Claude Sonnet 4.6 vs Gemini 4 Argon

Updated November 13, 2026. Rank says Gemini 4 Argon is ahead. Price, access, and your workload can each overturn that. Public scores include evidence status and uncertainty.

Decision reading

Gemini 4 Argon has the higher public score, 79.03 versus 55.81, and the 90% score intervals do not overlap. 6 results are shared. Category rows resting on Estimated evidence or different benchmark sets are marked directional and do not name a winner.

Model A

Claude Sonnet 4.6

Anthropic

55.81/100

Supported · Public rank #63

90% interval 43.1–68.5

Model B

Gemini 4 Argon

Google

79.03/100

Supported · Public rank #8

90% interval 75.4–82.7

API price per 1M tokens

Claude Sonnet 4.6: $3 input / $15 output

Gemini 4 Argon: $2 input / $10 output

Context window

Claude Sonnet 4.6: 200K

Gemini 4 Argon: 1M

Released

Claude Sonnet 4.6: February 1, 2026

Gemini 4 Argon: September 30, 2026

Shared results: 6
Claude Sonnet 4.6 only: 22
Gemini 4 Argon only: 33
Like-for-like categories: 4 / 8

Supported: Claude Sonnet 4.6 and Gemini 4 ArgonHow the comparison works

Which one for your work

Recommendations appear only when a shared evidence basis or an explicit operating constraint supports the call. Secondary and unsupported use cases stay disclosed below the initial list.

Coding work
Code generation, repair, and software-engineering tasks
Gemini 4 Argon
Gemini 4 Argon has the higher public coding point estimate, 71.8 to 44.7, with Supported evidence for both models. The conditional ranges do not establish rank confidence.
Confidence: limited
Agentic work
Tool use, computer use, and multi-step task completion
Gemini 4 Argon
Gemini 4 Argon has the higher public agentic point estimate, 74.9 to 47.4, with Supported evidence for both models. The conditional ranges do not establish rank confidence.
Confidence: limited
Long documents
Prompts that approach the documented context limit
Gemini 4 Argon
Gemini 4 Argon has the larger documented context window.
Confidence: documented

Show secondary and unsupported calls

Chat turn cost
1K fresh input + 500 output tokens
Gemini 4 Argon
Gemini 4 Argon has the lower estimated token cost for this stated workload. Costs use the listed standard API rates.
Confidence: listed-rates
Repository review cost
50K fresh input + 3K output tokens
Gemini 4 Argon
Gemini 4 Argon has the lower estimated token cost for this stated workload. Costs use the listed standard API rates.
Confidence: listed-rates
Cache-heavy agent loop cost
200K cached + 20K fresh input + 10K output tokens
Not enough matched evidence
The page does not recommend a cost winner because at least one model cannot fit the stated workload in one request. Claude Sonnet 4.6 does not fit this workload in one request. Claude Sonnet 4.6 has no published cached-input rate, so cached tokens use its listed input rate.
Confidence: rate-fallback

Which one for a specific job

Choose a job from the LLM Selector's task catalog to see the category row it rests on, under the same basis rules as the table below. A directional row stays directional; choosing a job never creates a winner.

Pick the job you would use them for

The same task catalog as the LLM Selector. Each job names the evidence surface it rests on; nothing here adds a new score.

44.7Claude Sonnet 4.671.8Gemini 4 Argon

Like-for-like · BenchAlign v5.8

Gemini 4 Argon has the higher coding point estimate. Conditional score ranges do not establish rank confidence.

Coding scores combine specific tasks and setups. Match the editor, harness, and effort to your workflow.

Open the coding leaderboard Shortlist models for this job

Same basis rules as the category table below

Or describe your own job

The LLM Selector reads what you need a model for and returns a shortlist, ranked in the same order the job pages publish.

What do you need a model for?

Describe the task and constraints. This selector recommends models; it cannot carry out the task or access your files and accounts.

We keep what you type here, drafts included, for 180 days, and after that only the job and requirements read from it. Nothing is tied to your IP address or account. Leave out names and other personal details. Privacy

Shape of the matched evidence

Only shared public evidence is shown. Sparse evidence stays a ruled list rather than being closed into a radar shape.

