Gemini 4 Argon

Released
2026-09-30
Last refreshed
2026-10-17
Status
Researched 28d ago
ProprietaryCommercial use: restrictedMultimodalCodingRAGAgentsLong contextVisionJSON / Tool useCodingAgentMultimodalHighlight
Google DeepMind releases · 54 in the last 12 months · this family litChangelog →
Specifications
Family
Gemini 4
Released
2026-09-30
Context
1M
Max output
1M
Specialization
general
Openness
Proprietary
License
ProprietaryRestricted
Weights
Not released
Code
Unknown
Training
Pretrained
Created by

Pioneering artificial intelligence research.

London, United Kingdom
Founded 2014
Website
Pricing
Output / 1M
$10.00
Input / 1M
$2.00

Cheapest of 4 routes · Google AI Studio · cache read $0.100

About

Gemini 4 Argon is a Google DeepMind reasoning model, announced on September 30, 2026 for trusted cyber defenders and testers in Google's Fairwind Program and made generally available on October 13, 2026 through the Gemini API, Gemini Enterprise Agent Platform, Google Antigravity and the Gemini app. Google built it for long-horizon software engineering, legal and finance work, cybersecurity defense and science. It takes text, image, video, audio and PDF input and returns text. Input and output share a 1,048,576-token limit; one synchronous request returns up to 65,536 output tokens, and long decodes extend output up to 1,048,576 tokens.

Providers(4)

Compare all 4

Compare API pricing across 4 tracked provider routes for input and output tokens, batch, and cached reads when available.

ProviderInput / 1MOutput / 1MBatch in / outCacheRoute
Google AI Studio$2.00$10.00$1.00 / $5.00read $0.100
Serverless
GCP Vertex AI$2.00$10.00$1.00 / $5.00read $0.100
ServerlessProvisioned
OpenRouter$2.00$10.00$1.00 / $5.00read $0.100
Serverless
Vercel AI Gateway$2.00$10.00-read $0.100
Serverless

Available via routers & gateways(13)

LiteLLM

Gateway

Open-source Python SDK and proxy server that unifies 100+ LLM APIs behind a single OpenAI-compatible interface, with load balancing, cost tracking, and configurable failover.

Free OSSGoogle AI StudioGCP Vertex AI

OpenRouter

Hybrid

Unified hybrid gateway to 500+ models from 80+ providers via a single OpenAI-compatible API, with an optional Auto Router that selects a model per prompt from market spend data.

Passthrough + feeGoogle AI StudioGCP Vertex AI

Portkey

Gateway

Production AI gateway routing to 1,600+ LLMs with failover, load balancing, caching, and guardrails; MIT-licensed open-source core is self-hostable. Now part of Palo Alto Networks as Prisma AIRS AI Gateway.

SubscriptionGoogle AI StudioGCP Vertex AI

AIRouter

Router

Commercial LLM router (branded "AI Router" on its site) that picks the best model per request via a Decision API or an OpenAI-compatible Chat Completions endpoint, with a private selection mode that routes on anonymized patterns; sold as BYOK subscription plans priced by routed tokens.

SubscriptionGoogle AI StudioGCP Vertex AI

Helicone

Gateway

Observability-first AI gateway with routing, caching, rate limiting, and request tracing; Apache-2.0 open-source platform with a managed hosted tier for logging and analytics.

SubscriptionGoogle AI StudioGCP Vertex AI

Kong AI Gateway

Gateway

Multi-LLM AI gateway built on Kong Gateway 3.x, adding semantic routing, load balancing, guardrails, and MCP traffic analytics as plugins over Kong's existing API management platform.

SubscriptionGoogle AI StudioGCP Vertex AI

Capabilities

VisionMultimodalReasoningJSON / Tool useStructured OutputsCode ExecutionPrompt CachingBatch APIAudioVideo

Benchmark peer barsfor Coding

No task-mapped benchmark peers are available for this model yet.

Benchmark scores(11)

