Head-to-head comparison
Ling 3.0 Flash (InclusionAI) and Ling 3.0 Flash VL (InclusionAI) 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 12 September 2026
As of 12 September 2026, Ling 3.0 Flash VL holds the stronger ModelCap Index position (#56 vs #75); Ling 3.0 Flash is 2.9× cheaper per output token ($0.063/1M vs $0.18/1M); and Ling 3.0 Flash offers the longer context window (262K vs 131K tokens).
Evidence: 4 reported rows against measured corpus ladders (50%); publisher-corpus-prior over 188 held-out anchors (50%); shrunk 3.8 toward the measured corpus · 1 public benchmark observation across 1 board. 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.
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Ling 3.0 Flash VL ranks higher on the ModelCap Index as of 12 September 2026: #56 against #75. 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.
Ling 3.0 Flash is cheaper on output tokens: $0.063/1M against $0.18/1M. Input tokens are $0.021/1M for Ling 3.0 Flash and $0.06/1M for Ling 3.0 Flash VL. 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 $0.07 for Ling 3.0 Flash versus $0.21 for Ling 3.0 Flash VL. Ling 3.0 Flash costs 65.0% less in this scenario. This excludes caching, batch discounts, prompt-length tiers, tool charges and retries; verify the selected endpoint before budgeting.
Ling 3.0 Flash has the larger context window: 262K tokens against 131K.
AA Terminal-Bench 2.1: Ling 3.0 Flash 55.4%, Ling 3.0 Flash VL 64.4% — Ling 3.0 Flash VL leads.
Ling 3.0 Flash: Open weights. Ling 3.0 Flash VL: Open weights. Open weights mean the checkpoint can be downloaded and self-hosted under its licence; API-only models are available solely through hosted endpoints.
ModelCap currently lists 2 API providers for Ling 3.0 Flash and 1 for Ling 3.0 Flash VL, from the OpenRouter catalogue snapshot the site serves; each model page lists the providers and their prices.
Every figure comes from the sealed ModelCap dataset published 12 September 2026; the page re-renders within a minute of each data refresh, and the ModelCap Index positions are the same ones shown on the live rankings.