Too few matched category axes support a radar. The ruled list below shows only shared benchmark results; positions use each benchmark’s normalized display scale when available.

OSWorld 2.0Agentic
Normalized gap 60.9
Claude Sonnet 4.6:8.3%
Gemini 4 Argon:69.2%
Claude Sonnet 4.6 source Gemini 4 Argon source
ARC-AGI-2Reasoning
Normalized gap 32.9
Claude Sonnet 4.6:58.3%
Gemini 4 Argon:91.3%
Claude Sonnet 4.6 source Gemini 4 Argon source

Bars run 0–100 on each benchmark’s normalized display scale

Category results, on a stated basis

Each row shows the public-lane category score for both models: the BenchAlign v5.8 lane for agentic, coding, reasoning, multimodal, and knowledge, and the weighted public rows elsewhere, with the same rank each model page reports. A row is like-for-like only when both scores rest on Supported evidence or the same weighted set. Directional and not-comparable rows remain visible, but they never receive a winner.

Agentic

Like-for-like

Claude Sonnet 4.6: 47.4; Supported · #56/135
Gemini 4 Argon: 74.9; Supported · #6/135
Basis: BenchAlign v5.8 lane · 10 vs 13 public rows
Reading: Gemini 4 Argon leads

Coding

Like-for-like

Claude Sonnet 4.6: 44.7; Supported · #61/162
Gemini 4 Argon: 71.8; Supported · #9/162
Basis: BenchAlign v5.8 lane · 9 vs 9 public rows
Reading: Gemini 4 Argon leads

Reasoning

Like-for-like

Claude Sonnet 4.6: 50.6; Supported · #51/160
Gemini 4 Argon: 76.5; Supported · #7/160
Basis: BenchAlign v5.8 lane · 2 vs 7 public rows
Reading: Gemini 4 Argon leads

Knowledge

Like-for-like

Claude Sonnet 4.6: 56.0; Supported · #57/180
Gemini 4 Argon: 79.2; Supported · #8/180
Basis: BenchAlign v5.8 lane · 6 vs 2 public rows
Reading: Gemini 4 Argon leads

Multimodal

Not comparable

Claude Sonnet 4.6: 55.2; Supported · #43/67
Gemini 4 Argon: Not ranked
Basis: BenchAlign v5.8 lane · 1 vs 5 public rows
Reading: Not comparable

Multilingual

Not comparable

Claude Sonnet 4.6: Not ranked
Gemini 4 Argon: Not ranked
Basis: Provisional lane · 0 vs 0 weighted rows
Reading: Not comparable

Instruction following

Not comparable

Claude Sonnet 4.6: 48.0; #106/157
Gemini 4 Argon: Not ranked
Basis: Provisional lane · 0 vs 0 weighted rows
Reading: Not comparable

Math

Not comparable

Claude Sonnet 4.6: Not ranked
Gemini 4 Argon: 87.4; Unranked · 2 rankable rows
Basis: Provisional lane · 0 vs 2 weighted rows
Reading: Not comparable

Category scores with the server-provided evidence basis for Claude Sonnet 4.6 and Gemini 4 Argon
Category	Claude Sonnet 4.6	Gemini 4 Argon	Basis	Reading
Agentic	47.4Supported · #56/135	74.9Supported · #6/135	Like-for-likeBenchAlign v5.8 lane · 10 vs 13 public rows	Gemini 4 Argon leads
Coding	44.7Supported · #61/162	71.8Supported · #9/162	Like-for-likeBenchAlign v5.8 lane · 9 vs 9 public rows	Gemini 4 Argon leads
Reasoning	50.6Supported · #51/160	76.5Supported · #7/160	Like-for-likeBenchAlign v5.8 lane · 2 vs 7 public rows	Gemini 4 Argon leads
Knowledge	56.0Supported · #57/180	79.2Supported · #8/180	Like-for-likeBenchAlign v5.8 lane · 6 vs 2 public rows	Gemini 4 Argon leads
Multimodal	55.2Supported · #43/67	Not ranked	Not comparableBenchAlign v5.8 lane · 1 vs 5 public rows	Not comparable
Multilingual	Not ranked	Not ranked	Not comparableProvisional lane · 0 vs 0 weighted rows	Not comparable
Instruction following	48.0#106/157	Not ranked	Not comparableProvisional lane · 0 vs 0 weighted rows	Not comparable
Math	Not ranked	87.4Unranked · 2 rankable rows	Not comparableProvisional lane · 0 vs 2 weighted rows	Not comparable

