Head-to-head comparison
GPT-6 Luna (OpenAI) and gpt-oss-20b (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 7 November 2026
As of 7 November 2026, GPT-6 Luna holds the stronger ModelCap Index position (#56 vs #228); gpt-oss-20b is 3.8× cheaper per output token ($0.13/1M vs $0.50/1M); GPT-6 Luna offers the longer context window (1M vs 131K tokens); and gpt-oss-20b ships open weights.
Evidence: 5 public benchmark observations across 5 boards · 2 public benchmark observations across 2 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 Luna ranks higher on the ModelCap Index as of 7 November 2026: #56 against #228. 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 do not overlap, but the aggregate Index does not predict performance on every task; compare the relevant benchmark configurations before choosing.
gpt-oss-20b is cheaper on output tokens: $0.13/1M against $0.50/1M. Input tokens are $0.10/1M for GPT-6 Luna and $0.03/1M for gpt-oss-20b. 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 $0.45 for GPT-6 Luna versus $0.13 for gpt-oss-20b. gpt-oss-20b costs 72.2% less in this scenario. This excludes caching, batch discounts, prompt-length tiers, tool charges and retries; verify the selected endpoint before budgeting.
GPT-6 Luna has the larger context window: 1M tokens against 131K. OpenRouter catalogue or provider-endpoint declaration. Limits can vary by provider and prompt length; a model-wide maximum has not been independently verified.
Arena coding: GPT-6 Luna 1501, gpt-oss-20b 1368 — GPT-6 Luna leads.
GPT-6 Luna: No linked weights. gpt-oss-20b: Open 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 3 API providers for GPT-6 Luna and 10 for gpt-oss-20b, 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 7 November 2026. Publication and page updates happen separately; use the snapshot date shown on the page.