Google

Gemini 4 Argonpreview

Google deep reasoning frontier research model featuring native multimodal chain-of-thought, sub-second video analysis, and 2M token active context.

#6released Oct 5, 2026·Proprietary·Not disclosed
textimageaudiovideo2M ctxreasoning
Intelligence
93.6 #6
AAQI 94.0
Output Speed
88 t/s
ITL 11.4 ms/tok
Blended price (3:1)
$5 /1M
In $2.5/M · Out $10/M
Context
2M
≈ 5,000 A4 pages · max out 65,536

Quality Domain Radar

6-Axis Frontier Evaluation vs Category Average & Flagship

Gemini 4 Argon
Claude Mythos Preview (#1)
Average (68)
Coding (88)Mathematics (93.5)Hard Science (GPQA) (94.2)Agentic & Tool Use (87)Knowledge (MMLU) (91)Vision / Multimodal (97.5)

Radar axes are approximated from category scores where direct benchmark measurements are missing — see Methodology.

Strengths & Trade-offs

Where it wins

  • Largest context window in production — 2M tokens
  • All four modalities native in a single architecture
  • Frontier coding, financial research and legal drafting
  • Purpose-built for autonomous vulnerability research

Trade-offs to watch

  • Staged rollout — full API access still ramping
  • Deep Think adds latency and token spend
  • Proprietary; no open weights

Killer Use Cases

Cyber defense triage
Autonomous vuln discovery and remediation — the Fairwind program's headline workload.
2M-token corpus analysis
Entire legal archives, monorepos or video libraries in one context.
Multimodal research
Cross-referencing text, audio calls and video feeds natively.

Developer Quickstart & API

Set GEMINI_API_KEY first — get an API key
curl "https://generativelanguage.googleapis.com/v1beta/models/gemini-4-argon:generateContent" \
  -H "x-goog-api-key: $GEMINI_API_KEY" \
  -H "content-type: application/json" \
  -d '{
    "contents": [{"parts": [{"text": "Refactor this function for O(n) time and explain the change."}]}]
  }'

Official Resources & Links

API deployment

Compare hosts & latency

Throughput, TTFT and cache pricing across Groq, Cerebras, Together, DeepInfra, Fireworks, Bedrock and Azure.

GroqCerebrasTogether AIDeepInfraFireworks AIAWS BedrockAzure AI
View providers matrix →

Scores by Source

Head-to-head Live Matchups

Live Specs & Architecture

Under the hood
Gemini 4 Argon — native multimodal transformer
  • Native multimodal chain-of-thought — reasons over text, image, audio and video in one pass
  • 2M-token context — the largest production window tracked
  • Deep Think mode trades latency for accuracy on hard problems
  • First Gemini 4-generation model; rolled out to trusted cyber defenders via the Fairwind program before GA
Release date
Oct 5, 2026
Architecture
Gemini 4 Argon — native multimodal transformer
Parameters
Not disclosed
License
Proprietary
Context Window
2,000,000 tokens
Max Output
65,536 tokens
Modalities
text + image + audio + video
Cache Pricing
read $0.25 · write $2.5 /1M
Reasoning
Effort levels
Input Price
$2.5/M
Output Price
$10/M
Output Speed
88 t/s
Time to First Token
—
Data Updated
Oct 10, 2026

Estimated monthly bill

Estimated monthly spend
$0.00
Calculating savings vs GPT-4o...

Cite & embed

GitHub Markdown badge
Loading badge markdown...
BibTeX
@misc{llmpodium2026gemini4argon,
  title = {Benchmark Analysis and Intelligence Evaluation of Gemini 4 Argon},
  author = {LLMPodium Research},
  year = {2026},
  url = {https://llmpodium.com/models/gemini-4-argon}
}

Embed Score Badge

Add a live Podium Score badge to your GitHub or Hugging Face README — it links back to the live ranking.

Preview
Gemini 4 Argon LLMPodium Score
Markdown
Loading badge snippet...
HTML
Loading badge snippet...

More from Google

Alternative Models

Closest alternatives to Gemini 4 Argon based on capabilities, pricing, and benchmark scores.

0 / 4