Ranks count the models scored in each category’s lane, so the agentic, coding, reasoning, multimodal, and knowledge denominators (BenchAlign v5.8) differ from the provisional-lane categories. Unranked scores sit on the provisional lane’s scale but never name a winner. Like-for-like rows within 0.5 points read as a practical tie.

Supported evidence per lane · bars run 0–100Methodology

What each workload costs

Three fixed token mixes turn per-token rates into comparable decisions. Each scenario states context fit and whether cached input had to fall back to the published list-input rate.

Chat turn

1K fresh input + 500 output tokens

Claude Sonnet 4.6: $0.0105; Fits in one request
Gemini 4 Argon: $0.007; Fits in one request

Gemini 4 Argon has the lower modeled cost

Costs use the listed standard API rates.

Repository review

50K fresh input + 3K output tokens

Claude Sonnet 4.6: $0.195; Fits in one request
Gemini 4 Argon: $0.13; Fits in one request

Gemini 4 Argon has the lower modeled cost

Costs use the listed standard API rates.

Cache-heavy agent loop

200K cached + 20K fresh input + 10K output tokens

Claude Sonnet 4.6: $0.81; Does not fit in one request; Cached input priced at the published list-input rate
Gemini 4 Argon: $0.16; Fits in one request

Claude Sonnet 4.6 does not fit this workload in one request. Claude Sonnet 4.6 has no published cached-input rate, so cached tokens use its listed input rate.

Your workload

Enter a month of tokens to price it at both models’ listed API rates.

Input, millionsOutput, millionsCached input, %

Claude Sonnet 4.6: $60.00; per month
Gemini 4 Argon: $40.00; per month

Standard listed rates, no batch or volume discounts.

Cached input falls back to the list input rate only where a cached rate is unpublished

Price against score, among all priced models

Overall score against output price per 1M tokens, one model per family. Pricing as of November 12, 2026.

Claude Sonnet 4.6Gemini 4 Argon

27 models score at least as high as Claude Sonnet 4.6 for the same price or less. The nearest is Kimi K3 (score 68.4, also $15.00 per 1M output tokens).
2 models at the same price score higher than Gemini 4 Argon. The nearest is Gemini 4 Carbon (score 89.2, also $10.00 per 1M output tokens).

Gray dots are the other priced models. The dark step line is the efficiency frontier: for a model under it, another model costs no more and scores at least as high.

See Gemini 4 Argon on the full price vs performance chart

Specification differences

Sourced differences are shown directly. Missing facts stay explicit instead of being inferred from a model name or family.

SpecificationClaude Sonnet 4.6Gemini 4 Argon

Context window

Maximum documented context; output-token limits may be lower.

Claude Sonnet 4.6

200K

Gemini 4 Argon

Google Gemini 4 Argon model documentation

API model ID

Claude Sonnet 4.6

Not sourced

Gemini 4 Argon

gemini-4-argon

Google Gemini 4 Argon model documentation

Cached-input rate

A missing cached-input rate falls back to the listed input rate only in the stated workload estimate.

