Ling 3.0 Flash Fin vs Qwen3 VL 30B A3B Thinking
Ling 3.0 Flash Fin leads the LLM Stats Score 43.3 to 18.3. Ling 3.0 Flash Fin is 4.4x cheaper per token.
InclusionAI · Alibaba Cloud / Qwen Team · Updated for 2026
Which is better?
Ling 3.0 Flash Fin leads the overall LLM Stats Score 43.3 to 18.3, ranking #39 overall.
On price, Ling 3.0 Flash Fin is roughly 4.4x 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 43.3 and ranks #39 on LLM Stats
- your work emphasizes reasoning and agents — it leads those capability indexes
- cost matters — it's about 4.4x 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 Qwen3 VL 30B A3B Thinking
- 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 · 50 for Qwen3 VL 30B A3B Thinking
Ling 3.0 Flash Fin and Qwen3 VL 30B A3B Thinkingdon'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 3.3x cheaper than Qwen3 VL 30B A3B Thinking ($0.20/1M tokens).
For output processing, Ling 3.0 Flash Fin ($0.18/1M tokens) is 5.5x cheaper than Qwen3 VL 30B A3B Thinking ($0.99/1M tokens).
In conclusion, Qwen3 VL 30B A3B Thinking 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 93.0B more parameters than Qwen3 VL 30B A3B Thinking, making it 300.0% larger.
Context Window
Maximum input and output token capacity
Ling 3.0 Flash Fin accepts 262,144 input tokens compared to Qwen3 VL 30B A3B Thinking's 131,072 tokens. Ling 3.0 Flash Fin can generate longer responses up to 262,144 tokens, while Qwen3 VL 30B A3B Thinking is limited to 32,768 tokens.
Input capabilities
Documented input modalities across available providers
Qwen3 VL 30B A3B Thinking supports multimodal inputs, whereas Ling 3.0 Flash Fin does not.
Qwen3 VL 30B A3B Thinking can handle both text and other forms of data like images, making it suitable for multimodal applications.
Ling 3.0 Flash Fin
Qwen3 VL 30B A3B Thinking
Release Timeline
When each model was launched
Ling 3.0 Flash Fin was released on 2026-09-03, while Qwen3 VL 30B A3B Thinking was released on 2025-09-22.
Ling 3.0 Flash Fin is 12 months newer than Qwen3 VL 30B A3B Thinking.
Sep 3, 2026
5 days ago
11mo newerSep 22, 2025
11 months 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. Qwen3 VL 30B A3B Thinking is available from Novita, DeepInfra.
Ling 3.0 Flash Fin
Qwen3 VL 30B A3B Thinking
Outputs Comparison
Judge for yourself.
Run your own prompts against Ling 3.0 Flash Fin and Qwen3 VL 30B A3B Thinking side-by-side, then vote on the output you prefer.
FAQ
Common questions about Ling 3.0 Flash Fin vs Qwen3 VL 30B A3B Thinking.