GPT-5.4 nano vs Ling 3.0 Flash Fin
Ling 3.0 Flash Fin leads the LLM Stats Score 43.0 to 26.6. Ling 3.0 Flash Fin is 5.1x cheaper per token.
OpenAI · InclusionAI · Updated for 2026
Which is better?
Ling 3.0 Flash Fin leads the overall LLM Stats Score 43.0 to 26.6, ranking #44 overall.
In the 1 individual benchmarks reported for both models, Ling 3.0 Flash Fin wins 1; this is a narrower head-to-head signal than the composite indexes.
On price, Ling 3.0 Flash Fin is roughly 5.1x cheaper per token on a blended 3:1 input/output basis, which adds up quickly at production volume.
GPT-5.4 nano also accepts a larger context window (400,000 input tokens), making it the stronger choice for long documents and large codebases.
Based on current LLM Stats indexes, shared benchmarks, pricing, and model metadata for 2026.
Choose GPT-5.4 nano
- you process long inputs — it offers a 400,000 token context window
Choose Ling 3.0 Flash Fin
- overall performance matters — it scores 43.0 and ranks #44 on LLM Stats
- your work emphasizes reasoning and agents — it leads those capability indexes
- you value its reported benchmark strengths — it wins 1 of 1 exact shared results
- cost matters — it's about 5.1x cheaper per token
- you want the most recent training data — it shipped Sep 2026
At a glance
The differences that matter most.
Capability indexes
Additional strengths measured across groups of related public benchmarks
Individual benchmarks
15 reported for GPT-5.4 nano · 6 for Ling 3.0 Flash Fin
GPT-5.4 nano outperforms in 0 benchmarks, while Ling 3.0 Flash Fin is better at 1 benchmark (Finance Agent v2).
Ling 3.0 Flash Fin significantly outperforms across most benchmarks.
Human preference
Blind head-to-head votes and playground preference scores
Pricing Analysis
Price comparison per million tokens
For input processing, GPT-5.4 nano ($0.20/1M tokens) is 3.3x more expensive than Ling 3.0 Flash Fin ($0.06/1M tokens).
For output processing, GPT-5.4 nano ($1.25/1M tokens) is 6.9x more expensive than Ling 3.0 Flash Fin ($0.18/1M tokens).
In conclusion, GPT-5.4 nano is more expensive than Ling 3.0 Flash Fin.*
* Using a 3:1 ratio of input to output tokens
Context Window
Maximum input and output token capacity
GPT-5.4 nano accepts 400,000 input tokens compared to Ling 3.0 Flash Fin's 262,144 tokens. Ling 3.0 Flash Fin can generate longer responses up to 262,144 tokens, while GPT-5.4 nano is limited to 128,000 tokens.
Input capabilities
Documented input modalities across available providers
GPT-5.4 nano supports multimodal inputs, whereas Ling 3.0 Flash Fin does not.
GPT-5.4 nano can handle both text and other forms of data like images, making it suitable for multimodal applications.
GPT-5.4 nano
Ling 3.0 Flash Fin
Release Timeline
When each model was launched
GPT-5.4 nano was released on 2026-03-17, while Ling 3.0 Flash Fin was released on 2026-09-03.
Ling 3.0 Flash Fin is 6 months newer than GPT-5.4 nano.
Mar 17, 2026
6 months ago
Sep 3, 2026
2 weeks ago
5mo newerKnowledge Cutoff
When training data ends
GPT-5.4 nano has a documented knowledge cutoff of 2025-08-31, while Ling 3.0 Flash Fin's cutoff date is not specified.
We can confirm GPT-5.4 nano's training data extends to 2025-08-31, but cannot make a direct comparison without Ling 3.0 Flash Fin's cutoff date.
Aug 2025
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Provider Availability
GPT-5.4 nano is available from OpenAI. Ling 3.0 Flash Fin is available from DeepInfra.
GPT-5.4 nano
Ling 3.0 Flash Fin
Outputs Comparison
Judge for yourself.
Run your own prompts against GPT-5.4 nano and Ling 3.0 Flash Fin side-by-side, then vote on the output you prefer.
FAQ
Common questions about GPT-5.4 nano vs Ling 3.0 Flash Fin.