Claude Sonnet 4.6

Not published

Gemini 4 Argon

$0.1 per 1M cached input tokens

Google Gemini API pricing

Documented inputs

Claude Sonnet 4.6

text, image

Anthropic Claude Sonnet 4.6 model page

Gemini 4 Argon

text, image, video, audio, pdf

Google Gemini 4 Argon model documentation

Documented outputs

Claude Sonnet 4.6

text

Anthropic Claude Sonnet 4.6 model page

Gemini 4 Argon

text

Google Gemini 4 Argon model documentation

Provider availability

Claude Sonnet 4.6

Not sourced

Gemini 4 Argon

Generally Available · Gemini API, Google AI Studio

Google Gemini 4 Argon model documentation

Reasoning profile

Claude Sonnet 4.6

Non-Reasoning

Gemini 4 Argon

Reasoning

Weight access

Claude Sonnet 4.6

Proprietary

Gemini 4 Argon

Proprietary

License

Claude Sonnet 4.6

Proprietary

Gemini 4 Argon

Proprietary

Release date

Claude Sonnet 4.6

2026-02-01

Gemini 4 Argon

2026-09-30

If you already use one of these models

Deployment change: The models list different providers, so authentication, endpoint behavior, limits, and feature support may change.
Quality signal: Gemini 4 Argon has the higher public score, 79.03 versus 55.81, and the 90% score intervals do not overlap.
Workload cost: Repository review: $0.195 vs $0.13. Cache-heavy agent loop: $0.81 vs $0.16.
Context tradeoff: Gemini 4 Argon has the larger documented window (1M).

Run the same representative tasks against both endpoints before changing production traffic.

Questions

Which is better, Claude Sonnet 4.6 or Gemini 4 Argon?

Gemini 4 Argon has the higher public score, 79.03 versus 55.81, and the 90% score intervals do not overlap. That is the clearest overall quality signal in the current public data.

Which is better for coding, Claude Sonnet 4.6 or Gemini 4 Argon?

Gemini 4 Argon has the higher public coding point estimate, 71.8 to 44.7, with Supported evidence for both models. The conditional ranges do not establish rank confidence.

Which is better for agentic tasks, Claude Sonnet 4.6 or Gemini 4 Argon?

Gemini 4 Argon has the higher public agentic tasks point estimate, 74.9 to 47.4, with Supported evidence for both models. The conditional ranges do not establish rank confidence.

Which costs less, Claude Sonnet 4.6 or Gemini 4 Argon?

For the stated presets, chat costs $0.0105 on Claude Sonnet 4.6 and $0.007 on Gemini 4 Argon; repository review costs $0.195 and $0.13; the cache-heavy agent loop costs $0.81 and $0.16. Claude Sonnet 4.6 does not fit this workload in one request. Claude Sonnet 4.6 has no published cached-input rate, so cached tokens use its listed input rate.

Which has the larger context window, Claude Sonnet 4.6 or Gemini 4 Argon?

Gemini 4 Argon has the larger documented context window: 1M, compared with 200K.

Benchmark evidence

The full public result ledger is available for audit without forcing a wide desktop table onto a phone.

