Head-to-head comparison
Muse Wonder (Meta) and GPT-6.1 Terra (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 6 November 2026
As of 6 November 2026, Muse Wonder holds the stronger ModelCap Index position (#4 vs #29); and GPT-6.1 Terra is 4× cheaper per output token ($5.00/1M vs $20.00/1M).
Evidence: 3 public benchmark observations across 3 boards · 1 reported rows against measured corpus ladders (21%); publisher-corpus-prior over 210 held-out anchors (14%); opens above measured predecessor openai/gpt-5.6-terra on same-family ordering evidence (53%); 1 specialist-board observation at 2.5% support (12%); shrunk 3.5 toward the measured corpus. 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.
Muse Wonder ranks higher on the ModelCap Index as of 6 November 2026: #4 against #29. 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.
GPT-6.1 Terra is cheaper on output tokens: $5.00/1M against $20.00/1M. Input tokens are $4.00/1M for Muse Wonder and $1.00/1M for GPT-6.1 Terra. 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 $18.00 for Muse Wonder versus $4.50 for GPT-6.1 Terra. GPT-6.1 Terra costs 75.0% 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.
Muse Wonder: No linked weights. GPT-6.1 Terra: 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 1 API provider for Muse Wonder and 3 for GPT-6.1 Terra, 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 6 November 2026. Publication and page updates happen separately; use the snapshot date shown on the page.