GLM-5.3-Flash vs Ling 3.0 Flash Fin
GLM-5.3-Flash and Ling 3.0 Flash Fin are closely matched at 50.2 and 43.0 on the LLM Stats Score. Ling 3.0 Flash Fin is 2.6x cheaper per token.
Zhipu AI · InclusionAI · Updated for 2026
Which is better?
GLM-5.3-Flash and Ling 3.0 Flash Fin are closely matched on the overall LLM Stats Score at 50.2 and 43.0.
On price, Ling 3.0 Flash Fin is roughly 2.6x cheaper per token on a blended 3:1 input/output basis, which adds up quickly at production volume.
GLM-5.3-Flash also accepts a larger context window (1,048,576 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 GLM-5.3-Flash
- you process long inputs — it offers a 1,048,576 token context window
- you need open weights you can self-host or fine-tune
Choose Ling 3.0 Flash Fin
- cost matters — it's about 2.6x 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 GLM-5.3-Flash · 6 for Ling 3.0 Flash Fin
GLM-5.3-Flash and Ling 3.0 Flash Findon'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, GLM-5.3-Flash ($0.15/1M tokens) is 2.5x more expensive than Ling 3.0 Flash Fin ($0.06/1M tokens).
For output processing, GLM-5.3-Flash ($0.50/1M tokens) is 2.8x more expensive than Ling 3.0 Flash Fin ($0.18/1M tokens).
In conclusion, GLM-5.3-Flash is more expensive than Ling 3.0 Flash Fin.*
* Using a 3:1 ratio of input to output tokens
Model Size
Parameter count comparison
GLM-5.3-Flash has 196.0B more parameters than Ling 3.0 Flash Fin, making it 158.1% larger.
Context Window
Maximum input and output token capacity
GLM-5.3-Flash accepts 1,048,576 input tokens compared to Ling 3.0 Flash Fin's 262,144 tokens. GLM-5.3-Flash can generate longer responses up to 1,048,576 tokens, while Ling 3.0 Flash Fin is limited to 262,144 tokens.
Input capabilities
Documented input modalities across available providers
GLM-5.3-Flash supports multimodal inputs, whereas Ling 3.0 Flash Fin does not.
GLM-5.3-Flash can handle both text and other forms of data like images, making it suitable for multimodal applications.
GLM-5.3-Flash
Ling 3.0 Flash Fin
Release Timeline
When each model was launched
GLM-5.3-Flash was released on 2026-08-26, while Ling 3.0 Flash Fin was released on 2026-09-03.
Ling 3.0 Flash Fin is 0 month newer than GLM-5.3-Flash.
Aug 26, 2026
3 weeks ago
Sep 3, 2026
2 weeks ago
1w newerKnowledge Cutoff
When training data ends
Neither model specifies a knowledge cutoff date.
Unable to compare the recency of their training data.
Provider Availability
GLM-5.3-Flash is available from DeepInfra, FriendliAI, Novita, ZAI. Ling 3.0 Flash Fin is available from DeepInfra.
GLM-5.3-Flash
Ling 3.0 Flash Fin
Outputs Comparison
Judge for yourself.
Run your own prompts against GLM-5.3-Flash and Ling 3.0 Flash Fin side-by-side, then vote on the output you prefer.
FAQ
Common questions about GLM-5.3-Flash vs Ling 3.0 Flash Fin.