Browse raw public benchmark evidence61 rows

Agentic

Terminal-Bench 2.0
Claude Sonnet 4.659.1%
Source
Gemini 4 Argon—
Not directly comparable
OSWorld-Verified
Claude Sonnet 4.672.1%
Source
Gemini 4 Argon—
Not directly comparable
Claw-Eval
Claude Sonnet 4.667.8%
Source
Gemini 4 Argon—
Not directly comparable
CyberGym
Claude Sonnet 4.665.2%
Source
Gemini 4 Argon—
Not directly comparable
Gert Labs
Claude Sonnet 4.662.92%
Source
Gemini 4 Argon—
Not directly comparable
OSWorld 2.0
Claude Sonnet 4.68.3%
Source
Gemini 4 Argon69.2%
Source
Gemini 4 Argon leads this result
JobBench
Claude Sonnet 4.636.9%
Source
Gemini 4 Argon—
Not directly comparable
Terminal-Bench 2.1 (Vals)
Claude Sonnet 4.657.3%
Source
Gemini 4 Argon57.7%
Source
Gemini 4 Argon leads this result
ApprenticeBench
Claude Sonnet 4.62%
Source
Gemini 4 Argon—
Not directly comparable
MazeBench
Claude Sonnet 4.60%
Source
Gemini 4 Argon12%
Source
Gemini 4 Argon leads this result
AutomationBench
Claude Sonnet 4.6—
Gemini 4 Argon51.3%
Source
Not directly comparable
Finance Agent v2
Claude Sonnet 4.6—
Gemini 4 Argon65.4%
Source
Not directly comparable
Terminal-Bench 4.0
Claude Sonnet 4.6—
Gemini 4 Argon57.40%
Source
Not directly comparable
Agents' Last Exam
Claude Sonnet 4.6—
Gemini 4 Argon39.5%
Source
Not directly comparable
CWE-bench v1
Claude Sonnet 4.6—
Gemini 4 Argon68.0%
Source
Not directly comparable
Terminal-Bench-Science 0.1 (6x verifier timeout)
Claude Sonnet 4.6—
Gemini 4 Argon57.6%
Source
Not directly comparable
OSWorld 2.1 Offline
Claude Sonnet 4.6—
Gemini 4 Argon74.7%
Source
Not directly comparable
ExploitGym
Claude Sonnet 4.6—
Gemini 4 Argon39.5%
Source
Not directly comparable
RoboDojo Sim
Claude Sonnet 4.6—
Gemini 4 Argon34.2%
Source
Not directly comparable
CWE-bench
Claude Sonnet 4.6—
Gemini 4 Argon65.0%
Source
Not directly comparable

Coding

SWE-bench Verified
Claude Sonnet 4.679.6%
Source
Gemini 4 Argon—
Not directly comparable
SWE-Rebench
Claude Sonnet 4.660.7%
Source
Gemini 4 Argon—
Not directly comparable
React Native Evals
Claude Sonnet 4.680.6%
Source
Gemini 4 Argon—
Not directly comparable
Terminal-Bench 2.0
Claude Sonnet 4.659.1%
Source
Gemini 4 Argon—
Not directly comparable
Vibe Code Bench
Claude Sonnet 4.651.48%
Source
Gemini 4 Argon91.90%
Source
Gemini 4 Argon leads this result
cursorBench31
Claude Sonnet 4.648.8%
Source
Gemini 4 Argon—
Not directly comparable
FrontierCode 1.1 Main
Claude Sonnet 4.624.3%
Source
Gemini 4 Argon—
Not directly comparable
LiveCodeBench (Vals)
Claude Sonnet 4.682.1%
Source
Gemini 4 Argon—
Not directly comparable
SWE-bench (Vals)
Claude Sonnet 4.677.4%
Source
Gemini 4 Argon—
Not directly comparable
ScarfBench
Claude Sonnet 4.6—
Gemini 4 Argon75.2%
Source
Not directly comparable
DeepSWE
Claude Sonnet 4.6—
Gemini 4 Argon77.9%
Source
Not directly comparable
FrontierSWE v2
Claude Sonnet 4.6—
Gemini 4 Argon55.0%
Source
Not directly comparable
PostTrainBench v1.1
Claude Sonnet 4.6—
Gemini 4 Argon45.3%
Source
Not directly comparable
Bug Hunt Bench
Claude Sonnet 4.6—
Gemini 4 Argon40.7 fixes
Source
Not directly comparable
FrontierCode 2.0
Claude Sonnet 4.6—
Gemini 4 Argon26.3%
Source
Not directly comparable
CursorBench 4.0
Claude Sonnet 4.6—
Gemini 4 Argon52.9%
Source
Not directly comparable
PostTrainBench
Claude Sonnet 4.6—
Gemini 4 Argon40.4%
Source
Not directly comparable

Reasoning

ARC-AGI-2
Claude Sonnet 4.658.3%
Source
Gemini 4 Argon91.3%
Source
Gemini 4 Argon leads this result
ARC-AGI-1
Claude Sonnet 4.686.00%
Source
Gemini 4 Argon98.50%
Source
Gemini 4 Argon leads this result
STEMBench
Claude Sonnet 4.6—
Gemini 4 Argon2.44
Source
Not directly comparable
Graphwalks BFS 128K
Claude Sonnet 4.6—
Gemini 4 Argon99.7%
Source
Not directly comparable
GraphWalks BFS 256K–1M
Claude Sonnet 4.6—
Gemini 4 Argon84.2%
Source
Not directly comparable
ARC-AGI-3
Claude Sonnet 4.6—
Gemini 4 Argon46.3%
Source
Not directly comparable
ARC-AGI-3 Provider Adapter
Claude Sonnet 4.6—
Gemini 4 Argon97.30%
Source
Not directly comparable

