Ling 3.0 Flash Fin (InclusionAI) and GPT-5.4 Nano (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 15 September 2026
As of 15 September 2026, Ling 3.0 Flash Fin holds the stronger ModelCap Index position (#79 vs #80); Ling 3.0 Flash Fin is 6.9× cheaper per output token ($0.18/1M vs $1.25/1M); GPT-5.4 Nano offers the longer context window (400K vs 262K tokens); and Ling 3.0 Flash Fin ships open weights.
Evidence: finetune of inclusionai/ling-3.0-flash · finetune (100%) · 4 public benchmark observations across 4 boards. Prices are the lowest listed API offer per million tokens observed on the OpenRouter catalogue.
Benchmark scores: Ling 3.0 Flash Fin vs GPT-5.4 Nano
Public benchmark boards where Ling 3.0 Flash Fin or GPT-5.4 Nano has a published result
Ling 3.0 Flash Fin vs GPT-5.4 Nano: common questions
Is Ling 3.0 Flash Fin better than GPT-5.4 Nano?
Ling 3.0 Flash Fin ranks higher on the ModelCap Index as of 15 September 2026: #79 against #80. 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.
Is Ling 3.0 Flash Fin cheaper than GPT-5.4 Nano?
Ling 3.0 Flash Fin is cheaper on output tokens: $0.18/1M against $1.25/1M. Input tokens are $0.06/1M for Ling 3.0 Flash Fin and $0.20/1M for GPT-5.4 Nano. 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 $0.21 for Ling 3.0 Flash Fin versus $1.02 for GPT-5.4 Nano. Ling 3.0 Flash Fin costs 79.5% less in this scenario. This excludes caching, batch discounts, prompt-length tiers, tool charges and retries; verify the selected endpoint before budgeting.
Which has the bigger context window, Ling 3.0 Flash Fin or GPT-5.4 Nano?
GPT-5.4 Nano has the larger context window: 400K tokens against 262K.
Which is better for coding, Ling 3.0 Flash Fin or GPT-5.4 Nano?
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.
Are Ling 3.0 Flash Fin and GPT-5.4 Nano open-weight models?
Ling 3.0 Flash Fin: Open weights. GPT-5.4 Nano: API only. Open weights mean the checkpoint can be downloaded and self-hosted under its licence; API-only models are available solely through hosted endpoints.
Where can I run Ling 3.0 Flash Fin and GPT-5.4 Nano?
ModelCap currently lists 1 API provider for Ling 3.0 Flash Fin and 2 for GPT-5.4 Nano, from the OpenRouter catalogue snapshot the site serves; each model page lists the providers and their prices.
How current is this Ling 3.0 Flash Fin vs GPT-5.4 Nano comparison?
Every figure comes from the sealed ModelCap dataset published 15 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.