GLM-5.3-Flash vs Llama 3.2 11B Instruct
Comparing GLM-5.3-Flash and Llama 3.2 11B Instruct across benchmarks, pricing, and capabilities.
Zhipu AI · Meta · Updated for 2026
Which is better?
GLM-5.3-Flash and Llama 3.2 11B Instruct trade strengths across price, capabilities, and technical limits. The better choice depends on the workload.
On price, Llama 3.2 11B Instruct is roughly 4.7x 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 benchmark, 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 want the most recent training data — it shipped Aug 2026
Choose Llama 3.2 11B Instruct
- cost matters — it's about 4.7x cheaper per token
At a glance
The differences that matter most.
Performance Benchmarks
Comparative analysis across standard metrics
GLM-5.3-Flash and Llama 3.2 11B Instructdon't have any common benchmark datasets to compare. They may have been evaluated on different testing suites.
Arena Performance
Playground indexes and blind preference scores
Pricing Analysis
Price comparison per million tokens
For input processing, GLM-5.3-Flash ($0.15/1M tokens) is 3.0x more expensive than Llama 3.2 11B Instruct ($0.05/1M tokens).
For output processing, GLM-5.3-Flash ($0.50/1M tokens) is 10.0x more expensive than Llama 3.2 11B Instruct ($0.05/1M tokens).
In conclusion, GLM-5.3-Flash is more expensive than Llama 3.2 11B Instruct.*
* Using a 3:1 ratio of input to output tokens
Model Size
Parameter count comparison
GLM-5.3-Flash has 309.4B more parameters than Llama 3.2 11B Instruct, making it 2918.9% larger.
Context Window
Maximum input and output token capacity
GLM-5.3-Flash accepts 1,048,576 input tokens compared to Llama 3.2 11B Instruct's 128,000 tokens. GLM-5.3-Flash can generate longer responses up to 131,072 tokens, while Llama 3.2 11B Instruct is limited to 128,000 tokens.
Input Capabilities
Supported data types and modalities
Both GLM-5.3-Flash and Llama 3.2 11B Instruct support multimodal inputs.
They are both capable of processing various types of data, offering versatility in application.
GLM-5.3-Flash
Llama 3.2 11B Instruct
License
Usage and distribution terms
GLM-5.3-Flash is licensed under MIT, while Llama 3.2 11B 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 11B Instruct was released on 2024-09-25.
GLM-5.3-Flash is 23 months newer than Llama 3.2 11B Instruct.
Aug 26, 2026
1 days ago
1.9yr newerSep 25, 2024
1.9 years ago
Knowledge Cutoff
When training data ends
Llama 3.2 11B Instruct has a documented knowledge cutoff of 2023-12-31, while GLM-5.3-Flash's cutoff date is not specified.
We can confirm Llama 3.2 11B Instruct's training data extends to 2023-12-31, but cannot make a direct comparison without GLM-5.3-Flash's cutoff date.
—
Dec 2023
Provider Availability
GLM-5.3-Flash is available from DeepInfra, Novita, ZAI. Llama 3.2 11B Instruct is available from DeepInfra, Sambanova, Bedrock, Groq, Together, Fireworks.
GLM-5.3-Flash
Llama 3.2 11B Instruct
Outputs Comparison
Judge for yourself.
Run your own prompts against GLM-5.3-Flash and Llama 3.2 11B Instruct side-by-side, then vote on the output you prefer.
FAQ
Common questions about GLM-5.3-Flash vs Llama 3.2 11B Instruct.