BenchLeader

Gemini 4 Argon

Reasoning effort

Gemini 4 Argon is a Google proprietary reasoning model, released 30 Sept 2026. Its best configuration (high reasoning effort) ranks #2 of 775 on the BenchLeader Index at 71.0 ±2.6, in the top ten. The ± is the point: 37 other configurations score within that range, so they and this one cannot be told apart on quality alone — price and speed are what separate them. It scores highest in composite (89) and lowest in long context (65). At $4.00 per million tokens blended it is among the most expensive ranked models. Output speed of 83 tokens per second puts it slower than most, with a first answer in 48.5 s. It has been measured at 5 reasoning-effort settings; this summary describes the best-scoring one, and the tabs above switch between them. Last measured 19 Oct 2026.

Blended price
$4.00/M
$2.00 in · $10.00 out
Output speed
83 tok/s
measured by Artificial Analysis
First answer
49 s
first token 4.23 s
Context
1.0M
Full answer
55 s
median, reasoning included
Cost per run
$1.99
one full Intelligence Index run
Released
30 Sept 2026
How it scores by categoryDashed line = average model (50). One step of 15 = one standard deviation.
  1. Overall index71
  2. Reasoning75
  3. Coding72
  4. Agents & tools72
  5. Maths71
  6. Knowledge77
  7. Human preference73
  8. Long context65
  9. Composite89

Reasoning-effort configurations

The same model behaves differently depending on how much it is allowed to think. Each row is one setting, scored only on the benchmarks that were run at that setting. “Not stated” collects results from publishers that did not say which setting they used; for a reasoning model that is usually its thinking mode, but we do not assume it. Pick a setting here or at the top of the page to see its price, speed and category scores.

EffortIndexRankSpeedFirst answerChat reply costCategories
minimal––40 tok/s4.23 s$0.0038
low––40 tok/s4.23 s$0.0038Reasoning 60
medium––40 tok/s4.23 s$0.0038Coding 62 · Reasoning 72
highbest71.0#283 tok/s49 s$0.0038Agents & tools 72 · Coding 72 · Composite 89 · Human preference 73 · Knowledge 77 · Long context 65 · Maths 71 · Reasoning 75
not stated63.3#6640 tok/s4.23 s$0.0038Agents & tools 75 · Composite 68 · Knowledge 59 · Maths 78

How its index has moved

2 Oct 2026 to 21 Oct 2026
606774
  • high
  • not stated

The index is recomputed from scratch every day, so a line moves when a new benchmark result lands, when a publisher revises a score, or when the models it is normalised against change. Early movement usually means the score is still settling.

Benchmark results

See all LLM benchmarks. One column per reasoning effort. Rank is among every configuration of every model on that benchmark. Hover a score for the run it came from.

Reasoning

Benchmarklowmediumhighnot statedSourceTrend
GPQA Diamond––96.4%#1–Epoch AI Benchmarking Hub
Arena Hard Prompts––1549#1–Arena (LMArena)
LiveBench 2.0 Reasoningnot in indexeffort not stated–––95.1%#1LiveBench
Humanity's Last Exam (AA)not in index––57.1%#5–Artificial Analysis
ARC-AGI-176.5%#12098.5%#198.5%#1–ARC Prize
ARC-AGI-242.1%#11087.1%#2591.3%#12–ARC Prize
ARC-AGI-397.5%#697.3%#797.3%#7–ARC Prize
CritPt––27.1%#33–Artificial Analysis
MysteryMechanismnot in index––45.5%#6–Vals AI
Chess Puzzlesnot in index––59.0%#10–Epoch AI Benchmarking Hub
Mystery Game Puzzlesnot in index––64.0%#5–Epoch AI Benchmarking Hub
LMCAnot in index62.9%#2562.9%#2663.7%#19–Epoch AI Benchmarking Hub
DTBenchnot in index97.6%#597.3%#997.3%#9–Epoch AI Benchmarking Hub

Coding

Benchmarkminimallowmediumhighnot statedSourceTrend
SciCode–––61.8%#4–SciCode
FrontierCode––47.5%#12––Cognition
Arena Coding–––1559#1–Arena (LMArena)
Arena WebDev–––1678#10–Arena (LMArena)
LiveBench 2.0 Codingnot in indexeffort not stated––––89.7%#14LiveBench
SciCode (AA)not in index–––61.8%#5–Artificial Analysis
IOI–––100.0%#1–Vals AI
Code Migrationnot in index–––68.2%#2–Vals AI
ProgramBenchnot in index–––2.5%#7–Vals AI
Vibe Code Bench 1-100not in index–––21.2%#8–Vals AI
Vibe Code Bench v1.1not in index–––91.9%#2–Vals AI
CursorBenchnot in index48.8%#1450.6%#1152.8%#752.9%#6–Cursor
ALE-Benchnot in index–1705.4#13–2100.1#8–Epoch AI Benchmarking Hub
FrontierSWEnot in index–––55.0%#5–Epoch AI Benchmarking Hub
Terminal-Bench 4.0 (AA)not in index–––57.1%#6–Artificial Analysis
FrontierCode 1.1 (AA)not in index–––43.5%#17–Artificial Analysis

