Google · Model release
Data as of September 30, 2026 · How the score is built
Released Sep 30, 2026Google Gemini 4 Argon evaluation methodology
Gemini 4 Argon
Decision readingGemini 4 Argon scores 64.6 out of 100 and ranks #32 of 211. This profile shows 17 source-displayable benchmark rows; its strongest eligible category is Coding at #8. API pricing is $2 input and $10 output per million tokens, with cached input at $0.1.
Released Sep 30, 2026 — see all recent releases
Gemini 4 Argon will be repriced, updated or retired. Get each notice with its source and date. Follow model changes
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Decision snapshot
Each value carries a field reference instead of floating alone. Markers compare this model with the current ranked and priced catalog; they are not absolute quality thresholds.
Capability
64.6/100
field median 50.7#32 of 211 ranked models
Public
#32of 211
Verified —
Price
$2input / $10 output
input median $1cached $0.10 · blended $6
Speed
Not measured
field median 89 tok/sTime to first token not measured
Context
Not published
field median 256,000No exact-model context limit is sourced
Strongest published evidence
Coding ranks #8. Particularly well-suited for software development and code generation tasks.
Validate before choosing
17 published rows leave some tracked benchmark slots empty. Independent runtime speed has not been measured.
Source-linked · 17 displayable benchmark rows
Follow model changesCategory score record
Scores and ranks appear only where published evidence can be displayed. The table keeps the score, weight, cohort, and evidence state together.
| Category | Score | Rank | Percentile | Weight | Benchmarks | Evidence |
|---|---|---|---|---|---|---|
| AgenticRank #14 of 119Percentile 89thWeight 22%7 benchmarksVerified | 63.7 | 7 benchmarks | Verified | |||
| CodingRank #8 of 144Percentile 95thWeight 20%4 benchmarksVerified | 68.4 | 4 benchmarks | Verified | |||
| ReasoningRank Not rankedWeight 17%2 benchmarksVerified | 77.1 | 2 benchmarks | Verified | |||
| MultimodalWeight 12%2 benchmarksVerified | Score pending | 2 benchmarks | Verified | |||
| KnowledgeRank #11 of 170Percentile 94thWeight 12%1 benchmarkVerified | 72.9 | 1 benchmark | Verified | |||
| MultilingualWeight 7%0 benchmarksNot measured | Not measured | 0 benchmarks | Not measured | |||
| Inst. FollowingWeight 5%1 benchmarkVerified | Score pending | 1 benchmark | Verified | |||
| MathWeight 5%0 benchmarksNot measured | Not measured | 0 benchmarks | Not measured |
17 of 491 tracked benchmark slots have displayable evidence · bars run 0–100
Coverage detailsHow much of this is verified
Coverage is split by category so a strong number never hides a thin evidence base. Verified means the row is tied to a published source; provisional rows remain visible but separate.
- Agentic7/7 verified
- Coding4/4 verified
- Reasoning2/2 verified
- Multimodal2/2 verified
- Knowledge1/1 verified
- MultilingualNot measured
- Inst. Following1/1 verified
- MathNot measured
Capability shape
Each axis shows percentile within that category’s eligible cohort. The comparison outline is the median of the six nearest public-score peers; a collapsed vertex means the category is not rank-eligible.
Gemini 4 Argon category percentile values
- Agentic89th percentile
- Coding95th percentile
- ReasoningNot eligible
- MultimodalNot eligible
- Knowledge94th percentile
- MultilingualNot eligible
- Instruction followingNot eligible
- MathNot eligible
The dashed outline is median of 6 nearest peers.
Eligible category ranks
- Agentic#14/119
- Coding#8/144
- ReasoningNot ranked
- MultimodalNot ranked
- Knowledge#11/170
- MultilingualNot ranked
- Inst. FollowingNot ranked
- MathNot ranked
Benchmark ledger
Coding opens by default. The marker compares each value with the best source-verified result in the catalog; provisional leaders do not set the reference. Expand the remaining categories for every published row.
