Ling 3.0 Flash Fin vs Llama 4 Scout
Ling 3.0 Flash Fin leads the LLM Stats Score 43.3 to 7.9. Ling 3.0 Flash Fin is 1.5x cheaper per token.
InclusionAI · Meta · Updated for 2026
Which is better?
Ling 3.0 Flash Fin leads the overall LLM Stats Score 43.3 to 7.9, ranking #39 overall.
On price, Ling 3.0 Flash Fin is roughly 1.5x cheaper per token on a blended 3:1 input/output basis, which adds up quickly at production volume.
Llama 4 Scout also accepts a larger context window (10,000,000 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 Ling 3.0 Flash Fin
- overall performance matters — it scores 43.3 and ranks #39 on LLM Stats
- your work emphasizes reasoning — it leads those capability indexes
- cost matters — it's about 1.5x cheaper per token
- you want the most recent training data — it shipped Sep 2026
Choose Llama 4 Scout
- you process long inputs — it offers a 10,000,000 token context window
- you need open weights you can self-host or fine-tune
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 · 12 for Llama 4 Scout
Ling 3.0 Flash Fin and Llama 4 Scoutdon'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 1.3x cheaper than Llama 4 Scout ($0.08/1M tokens).
For output processing, Ling 3.0 Flash Fin ($0.18/1M tokens) is 1.7x cheaper than Llama 4 Scout ($0.30/1M tokens).
In conclusion, Llama 4 Scout is more expensive than Ling 3.0 Flash Fin.*
* Using a 3:1 ratio of input to output tokens
Model Size
Parameter count comparison
Ling 3.0 Flash Fin has 15.0B more parameters than Llama 4 Scout, making it 13.8% larger.
Context Window
Maximum input and output token capacity
Llama 4 Scout accepts 10,000,000 input tokens compared to Ling 3.0 Flash Fin's 262,144 tokens. Llama 4 Scout can generate longer responses up to 10,000,000 tokens, while Ling 3.0 Flash Fin is limited to 262,144 tokens.
Input capabilities
Documented input modalities across available providers
Llama 4 Scout supports multimodal inputs, whereas Ling 3.0 Flash Fin does not.
Llama 4 Scout can handle both text and other forms of data like images, making it suitable for multimodal applications.
Ling 3.0 Flash Fin
Llama 4 Scout
Release Timeline
When each model was launched
Ling 3.0 Flash Fin was released on 2026-09-03, while Llama 4 Scout was released on 2025-04-05.
Ling 3.0 Flash Fin is 17 months newer than Llama 4 Scout.
Sep 3, 2026
5 days ago
1.4yr newerApr 5, 2025
1.4 years ago
Knowledge Cutoff
When training data ends
Neither model specifies a knowledge cutoff date.
Unable to compare the recency of their training data.
Provider Availability
Ling 3.0 Flash Fin is available from DeepInfra. Llama 4 Scout is available from DeepInfra, Lambda, Novita, Groq, Fireworks, Together.
Ling 3.0 Flash Fin
Llama 4 Scout
Outputs Comparison
Judge for yourself.
Run your own prompts against Ling 3.0 Flash Fin and Llama 4 Scout side-by-side, then vote on the output you prefer.
FAQ
Common questions about Ling 3.0 Flash Fin vs Llama 4 Scout.