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Gemini 4 Argon vs GPT-6 Astra

Updated November 13, 2026. Rank says GPT-6 Astra is ahead. Price, access, and your workload can each overturn that. Public scores include evidence status and uncertainty.

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Decision reading

GPT-6 Astra has the higher public score estimate, 85.65 versus 79.03, but the 90% score intervals overlap. Treat that as a lead, not a settled winner. 28 results are shared. Category rows resting on Estimated evidence or different benchmark sets are marked directional and do not name a winner.

Model A
Google logo
Gemini 4 Argon

Google

79.03/100

Supported · Public rank #8

90% interval 75.4–82.7

Model B
OpenAI logo
GPT-6 Astra

OpenAI

85.65/100

Supported · Public rank #4

90% interval 80.3–91.0

API price per 1M tokens

Gemini 4 Argon: $2 input / $10 output

GPT-6 Astra: $10 input / $50 output

Context window

Gemini 4 Argon: 1M

GPT-6 Astra: 1.05M

Released

Gemini 4 Argon: September 30, 2026

GPT-6 Astra: September 3, 2026

Shared results
28
Gemini 4 Argon only
11
GPT-6 Astra only
30
Like-for-like categories
4 / 8
Supported: Gemini 4 Argon and GPT-6 AstraHow 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

    GPT-6 Astra

    GPT-6 Astra has the higher public coding point estimate, 78.7 to 71.8, 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 73.7, 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

    GPT-6 Astra

    GPT-6 Astra 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

  • Cache-heavy agent loop cost

    200K cached + 20K fresh input + 10K 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

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.

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

71.8Gemini 4 Argon78.7GPT-6 Astra

Like-for-like · BenchAlign v5.8

GPT-6 Astra 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 leaderboardShortlist 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.

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

What is actually comparable

Shared results can support a head-to-head reading. Results present for only one model describe coverage, not superiority.

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.

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
Gemini 4 Argon
74.9
Supported · #6/135
GPT-6 Astra
73.7
Supported · #7/135
Basis
BenchAlign v5.8 lane · 13 vs 20 public rows
Reading
Gemini 4 Argon leads · intervals overlap

Coding

Like-for-like
Gemini 4 Argon
71.8
Supported · #9/162
GPT-6 Astra
78.7
Supported · #5/162
Basis
BenchAlign v5.8 lane · 9 vs 10 public rows
Reading
GPT-6 Astra leads · intervals overlap

Reasoning

Like-for-like
Gemini 4 Argon
76.5
Supported · #7/160
GPT-6 Astra
81.1
Supported · #3/160
Basis
BenchAlign v5.8 lane · 7 vs 10 public rows
Reading
GPT-6 Astra leads · intervals overlap

Knowledge

Like-for-like
Gemini 4 Argon
79.2
Supported · #8/180
GPT-6 Astra
85.5
Supported · #4/180
Basis
BenchAlign v5.8 lane · 2 vs 9 public rows
Reading
GPT-6 Astra leads · intervals overlap

Multimodal

Not comparable
Gemini 4 Argon
Not ranked
GPT-6 Astra
79.7
Supported · #3/67
Basis
BenchAlign v5.8 lane · 5 vs 6 public rows
Reading
Not comparable

Multilingual

Not comparable
Gemini 4 Argon
Not ranked
GPT-6 Astra
Not ranked
Basis
Provisional lane · 0 vs 0 weighted rows
Reading
Not comparable

Instruction following

Not comparable
Gemini 4 Argon
Not ranked
GPT-6 Astra
Not ranked
Basis
Provisional lane · 0 vs 0 weighted rows
Reading
Not comparable

Math

Not comparable
Gemini 4 Argon
87.4
Unranked · 2 rankable rows
GPT-6 Astra
93.8
Unranked · 2 rankable rows
Basis
Provisional lane · 2 vs 2 weighted rows
Reading
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

Gemini 4 Argon
$0.007
Fits in one request
GPT-6 Astra
$0.035
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

Gemini 4 Argon
$0.13
Fits in one request
GPT-6 Astra
$0.65
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

Gemini 4 Argon
$0.16
Fits in one request
GPT-6 Astra
$0.9
Fits in one request

Gemini 4 Argon has the lower modeled cost

Costs use the listed standard API rates.

