Head-to-head comparison
Gemini 4 Argon (Google) and GPT-6 Astra (OpenAI) compared on the ModelCap Index, API price, context window, provider availability, weight access and every public benchmark board they share. Figures are the same ones shown on the live rankings; nothing here is a hidden score.
Snapshot as of 13 October 2026
As of 13 October 2026, GPT-6 Astra holds the stronger ModelCap Index position (#13 vs #33); and Gemini 4 Argon is 5× cheaper per output token ($10.00/1M vs $50.00/1M).
Evidence: 1 reported rows against measured corpus ladders (72%); publisher-corpus-prior over 211 held-out anchors (28%); shrunk 3.7 toward the measured corpus · 5 public benchmark observations across 5 boards. Prices are the lowest listed API offer per million tokens observed on the OpenRouter catalogue.
Scores are the sources' own published figures for each model's best evaluated configuration; ModelCap never re-runs a benchmark.
Want a different pairing? Open the interactive comparison tool to swap either model for any current ranked language model.
GPT-6 Astra ranks higher on the ModelCap Index as of 13 October 2026: #13 against #33. That is a capability ranking built from public benchmark evidence with published uncertainty; whether it is "better" for you also depends on price, context and where you can run it. Their published uncertainty intervals overlap, so the rank difference alone does not establish a reliable capability advantage for your workload.
Gemini 4 Argon is cheaper on output tokens: $10.00/1M against $50.00/1M. Input tokens are $2.00/1M for Gemini 4 Argon and $10.00/1M for GPT-6 Astra. Prices are the lowest listed API offer ModelCap observed, in USD per million tokens. For 1,000 requests with 2,000 input and 500 output tokens each (2M input + 0.5M output), the listed-rate estimate is $9.00 for Gemini 4 Argon versus $45.00 for GPT-6 Astra. Gemini 4 Argon costs 80.0% less in this scenario. This excludes caching, batch discounts, prompt-length tiers, tool charges and retries; verify the selected endpoint before budgeting.
Both publish a 1M-token context window. OpenRouter catalogue or provider-endpoint declaration. Limits can vary by provider and prompt length; a model-wide maximum has not been independently verified.
The two models do not share a coding benchmark board on ModelCap yet, so no head-to-head coding score is published; the ModelCap Index position is the closest overall signal.
Gemini 4 Argon: No linked weights. GPT-6 Astra: No linked weights. Open weights mean the checkpoint can be downloaded and self-hosted under its licence. A missing weight link does not identify every API or chat product that offers a model.
ModelCap currently lists 2 API providers for Gemini 4 Argon and 3 for GPT-6 Astra, from the OpenRouter catalogue snapshot the site serves; each model page lists the providers and their prices.
Every figure and ModelCap Index position comes from the same published snapshot dated 13 October 2026. Publication and page updates happen separately; use the snapshot date shown on the page.