Ling 3.0 Flash Fin vs o4-mini
Ling 3.0 Flash Fin leads the LLM Stats Score 43.2 to 27.5. Ling 3.0 Flash Fin is 21.4x cheaper per token.
InclusionAI · OpenAI · Updated for 2026
Which is better?
Ling 3.0 Flash Fin leads the overall LLM Stats Score 43.2 to 27.5, ranking #41 overall.
On price, Ling 3.0 Flash Fin is roughly 21.4x cheaper per token on a blended 3:1 input/output basis, which adds up quickly at production volume.
Ling 3.0 Flash Fin also accepts a larger context window (262,144 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 Ling 3.0 Flash Fin
- overall performance matters — it scores 43.2 and ranks #41 on LLM Stats
- your work emphasizes reasoning and agents — it leads those capability indexes
- cost matters — it's about 21.4x cheaper per token
- you process long inputs — it offers a 262,144 token context window
- you want the most recent training data — it shipped Sep 2026
Choose o4-mini
- you want predictable pricing at $1.10/M input and $4.40/M output
At a glance
The differences that matter most.
Capability indexes
Additional strengths measured across groups of related public benchmarks
Individual benchmarks
6 reported for Ling 3.0 Flash Fin · 14 for o4-mini
Ling 3.0 Flash Fin and o4-minidon't have any common benchmark datasets to compare. They may have been evaluated on different testing suites.
Human preference
Blind head-to-head votes and playground preference scores
Pricing Analysis
Price comparison per million tokens
For input processing, Ling 3.0 Flash Fin ($0.06/1M tokens) is 18.3x cheaper than o4-mini ($1.10/1M tokens).
For output processing, Ling 3.0 Flash Fin ($0.18/1M tokens) is 24.4x cheaper than o4-mini ($4.40/1M tokens).
In conclusion, o4-mini 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
Ling 3.0 Flash Fin accepts 262,144 input tokens compared to o4-mini's 200,000 tokens. Ling 3.0 Flash Fin can generate longer responses up to 262,144 tokens, while o4-mini is limited to 100,000 tokens.
Input capabilities
Documented input modalities across available providers
o4-mini supports multimodal inputs, whereas Ling 3.0 Flash Fin does not.
o4-mini can handle both text and other forms of data like images, making it suitable for multimodal applications.
Ling 3.0 Flash Fin
o4-mini
Release Timeline
When each model was launched
Ling 3.0 Flash Fin was released on 2026-09-03, while o4-mini was released on 2025-04-16.
Ling 3.0 Flash Fin is 17 months newer than o4-mini.
Sep 3, 2026
1 weeks ago
1.4yr newerApr 16, 2025
1.4 years ago
Knowledge Cutoff
When training data ends
o4-mini has a documented knowledge cutoff of 2024-05-31, while Ling 3.0 Flash Fin's cutoff date is not specified.
We can confirm o4-mini's training data extends to 2024-05-31, but cannot make a direct comparison without Ling 3.0 Flash Fin's cutoff date.
—
May 2024
Provider Availability
Ling 3.0 Flash Fin is available from DeepInfra. o4-mini is available from OpenAI.
Ling 3.0 Flash Fin
o4-mini
Outputs Comparison
Judge for yourself.
Run your own prompts against Ling 3.0 Flash Fin and o4-mini side-by-side, then vote on the output you prefer.
FAQ
Common questions about Ling 3.0 Flash Fin vs o4-mini.