Your workload

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

Gemini 4 Argon
$40.00
per month
GPT-6 Astra
$200.00
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.

Gemini 4 ArgonGPT-6 Astra

20406080100$0.10$0.50$1$5$10$50$100Output price, $ per 1M tokens (log)Overall score
  • 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).
  • 3 cheaper models score at least as high as GPT-6 Astra. The nearest is Claude Fable 5.2 (score 93.7, $40.00 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.

Reasoning profile

Gemini 4 Argon

Reasoning

GPT-6 Astra

Reasoning

Weight access

Gemini 4 Argon

Proprietary

GPT-6 Astra

Proprietary

License

Gemini 4 Argon

Proprietary

GPT-6 Astra

Proprietary

Release date

Gemini 4 Argon

2026-09-30

GPT-6 Astra

2026-09-03

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
GPT-6 Astra has the higher public score estimate, 85.65 versus 79.03, but the 90% score intervals overlap.
Workload cost
Repository review: $0.13 vs $0.65. Cache-heavy agent loop: $0.16 vs $0.9.
Context tradeoff
GPT-6 Astra has the larger documented window (1.05M).
Run the same representative tasks against both endpoints before changing production traffic.

Questions

Which is better, Gemini 4 Argon or GPT-6 Astra?

GPT-6 Astra has the higher public score estimate, 85.65 versus 79.03, but the 90% score intervals overlap. The higher estimate is not a decisive winner because the uncertainty ranges overlap.

Which is better for coding, Gemini 4 Argon or GPT-6 Astra?

GPT-6 Astra has the higher public coding point estimate, 78.7 to 71.8, with Supported evidence for both models. The conditional ranges do not establish rank confidence.

Which is better for agentic tasks, Gemini 4 Argon or GPT-6 Astra?

Gemini 4 Argon has the higher public agentic tasks point estimate, 74.9 to 73.7, with Supported evidence for both models. The conditional ranges do not establish rank confidence.

Which costs less, Gemini 4 Argon or GPT-6 Astra?

For the stated presets, chat costs $0.007 on Gemini 4 Argon and $0.035 on GPT-6 Astra; repository review costs $0.13 and $0.65; the cache-heavy agent loop costs $0.16 and $0.9. Costs use the listed standard API rates.

Which has the larger context window, Gemini 4 Argon or GPT-6 Astra?

GPT-6 Astra has the larger documented context window: 1.05M, compared with 1M.

Benchmark evidence

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

Browse raw public benchmark evidence69 rows

Agentic

  • AutomationBench

    Gemini 4 Argon51.3%
    Source
    GPT-6 Astra41.4%
    Source

    Gemini 4 Argon leads this result

  • Finance Agent v2

    Gemini 4 Argon65.4%
    Source
    GPT-6 Astra—

    Not directly comparable

  • Terminal-Bench 4.0

    Gemini 4 Argon57.40%
    Source
    GPT-6 Astra57.90%
    Source

    GPT-6 Astra leads this result

  • Agents' Last Exam

    Gemini 4 Argon39.5%
    Source
    GPT-6 Astra59.3%
    Source

    GPT-6 Astra leads this result

  • OSWorld 2.0

    Gemini 4 Argon69.2%
    Source
    GPT-6 Astra72.6%
    Source

    GPT-6 Astra leads this result

  • CWE-bench v1

    Shared source
    Gemini 4 Argon68.0%
    GPT-6 Astra68.0%

    Tie

  • Terminal-Bench-Science 0.1 (6x verifier timeout)

    Gemini 4 Argon57.6%
    Source
    GPT-6 Astra—

    Not directly comparable

  • MazeBench

    Gemini 4 Argon12%
    Source
    GPT-6 Astra23%
    Source

    GPT-6 Astra leads this result

  • OSWorld 2.1 Offline

    Gemini 4 Argon74.7%
    Source
    GPT-6 Astra—

    Not directly comparable

  • ExploitGym

    Gemini 4 Argon39.5%
    Source
    GPT-6 Astra42.4%
    Source

    GPT-6 Astra leads this result

  • RoboDojo Sim

    Shared source
    Gemini 4 Argon34.2%
    GPT-6 Astra29.8%

    Gemini 4 Argon leads this result

  • CWE-bench

    Shared source
    Gemini 4 Argon65.0%
    GPT-6 Astra64.2%

    Gemini 4 Argon leads this result

  • Terminal-Bench 2.1 (Vals)

