Ling 3.0 Flash Fin vs Qwen3 Max Thinking
Ling 3.0 Flash Fin leads the LLM Stats Score 43.3 to 33.0. Ling 3.0 Flash Fin is 26.7x 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 33.0, ranking #39 overall.
On price, Ling 3.0 Flash Fin is roughly 26.7x 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 26.7x 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 Max Thinking
- you want predictable pricing at $1.20/M input and $6.00/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 · 34 for Qwen3 Max Thinking
Ling 3.0 Flash Fin and Qwen3 Max 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 20.0x cheaper than Qwen3 Max Thinking ($1.20/1M tokens).
For output processing, Ling 3.0 Flash Fin ($0.18/1M tokens) is 33.3x cheaper than Qwen3 Max Thinking ($6.00/1M tokens).
In conclusion, Qwen3 Max 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
Qwen3 Max Thinking has 876.0B more parameters than Ling 3.0 Flash Fin, making it 706.5% larger.
Context Window
Maximum input and output token capacity
Ling 3.0 Flash Fin accepts 262,144 input tokens compared to Qwen3 Max Thinking's 256,000 tokens. Ling 3.0 Flash Fin can generate longer responses up to 262,144 tokens, while Qwen3 Max Thinking is limited to 256,000 tokens.
Release Timeline
When each model was launched
Ling 3.0 Flash Fin was released on 2026-09-03, while Qwen3 Max Thinking was released on 2026-02-13.
Ling 3.0 Flash Fin is 7 months newer than Qwen3 Max Thinking.
Sep 3, 2026
5 days ago
6mo newerFeb 13, 2026
6 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 Max Thinking is available from DeepInfra.
Ling 3.0 Flash Fin
Qwen3 Max Thinking
Outputs Comparison
Judge for yourself.
Run your own prompts against Ling 3.0 Flash Fin and Qwen3 Max Thinking side-by-side, then vote on the output you prefer.
FAQ
Common questions about Ling 3.0 Flash Fin vs Qwen3 Max Thinking.