Coding4 rows
| Benchmark | Score | Versus best verified row | Gap | Weight | Evidence |
|---|---|---|---|---|---|
| DeepSWE | Score77.9% | Versus best verified row Best verified: Gemini 4 Argon · 77.9% | GapBest verified | Weight15% ref. weight | Provider exact |
| FrontierSWE v2 | Score55.1% | Versus best verified row Best verified: GPT-6 Astra · 65.5% | Gap10.4 behind | Weight8% ref. weight | Benchmark exact |
| Vibe Code BenchVibe Code Bench v1.1 | Score91.90% | Versus best verified row Best verified: Gemini 4 Argon · 91.90% | GapBest verified | WeightDisplay only | Provider exact |
| PostTrainBench v1.1 | Score45.3% | Versus best verified row Best verified: Claude Opus 5.5 · 49.3% | Gap4 behind | WeightDisplay only | Provider exact |
Agentic7 rows
| Benchmark | Score | Versus best verified row | Gap | Weight | Evidence |
|---|---|---|---|---|---|
| OSWorld 2.0 | Score69.2% | Versus best verified row Best verified: GPT-6 Astra · 72.6% | Gap3.4 behind | Weight10% ref. weight | Provider exact |
| Terminal-Bench 4.0 | Score57.40% | Versus best verified row Best verified: Claude Sonnet 5.5 · 70.60% | Gap13.2 behind | Weight8% ref. weight | Provider exact |
| AutomationBench | Score51.3% | Versus best verified row Best verified: DeepSeek V4.1 Flash · 54.8% | Gap3.5 behind | Weight5% ref. weight | Provider exact |
| Agents' Last Exam | Score39.5% | Versus best verified row Best verified: GPT-6 Astra · 59.3% | Gap19.8 behind | Weight3% ref. weight | Provider exact |
| Finance Agent v2 | Score65.4% | Versus best verified row Best verified: Gemini 4 Argon · 65.4% | GapBest verified | WeightDisplay only | Provider exact |
| CWE-bench v1 | Score68.0% | Versus best verified row Best verified: GPT-6 Astra · 68.0% | GapBest verified | WeightDisplay only | Benchmark exact |
| Terminal-Bench-Science 0.1 (6x verifier timeout)Terminal-Bench-Science 0.1 with sixfold verifier timeout | Score57.6% | Versus best verified row Best verified: Gemini 4 Argon · 57.6% | GapBest verified | WeightDisplay only | Provider exact |
Reasoning2 rows
| Benchmark | Score | Versus best verified row | Gap | Weight | Evidence |
|---|---|---|---|---|---|
| Graphwalks BFS 128KGraphwalks BFS 0K-128K | Score99.7% | Versus best verified row Best verified: Gemini 4 Argon · 99.7% | GapBest verified | WeightDisplay only | Provider exact |
| GraphWalks BFS 256K–1M | Score84.2% | Versus best verified row Best verified: Gemini 4 Argon · 84.2% | GapBest verified | WeightDisplay only | Provider exact |
Multimodal2 rows
| Benchmark | Score | Versus best verified row | Gap | Weight | Evidence |
|---|---|---|---|---|---|
| Chartography (no tools)Chartography without tools | Score71.6% | Versus best verified row Best verified: Gemini 4 Argon · 71.6% | GapBest verified | WeightDisplay only | Provider exact |
| LVBench | Score91.7% | Versus best verified row Best verified: Gemini 4 Argon · 91.7% | GapBest verified | WeightDisplay only | Provider exact |
Knowledge1 row
| Benchmark | Score | Versus best verified row | Gap | Weight | Evidence |
|---|---|---|---|---|---|
| LABBench2LABBench2: An Improved Benchmark for AI Systems Performing Biology Research | Score88.8% | Versus best verified row Best verified: Gemini 4 Argon · 88.8% | GapBest verified | WeightDisplay only | Provider exact |
Inst. Following1 row
| Benchmark | Score | Versus best verified row | Gap | Weight | Evidence |
|---|---|---|---|---|---|
| Gray Swan IPI (15 attempts)Gray Swan Indirect Prompt Injection, attack success at 15 attempts | Score0.7% | Versus best verified row Best verified: Gemini 4 Argon · 0.7% | GapBest verified | WeightDisplay only | Provider exact |
What it costs to get this score
Published API price against the public score. The x-axis uses a log scale; the dashed path marks models that are not beaten by a cheaper, higher-scoring option. Price uses average of published input and output rates.
Gemini 4 Argon · 64.6 score · $6 blended per million tokens
The chart opens on the current model. Scroll horizontally to inspect the full price axis.
Horizontal: blended price per million tokens, log scale · Vertical: public score
Lineage
The sequence follows explicit supersedes links. Each score is estimated for that model; a relative can inform a sparse estimate but never sets a floor, so a newer release can score below an earlier one. Scores and prices remain blank when the corresponding public row or first-party rate is unavailable.
Base entry
Gemini 4 Argon release history
Radar confirmed these at the source. Use Gemini 4 Argon in your work? Explore Radar to follow supported changes and choose your alerts.
Radar
Spec sheet
Each documented value carries its source. Missing fields stay visible as not sourced or not published, rather than disappearing from the page.