Scores are benchmark-specific and are direction-aware: the same numeric gap can mean very different outcomes across suites. Use the leaderboard context and this model's provider route to decide whether the winning margin is meaningful for your workload.
BenchmarkScoreVersionEvaluationSource
77.9DeepSWE v1.1Observed 2026-10-17
Configuration: Gemini 4 Argon (highest thinking)
Harness: mini-swe-agent
Evaluator: Google DeepMind
Confidence: self-reported
Notes: Blog benchmark table (gemini-4-argon_table_blog.gif); evals methodology page https://deepmind.google/models/evals-methodology/gemini-4-argon: self-computed with mini-swe-agent harness, highest thinking level. Retrieved 2026-10-17.
39.5Agents' Last Exam (binary pass rate)Observed 2026-10-17
Configuration: Gemini 4 Argon
Harness: ALE-Claw (default harness)
Evaluator: Google DeepMind
Confidence: self-reported
Notes: Blog table + methodology page: binary pass rate, ALE-Claw default harness, 5-hour window, safety filters on. Retrieved 2026-10-17.
69.2OSWorld 2.0 offline subset (partial score)Observed 2026-10-17
Configuration: Gemini 4 Argon; max of 3 runs
Harness: Gemini CUA harness; official OSWorld 2.0 evaluator
Evaluator: Google DeepMind
Confidence: self-reported
Notes: Blog table + methodology page: OSWorld 2.0 offline subset, partial score, max over 3 runs, Gemini CUA harness, official evaluator, 1080p, 500 steps, 08.08 patch. Comparability caveat: max-of-3 and offline subset differ from other OSWorld 2.0 rows. Retrieved 2026-10-17.
51.3AutomationBench private setObserved 2026-10-17
Configuration: Gemini 4 Argon; private split
Harness: Zapier official AutomationBench evaluation
Evaluator: Zapier
Confidence: confirmed
Notes: Blog table + methodology page: private set figure taken from Zapier's official AutomationBench leaderboard (Zapier-run). Note: most other catalog automation-bench rows are the public split; not directly comparable. Retrieved 2026-10-17.
96.4diamondObserved 2026-10-17
Configuration: gemini-4-argon (High)
Harness: Epoch AI Inspect harness (GPQA Diamond, 198 Q)
Evaluator: Epoch AI
Confidence: confirmed
Notes: Epoch AI-run evaluation (evaluator of record), from Epoch AI Benchmarking Hub data download https://epoch.ai/data/benchmark_data.zip (file gpqa_diamond.csv, row 'gemini-4-argon_high', run started 2026-10-13). Epoch data is CC BY 4.0: credit 'Epoch AI, Capabilities Benchmarking Hub'. Retrieved 2026-10-17.
78.0FrontierMath Tier 4 v2 (private)Observed 2026-10-17
Configuration: gemini-4-argon (High)
Harness: Epoch AI FrontierMath Tier 4 v2 private set
Evaluator: Epoch AI
Confidence: confirmed
Notes: Epoch AI-run evaluation (evaluator of record), from Epoch AI Benchmarking Hub data download https://epoch.ai/data/benchmark_data.zip (file frontiermath_tier_4.csv, row 'gemini-4-argon_high', run started 2026-10-13). Epoch data is CC BY 4.0: credit 'Epoch AI, Capabilities Benchmarking Hub'. Retrieved 2026-10-17.
91.3ARC-AGI-2 semi-privateObserved 2026-10-17
Configuration: gemini-4-argon (High)
Harness: ARC Prize semi-private evaluation
Evaluator: ARC Prize Foundation
Confidence: confirmed
Cost/task: $0.33
Notes: ARC Prize official leaderboard data (ARC-AGI-2 semi-private), verified in https://arcprize.org/media/data/leaderboard/v2.json (generatedAt 2026-10-15T13:43:29Z) for modelDisplayName 'Gemini 4 Argon (High)'; cost $0.325/task. Retrieved 2026-10-17.
65.4Finance Agent v2 (Vals benchmark_id finance_agent_v2, version 2)Observed 2026-10-17
Configuration: Vals AI default provider Google; temperature 1, max output 262,144, reasoning effort high
Harness: Vals AI Finance Agent harness (Valkyrie)
Evaluator: Vals AI
Confidence: third-party
Cost/task: $4.38
Notes: Vals AI leaderboard (https://www.vals.ai/benchmarks/fabv2), page 'Updated 10/16/2026', retrieved 2026-10-17. Vals model page https://www.vals.ai/models/google_gemini-4-argon shows the hyperparameters. Accuracy; ranked #1 on the page. The lab's restatement (https://blog.google/innovation-and-ai/models-and-research/gemini-models/gemini-4-argon/) reads 65.4; it matches after rounding and is not the source of this row.
19.6Harvey's Legal Agent Benchmark v1 (Vals benchmark_id legal_agent_benchmark)Observed 2026-10-17
Configuration: Vals AI default provider Google; temperature 1, max output 262,144, reasoning effort high
Harness: Harvey generation and grading protocol, run by Vals on Valkyrie, internet disabled
Evaluator: Vals AI
Confidence: third-party
Cost/task: $10.55
Notes: Vals AI leaderboard (https://www.vals.ai/benchmarks/hlab), page 'Updated 10/16/2026', retrieved 2026-10-17. Vals model page https://www.vals.ai/models/google_gemini-4-argon shows the hyperparameters. Metric is the task all-pass rate: a task passes only if 100% of its criteria pass, averaged over two LLM judges (GPT 5.5 medium reasoning, Claude Sonnet 4.6). Vals model page: ±3.31. The lab's restatement (https://blog.google/innovation-and-ai/models-and-research/gemini-models/gemini-4-argon/) reads 19.6; it matches after rounding and is not the source of this row.
1517.0text_style_control overall 2026-10-22 (style control, default view)Observed 2026-10-26
Configuration: Gemini 4 Argon (High)
Harness: LMArena blind pairwise human votes, Bradley-Terry
Evaluator: LMArena
Confidence: confirmed
Notes: LMArena text style control leaderboard, overall category, published 2026-10-22 (HF lmarena-ai/leaderboard-dataset @9761a3ce, latest split). Board entry 'Gemini 4 Argon (High)': rank 1, Arena Score 1517.2 (95% CI 1510.6-1523.8), 10083 votes. Retrieved 2026-10-26.
Source

Source: LMArena (lmarena.ai), CC BY 4.0

1523.0text creative_writing 2026-10-22Observed 2026-10-22
Configuration: Gemini 4 Argon (High)
Harness: LMArena blind pairwise human votes, Bradley-Terry
Evaluator: LMArena
Confidence: confirmed
Notes: LMArena Text arena, Creative Writing category (no style control), board published 2026-10-22 (HF lmarena-ai/leaderboard-dataset @a467e6b9, text config, latest split). Board entry 'Gemini 4 Argon (High)' (category creative_writing in text/latest-00000-of-00001.parquet): rank 2 of 416, rating 1523.1 (95% CI 1509.6-1536.5), 2335 votes. Source: LMArena (CC BY 4.0). Retrieved 2026-10-27.
Source

Source: LMArena (lmarena.ai), CC BY 4.0

Migration checks

No linked migration route is available for this model yet.