GLM-5.3-Flash vs Llama 3.2 3B Instruct
GLM-5.3-Flash leads the LLM Stats Score 51.6 to -5.5. Llama 3.2 3B Instruct is 19.0x cheaper per token.
Zhipu AI · Meta · Updated for 2026
Which is better?
GLM-5.3-Flash leads the overall LLM Stats Score 51.6 to -5.5, ranking #11 overall.
On price, Llama 3.2 3B Instruct is roughly 19.0x 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
- overall performance matters — it scores 51.6 and ranks #11 on LLM Stats
- your work emphasizes reasoning — it leads those capability indexes
- you process long inputs — it offers a 1,048,576 token context window
- you want the most recent training data — it shipped Aug 2026
Choose Llama 3.2 3B Instruct
- cost matters — it's about 19.0x cheaper per token
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 · 15 for Llama 3.2 3B Instruct
GLM-5.3-Flash and Llama 3.2 3B Instructdon'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 15.0x more expensive than Llama 3.2 3B Instruct ($0.01/1M tokens).
For output processing, GLM-5.3-Flash ($0.50/1M tokens) is 25.0x more expensive than Llama 3.2 3B Instruct ($0.02/1M tokens).
In conclusion, GLM-5.3-Flash is more expensive than Llama 3.2 3B Instruct.*
* Using a 3:1 ratio of input to output tokens
Model Size
Parameter count comparison
GLM-5.3-Flash has 316.8B more parameters than Llama 3.2 3B Instruct, making it 9868.8% larger.
Context Window
Maximum input and output token capacity
GLM-5.3-Flash accepts 1,048,576 input tokens compared to Llama 3.2 3B Instruct's 128,000 tokens. GLM-5.3-Flash can generate longer responses up to 131,072 tokens, while Llama 3.2 3B Instruct is limited to 128,000 tokens.
Input capabilities
Documented input modalities across available providers
GLM-5.3-Flash supports multimodal inputs, whereas Llama 3.2 3B Instruct 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
Llama 3.2 3B Instruct
License
Usage and distribution terms
GLM-5.3-Flash is licensed under MIT, while Llama 3.2 3B Instruct uses Llama 3.2 Community License.
License differences may affect how you can use these models in commercial or open-source projects.
MIT
Open weights
Llama 3.2 Community License
Open weights
Release Timeline
When each model was launched
GLM-5.3-Flash was released on 2026-08-26, while Llama 3.2 3B Instruct was released on 2024-09-25.
GLM-5.3-Flash is 23 months newer than Llama 3.2 3B Instruct.
Aug 26, 2026
2 days ago
1.9yr newerSep 25, 2024
1.9 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
GLM-5.3-Flash is available from DeepInfra, Novita, ZAI. Llama 3.2 3B Instruct is available from DeepInfra.
GLM-5.3-Flash
Llama 3.2 3B Instruct
Outputs Comparison
Judge for yourself.
Run your own prompts against GLM-5.3-Flash and Llama 3.2 3B Instruct side-by-side, then vote on the output you prefer.
FAQ
Common questions about GLM-5.3-Flash vs Llama 3.2 3B Instruct.