- API model ID
- Not publishedGoogle Gemini 4 Argon announcement
- Context window
- Not publishedGoogle Gemini 4 Argon announcement
- Maximum output
- Not sourced yet
- Knowledge cutoff
- Not sourced yet
- Input modalities
- Not sourced yetGoogle Gemini 4 Argon announcement
- Output modalities
- Not sourced yetGoogle Gemini 4 Argon announcement
- Parameters
- Not disclosed by the provider
- Availability
- Fairwind ProgramGoogle Gemini 4 Argon announcement
- Cloud regions
- Not tracked yet
- Lifecycle
- limited accessGoogle Gemini 4 Argon announcement
- API capabilities
- Tool calling, structured outputs, and batch support are not tracked yet
- Prompt caching
- Published at $0.10 per million cached input tokensGoogle Gemini 4 Argon announcement
- Self-host
- Weights are not published
- Rate limits
- Not tracked yet
How to read this profile
The visual layer above carries the decisions. These notes preserve the model, ranking, coverage, and family context behind the numbers.
Gemini 4 Argon ranks #32 of 211 on the public leaderboard with a score of 64.59/100. It does not yet have enough sourced coverage for a verified position.
Gemini 4 Argon is a proprietary model. It uses an explicit reasoning mode, which can improve complex problem solving while adding latency and token use.
Restricted rollout to trusted cyber defenders through the Fairwind Program. Broader access is planned, starting with paid API customers and Google AI Ultra subscribers; Google has not announced a public API model ID or a date for broad availability.
Google announced Gemini 4 Argon on September 30, 2026. The launch specifies a 1 million-token output limit, not an input context-window limit. Exact launch scores use the highest thinking settings unless noted. OSWorld 2.0 is the offline-subset partial score, maximized over three runs; Terminal-Bench-Science 0.1 uses a sixfold verifier timeout. PostTrainBench v1.1 and CWE-bench v1 remain separate from older benchmark versions. Vals Index (68.9%), Harvey legal (19.6%), and RiemannBench (76.0%) remain outside scored fields because the launch does not establish an exact compatible catalog protocol for each. Private vulnerability and prompt-injection charts are not ranking inputs. BenchAlign determines placement from available source-backed evidence; provider-reported launch scores do not establish a Supported position.
17 of 491 tracked benchmark slots currently have displayable evidence. Missing categories stay blank.
Its strongest eligible category is Coding at #8, while its lowest eligible position is Agentic at #14. particularly well-suited for software development and code generation tasks.
Last updated September 30, 2026. Runtime fields remain blank until a sourced snapshot exists.
Questions
How does Gemini 4 Argon perform overall in AI benchmarks?
Gemini 4 Argon ranks #32 out of 211 models on the public BenchAlign leaderboard, with a score of 64.59/100. Its evidence status is Estimated, and this profile shows 17 source-displayable benchmark rows. The label describes evidence depth, not a provider quality claim; inspect category rows before choosing a workload.
Is Gemini 4 Argon good for knowledge and understanding?
Gemini 4 Argon ranks #11 out of 170 eligible models for knowledge and understanding, with a public category score of 72.9/100. Higher-ranked alternatives are available for workloads where this category decides the choice. Check the underlying rows before treating the aggregate as a workload guarantee.
Is Gemini 4 Argon good for coding and programming?
Gemini 4 Argon ranks #8 out of 144 eligible models for coding and programming, with a public category score of 68.4/100. That places it in the current top ten for this category. Check the underlying rows before treating the aggregate as a workload guarantee.
Is Gemini 4 Argon good for reasoning and logic?
Gemini 4 Argon has source-displayable benchmark coverage for reasoning and logic, but the public category table does not assign it a rank there. The individual rows remain available for inspection. A missing category position means the evidence threshold was not met; it does not convert the model's unmeasured work into a zero.
Is Gemini 4 Argon good for agentic tool use and computer tasks?
Gemini 4 Argon ranks #14 out of 119 eligible models for agentic tool use and computer tasks, with a public category score of 63.7/100. Higher-ranked alternatives are available for workloads where this category decides the choice. Check the underlying rows before treating the aggregate as a workload guarantee.
Is Gemini 4 Argon good for multimodal and grounded tasks?
Gemini 4 Argon has source-displayable benchmark coverage for multimodal and grounded tasks, but the public category table does not assign it a rank there. The individual rows remain available for inspection. A missing category position means the evidence threshold was not met; it does not convert the model's unmeasured work into a zero.
Is Gemini 4 Argon good for instruction following?
Gemini 4 Argon has source-displayable benchmark coverage for instruction following, but the public category table does not assign it a rank there. The individual rows remain available for inspection. A missing category position means the evidence threshold was not met; it does not convert the model's unmeasured work into a zero.
Does Gemini 4 Argon have full benchmark coverage on BenchLM?
No. Gemini 4 Argon currently has 31 source-displayable rows across 491 tracked benchmark slots. The profile exposes published, non-generated evidence and leaves missing categories blank until an exact evaluation is available. Coverage describes how much was measured; it is not a penalty added to an individual benchmark result.
What is the context window size of Gemini 4 Argon?
Gemini 4 Argon's provider has not published a context-window limit for this exact model. The profile leaves the value unavailable instead of borrowing a number from an earlier family member or a third-party route. Maximum output length is tracked separately when the provider documents it.