    Gemini 4 Argon57.7%
    Source
    GPT-6 Astra87.3%
    Source

    GPT-6 Astra leads this result

  • Terminal-Bench 4.1

    Gemini 4 Argon—
    GPT-6 Astra60.30%
    Source

    Not directly comparable

  • LifeVal

    Gemini 4 Argon—
    GPT-6 Astra80.6%
    Source

    Not directly comparable

  • BrowseComp

    Gemini 4 Argon—
    GPT-6 Astra91.5%
    Source

    Not directly comparable

  • Terminal-Bench-Science 0.1

    Gemini 4 Argon—
    GPT-6 Astra64.6%
    Source

    Not directly comparable

  • HLE w/ tools

    Gemini 4 Argon—
    GPT-6 Astra57.2%
    Source

    Not directly comparable

  • ApprenticeBench

    Gemini 4 Argon—
    GPT-6 Astra68%
    Source

    Not directly comparable

  • Hermes Index

    Gemini 4 Argon—
    GPT-6 Astra56.3%
    Source

    Not directly comparable

  • Hermes Bench

    Gemini 4 Argon—
    GPT-6 Astra73.7%
    Source

    Not directly comparable

  • OSWorld 2.1

    Gemini 4 Argon—
    GPT-6 Astra75.8%
    Source

    Not directly comparable

  • Remote Labor Index

    Gemini 4 Argon—
    GPT-6 Astra20.8%
    Source

    Not directly comparable

Coding

  • ScarfBench

    Shared source
    Gemini 4 Argon75.2%
    GPT-6 Astra65.4%

    Gemini 4 Argon leads this result

  • DeepSWE

    Gemini 4 Argon77.9%
    Source
    GPT-6 Astra74.1%
    Source

    Gemini 4 Argon leads this result

  • FrontierSWE v2

    Shared source
    Gemini 4 Argon55.0%
    GPT-6 Astra65.5%

    GPT-6 Astra leads this result

  • Vibe Code Bench

    Gemini 4 Argon91.90%
    Source
    GPT-6 Astra—

    Not directly comparable

  • PostTrainBench v1.1

    Gemini 4 Argon45.3%
    Source
    GPT-6 Astra44.3%
    Source

    Gemini 4 Argon leads this result

  • Bug Hunt Bench

    Shared source
    Gemini 4 Argon40.7 fixes
    GPT-6 Astra45.0 fixes

    GPT-6 Astra leads this result

  • FrontierCode 2.0

    Shared source
    Gemini 4 Argon26.3%
    GPT-6 Astra42.8%

    GPT-6 Astra leads this result

  • CursorBench 4.0

    Gemini 4 Argon52.9%
    Source
    GPT-6 Astra—

    Not directly comparable

  • PostTrainBench

    Shared source
    Gemini 4 Argon40.4%
    GPT-6 Astra41.9%

    GPT-6 Astra leads this result

  • FrontierCode 1.1 Main

    Gemini 4 Argon—
    GPT-6 Astra53.3%
    Source

    Not directly comparable

  • FrontierCode 1.1 Extended

    Gemini 4 Argon—
    GPT-6 Astra64.5%
    Source

    Not directly comparable

  • VulcanBench Frontier v4

    Gemini 4 Argon—
    GPT-6 Astra89.3%
    Source

    Not directly comparable

Reasoning

  • STEMBench

    Shared source
    Gemini 4 Argon2.44
    GPT-6 Astra2.81

    GPT-6 Astra leads this result

  • Graphwalks BFS 128K

    Gemini 4 Argon99.7%
    Source
    GPT-6 Astra—

    Not directly comparable

  • GraphWalks BFS 256K–1M

    Gemini 4 Argon84.2%
    Source
    GPT-6 Astra71.8%
    Source

    Gemini 4 Argon leads this result

  • ARC-AGI-1

    Gemini 4 Argon98.50%
    Source
    GPT-6 Astra97.50%
    Source

    Gemini 4 Argon leads this result

  • ARC-AGI-2

    Gemini 4 Argon91.3%
    Source
    GPT-6 Astra95%
    Source

    GPT-6 Astra leads this result

  • ARC-AGI-3

    Gemini 4 Argon46.3%
    Source
    GPT-6 Astra62.7%
    Source

    GPT-6 Astra leads this result

