gemini 4 Argon (High) achieves a score of 50 on the Artificial Analysis Intelligence Index. This composite benchmark evaluates models across reasoning, knowledge, mathematics, and coding.

Yes, Gemini 4 Argon (High) is available via API through 4 providers. Compare API providers

Gemini 4 Argon (High) is available through 4 API providers. Compare providers

Original source: artificialanalysis.ai

Artificial Intelligence