Skip to main content
BenchLM

Data as of September 30, 2026 · How the score is built

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

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 changes

Category 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 scores, ranks, weighting, benchmark coverage, and evidence status
CategoryScore
AgenticRank #14 of 119Percentile 89thWeight 22%7 benchmarksVerified
63.7
CodingRank #8 of 144Percentile 95thWeight 20%4 benchmarksVerified
68.4
ReasoningRank Not rankedWeight 17%2 benchmarksVerified
77.1
MultimodalWeight 12%2 benchmarksVerified
Score pending
KnowledgeRank #11 of 170Percentile 94thWeight 12%1 benchmarkVerified
72.9
MultilingualWeight 7%0 benchmarksNot measured
Not measured
Inst. FollowingWeight 5%1 benchmarkVerified
Score pending
MathWeight 5%0 benchmarksNot measured
Not measured

17 of 491 tracked benchmark slots have displayable evidence · bars run 0–100

Coverage details

How 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.

  1. Agentic7/7 verified
  2. Coding4/4 verified
  3. Reasoning2/2 verified
  4. Multimodal2/2 verified
  5. Knowledge1/1 verified
  6. MultilingualNot measured
  7. Inst. Following1/1 verified
  8. MathNot measured
Verified sourceProvisionalNot 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

  1. Agentic#14/119
  2. Coding#8/144
  3. ReasoningNot ranked
  4. MultimodalNot ranked
  5. Knowledge#11/170
  6. MultilingualNot ranked
  7. Inst. FollowingNot ranked
  8. MathNot ranked
Top decileTop quartileMid-fieldNot eligible

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
Coding benchmark values, best verified comparison, weight, and source status
DeepSWEScore77.9%Versus best verified row

Best verified: Gemini 4 Argon · 77.9%

GapBest verifiedWeight15% ref. weight
FrontierSWE v2Score55.1%Versus best verified row

Best verified: GPT-6 Astra · 65.5%

Gap10.4 behindWeight8% ref. weight
Vibe Code BenchVibe Code Bench v1.1Score91.90%Versus best verified row

Best verified: Gemini 4 Argon · 91.90%

GapBest verifiedWeightDisplay only
PostTrainBench v1.1Score45.3%Versus best verified row

Best verified: Claude Opus 5.5 · 49.3%

Gap4 behindWeightDisplay only
Agentic7 rows
Agentic benchmark values, best verified comparison, weight, and source status
OSWorld 2.0Score69.2%Versus best verified row

Best verified: GPT-6 Astra · 72.6%

Gap3.4 behindWeight10% ref. weight
Terminal-Bench 4.0Score57.40%Versus best verified row

Best verified: Claude Sonnet 5.5 · 70.60%

Gap13.2 behindWeight8% ref. weight
AutomationBenchScore51.3%Versus best verified row

Best verified: DeepSeek V4.1 Flash · 54.8%

Gap3.5 behindWeight5% ref. weight
Agents' Last ExamScore39.5%Versus best verified row

Best verified: GPT-6 Astra · 59.3%

Gap19.8 behindWeight3% ref. weight
Finance Agent v2Score65.4%Versus best verified row

Best verified: Gemini 4 Argon · 65.4%

GapBest verifiedWeightDisplay only
CWE-bench v1Score68.0%Versus best verified row

Best verified: GPT-6 Astra · 68.0%

GapBest verifiedWeightDisplay only
Terminal-Bench-Science 0.1 (6x verifier timeout)Terminal-Bench-Science 0.1 with sixfold verifier timeoutScore57.6%Versus best verified row

Best verified: Gemini 4 Argon · 57.6%

GapBest verifiedWeightDisplay only
Reasoning2 rows
Reasoning benchmark values, best verified comparison, weight, and source status
Graphwalks BFS 128KGraphwalks BFS 0K-128KScore99.7%Versus best verified row

Best verified: Gemini 4 Argon · 99.7%

GapBest verifiedWeightDisplay only
GraphWalks BFS 256K–1MScore84.2%Versus best verified row

Best verified: Gemini 4 Argon · 84.2%

GapBest verifiedWeightDisplay only
Multimodal2 rows
Multimodal benchmark values, best verified comparison, weight, and source status
Chartography (no tools)Chartography without toolsScore71.6%Versus best verified row

Best verified: Gemini 4 Argon · 71.6%

GapBest verifiedWeightDisplay only
LVBenchScore91.7%Versus best verified row

Best verified: Gemini 4 Argon · 91.7%

GapBest verifiedWeightDisplay only
Knowledge1 row
Knowledge benchmark values, best verified comparison, weight, and source status
LABBench2LABBench2: An Improved Benchmark for AI Systems Performing Biology ResearchScore88.8%Versus best verified row

Best verified: Gemini 4 Argon · 88.8%

GapBest verifiedWeightDisplay only
Inst. Following1 row
Inst. Following benchmark values, best verified comparison, weight, and source status
Gray Swan IPI (15 attempts)Gray Swan Indirect Prompt Injection, attack success at 15 attemptsScore0.7%Versus best verified row

Best verified: Gemini 4 Argon · 0.7%

GapBest verifiedWeightDisplay only

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.

Current modelExplore all models

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.

2030405060708090100$0.10$0.50$1$5$10$25$50$100↘ frontierGemini 4 Argon

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.

  1. Sep 30, 2026 · you are here

    Gemini 4 Argon

    Score 64.6 · $2 / $10

Base entry

Radar

Gemini 4 Argon release history

Full 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.

Watch Gemini 4 Argon in the weekly brief

Get one weekly email when material rank, price, availability, or benchmark evidence changes are worth revisiting.

Read a sample issue

Join 2,000+ readers.

Compare Gemini 4 Argon with every tracked model524 comparisons