Multimodal

CharXiv
Claude Sonnet 4.677.4%
Source
Gemini 4 Argon—
Not directly comparable
ParseBench-2
Claude Sonnet 4.6—
Gemini 4 Argon84.20%
Source
Not directly comparable
ExtractBench Pro
Claude Sonnet 4.6—
Gemini 4 Argon30%
Source
Not directly comparable
Chartography (no tools)
Claude Sonnet 4.6—
Gemini 4 Argon71.6%
Source
Not directly comparable
LVBench
Claude Sonnet 4.6—
Gemini 4 Argon91.7%
Source
Not directly comparable
Blueprint-Bench 2
Claude Sonnet 4.6—
Gemini 4 Argon54.4%
Source
Not directly comparable

Knowledge

GPQA
Claude Sonnet 4.689.9%
Source
Gemini 4 Argon—
Not directly comparable
SuperGPQA
Claude Sonnet 4.695%
Source
Gemini 4 Argon—
Not directly comparable
MMLU-Pro
Claude Sonnet 4.679.2%
Source
Gemini 4 Argon—
Not directly comparable
HLE
Claude Sonnet 4.649%
Source
Gemini 4 Argon—
Not directly comparable
GPQA Diamond (Vals)
Claude Sonnet 4.685.6%
Source
Gemini 4 Argon—
Not directly comparable
MMLU-Pro (Vals)
Claude Sonnet 4.687.3%
Source
Gemini 4 Argon—
Not directly comparable
LABBench2
Claude Sonnet 4.6—
Gemini 4 Argon88.8%
Source
Not directly comparable
Morphology-to-molecule matching
Claude Sonnet 4.6—
Gemini 4 Argon25.2%
Source
Not directly comparable

Instruction following

Gray Swan IPI (15 attempts)
Claude Sonnet 4.6—
Gemini 4 Argon0.7%
Source
Not directly comparable

Math

FrontierMath v2 (Tiers 1-3)
Claude Sonnet 4.6—
Gemini 4 Argon85.965%
Source
Not directly comparable
FrontierMath v2 (Tier 4)
Claude Sonnet 4.6—
Gemini 4 Argon78.049%
Source
Not directly comparable

61 public results · 6 shared

Related comparisons

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Last updated November 13, 2026

Claude Sonnet 4.6 vs Gemini 4 Argon

Decision reading

Which one for your work

Coding work

Agentic work

Long documents

Chat turn cost

Repository review cost

Cache-heavy agent loop cost

Which one for a specific job

Or describe your own job

What is actually comparable

Shape of the matched evidence

Category results, on a stated basis

Agentic

Coding

Reasoning

Knowledge

Multimodal

Multilingual

Instruction following

Math

What each workload costs

Chat turn

Repository review

Cache-heavy agent loop

Your workload

Price against score, among all priced models

Specification differences

Context window

API model ID

Cached-input rate

Documented inputs

Documented outputs

Provider availability

Reasoning profile

Weight access

License

Release date

If you already use one of these models

Questions

Which is better, Claude Sonnet 4.6 or Gemini 4 Argon?

Which is better for coding, Claude Sonnet 4.6 or Gemini 4 Argon?

Which is better for agentic tasks, Claude Sonnet 4.6 or Gemini 4 Argon?

Which costs less, Claude Sonnet 4.6 or Gemini 4 Argon?

Which has the larger context window, Claude Sonnet 4.6 or Gemini 4 Argon?

Benchmark evidence

Agentic

Coding

Reasoning

Multimodal

Knowledge

Instruction following

Math

Related comparisons

Watch Claude Sonnet 4.6 vs Gemini 4 Argon