Agents & tools

Benchmarkhighnot statedSourceTrend
APEX-Agentseffort not stated–82.4%#1Mercor
Arena Agent12.1#6–Arena (LMArena)
LiveBench Long Agenticnot in indexeffort not stated–69.9%#6LiveBench
LiveBench Browsernot in indexeffort not stated–92.0%#3LiveBench
HiL-Bencheffort not stated–62.0%#5Scale AI SEAL
GDPval-AA v2.1not in index56.2%#24–Artificial Analysis
Analyst Agent (AA)not in index48.8%#12–Artificial Analysis
CUA-benchnot in index4.8%#8–Vals AI
CyberBenchnot in index77.9%#3–Vals AI
Finance Agent v2not in index65.4%#1–Vals AI
Harvey's Legal Agent Benchmarknot in index27.1%#1–Vals AI
Legal Research Benchnot in index54.8%#4–Vals AI
SREBenchnot in index44.3%#3–Vals AI
Tax Agent Benchnot in index44.6%#4–Vals AI
Terminal-Bench 4.0 (Vals)not in index57.6%#6–Vals AI
Terminal-Bench Sciencenot in index44.3%#5–Vals AI
Time Horizon Index: KSPnot in index52.5%#4–Vals AI
Vending-Bench 2not in indexeffort not stated–13718.2#3Andon Labs
AutomationBenchnot in index77.5%#1–Artificial Analysis
GDP.pdf (AA)not in index21.8%#51–Artificial Analysis
Harvey LAB-AA v1.1not in index3.9%#10–Harvey
AA-Briefcase v1.1not in index1486#32–Artificial Analysis
Terminal-Bench-Science 0.1 (AA)not in index52.9%#6–Artificial Analysis
FACTS Searchnot in indexeffort not stated–84.0%#7Google

Knowledge

Benchmarkhighnot statedSourceTrend
SimpleQA Verified76.0%#1–Epoch AI Benchmarking Hub
LiveBench 2.0 Data Analysisnot in indexeffort not stated–85.2%#1LiveBench
LiveBench Researchnot in indexeffort not stated–83.1%#12LiveBench
AA-Omniscience42.4#9–Artificial Analysis
LegalBench88.3%#3–Vals AI
PRBench Financeeffort not stated–49.9%#11Scale AI SEAL
PRBench Legaleffort not stated–49.4%#12Scale AI SEAL
BioMysteryBenchnot in index76.3%#6–Vals AI
Excel Modeling Benchmarknot in index75.2%#4–Vals AI
MedCodenot in index58.8%#3–Vals AI
MedScribenot in index87.4%#17–Vals AI
Public Benefits Benchnot in index69.8%#7–Vals AI
EBR-benchnot in index64.8%#3–Epoch AI Benchmarking Hub
GDP.pdfnot in index28.4%#11–Epoch AI Benchmarking Hub
AA-Omniscience: accuracynot in index49.9%#62–Artificial Analysis
AA-Omniscience: non-hallucinationnot in index84.9%#5–Artificial Analysis

Instruction following

BenchmarkhighSourceTrend
Arena Instruction Followingnot in index1527#1Arena (LMArena)

Human preference

Multimodal

Benchmarkhighnot statedSourceTrend
LiveBench Designnot in indexeffort not stated–73.7%#31LiveBench
SAGEnot in index53.6%#4–Vals AI
AudioMCnot in index58.4%#3–Scale AI SEAL
AudioMC (text output)not in index58.4%#3–Scale AI SEAL
Blueprint-Bench 2not in indexeffort not stated–54.5%#1Epoch AI Benchmarking Hub
AA-3Dnot in index1154#4–Artificial Analysis

Long context

BenchmarkhighSourceTrend
AA-LCR79.7%#87Artificial Analysis

Composite

Benchmarkhighnot statedSourceTrend
Epoch Capabilities Indexnot in indexeffort not stated–166.4#5Epoch AI Benchmarking Hub
LiveBench 2.0effort not stated–84.1%#5LiveBench
AA Intelligence Index v4.3.252.6#9–Artificial Analysis
Vals Indexnot in index69.2#3–Vals AI

Where it wins

Benchmarks where this configuration ranks in the top five of every configuration measured.

Where to run it

Every provider serving this model through OpenRouter, with throughput and first-token latency measured on live traffic over the last 30 minutes and each provider’s own price. Purple marks the best in each column.

ProviderSpeedFirst tokenInput $/MOutput $/MContextQuantisation
Google AI Studio46 tok/s4.70 s$1.00$5.001.0M–
Google Vertex40 tok/s3.33 s$3.60$18.001.0M–
Google AI Studio40 tok/s6.33 s$2.00$10.001.0M–
Google Vertex39 tok/s4.58 s$2.00$10.001.0M–
Google Vertex27 tok/s3.95 s$2.20$11.001.0M–

What a task costs

Estimates from list price, output speed and time to first answer for the best configuration. “With caching” assumes three-quarters of the input is served from the prompt cache at $0.100 per 1M. Reasoning tokens are not modelled.

WorkloadTokens in / outCostWith cachingTime
Chat reply400 / 300$0.0038$0.003252.2 s
Summarize a 30-page report12,000 / 600$0.030$0.01355.8 s
Code edit6,000 / 1,500$0.027$0.0181.1 min
Agentic coding session60,000 / 4,000$0.160$0.0741.6 min
Structured extraction2,000 / 200$0.0060$0.003251.0 s

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See also

Data as of 21 Oct 2026. Compare these configurations.

Cite as: BenchLeader, “Gemini 4 Argon: benchmarks, pricing, speed and rank”, https://www.benchleader.com/models/gemini-4-argon, data as of 21 Oct 2026.