  • ARC-AGI-3 Provider Adapter

    Gemini 4 Argon97.30%
    Source
    GPT-6 Astra98.55%
    Source

    GPT-6 Astra leads this result

  • BioBasicsBench

    Gemini 4 Argon—
    GPT-6 Astra67.0%
    Source

    Not directly comparable

  • GeneBench-Pro

    Gemini 4 Argon—
    GPT-6 Astra37.8%
    Source

    Not directly comparable

  • MRCR v2 256K-512K

    Gemini 4 Argon—
    GPT-6 Astra100.0%
    Source

    Not directly comparable

  • MRCR v2 512K-1M

    Gemini 4 Argon—
    GPT-6 Astra96.3%
    Source

    Not directly comparable

Multimodal

  • ParseBench-2

    Gemini 4 Argon84.20%
    Source
    GPT-6 Astra—

    Not directly comparable

  • ExtractBench Pro

    Shared source
    Gemini 4 Argon30%
    GPT-6 Astra58%

    GPT-6 Astra leads this result

  • Chartography (no tools)

    Gemini 4 Argon71.6%
    Source
    GPT-6 Astra—

    Not directly comparable

  • LVBench

    Gemini 4 Argon91.7%
    Source
    GPT-6 Astra—

    Not directly comparable

  • Blueprint-Bench 2

    Gemini 4 Argon54.4%
    Source
    GPT-6 Astra—

    Not directly comparable

  • ExtractBench (LlamaIndex)

    Gemini 4 Argon—
    GPT-6 Astra91.91%
    Source

    Not directly comparable

  • ParseBench-1

    Gemini 4 Argon—
    GPT-6 Astra69.81%
    Source

    Not directly comparable

  • ScreenSpot Pro

    Gemini 4 Argon—
    GPT-6 Astra92.7%
    Source

    Not directly comparable

  • BenchCAD Vision2Code (tools)

    Gemini 4 Argon—
    GPT-6 Astra0.959
    Source

    Not directly comparable

  • Biomedical image analysis

    Gemini 4 Argon—
    GPT-6 Astra77.5%
    Source

    Not directly comparable

Knowledge

  • LABBench2

    Gemini 4 Argon88.8%
    Source
    GPT-6 Astra—

    Not directly comparable

  • Morphology-to-molecule matching

    Shared source
    Gemini 4 Argon25.2%
    GPT-6 Astra22.8%

    Gemini 4 Argon leads this result

  • GPQA

    Gemini 4 Argon—
    GPT-6 Astra96%
    Source

    Not directly comparable

  • GPQA-D

    Gemini 4 Argon—
    GPT-6 Astra96.0%
    Source

    Not directly comparable

  • HealthBench (raw)

    Gemini 4 Argon—
    GPT-6 Astra56.9%
    Source

    Not directly comparable

  • HealthBench (length-adjusted)

    Gemini 4 Argon—
    GPT-6 Astra58.3%
    Source

    Not directly comparable

  • HealthBench Professional

    Gemini 4 Argon—
    GPT-6 Astra64.7%
    Source

    Not directly comparable

  • HealthBench Professional (raw)

    Gemini 4 Argon—
    GPT-6 Astra68.2%
    Source

    Not directly comparable

  • HealthBench Hard

    Gemini 4 Argon—
    GPT-6 Astra36.6%
    Source

    Not directly comparable

  • PhysicianBench

    Gemini 4 Argon—
    GPT-6 Astra48.0%
    Source

    Not directly comparable

Instruction following

  • Gray Swan IPI (15 attempts)

    Shared source
    Gemini 4 Argon0.7%
    GPT-6 Astra8.5%

    Gemini 4 Argon leads this result

Math

  • FrontierMath v2 (Tiers 1-3)

    Shared source
    Gemini 4 Argon85.965%
    GPT-6 Astra93.684%

    GPT-6 Astra leads this result

  • FrontierMath v2 (Tier 4)

    Gemini 4 Argon78.049%
    Source
    GPT-6 Astra97.600%
    Source

    GPT-6 Astra leads this result

69 public results · 28 shared

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Last updated November 13, 2026