GLM-5.3-Flash vs Llama 3.1 8B Instruct
Comparing GLM-5.3-Flash and Llama 3.1 8B Instruct across benchmarks, pricing, and capabilities.
Zhipu AI · Meta · Updated for 2026
Which is better?
GLM-5.3-Flash and Llama 3.1 8B Instruct trade strengths across price, capabilities, and technical limits. The better choice depends on the workload.
On price, Llama 3.1 8B Instruct is roughly 7.9x 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 (1,000,000 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 1,000,000 token context window
- you want the most recent training data — it shipped Aug 2026
Choose Llama 3.1 8B Instruct
- cost matters — it's about 7.9x cheaper per token
At a glance
The differences that matter most.
Performance Benchmarks
Comparative analysis across standard metrics
GLM-5.3-Flash and Llama 3.1 8B 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 5.0x more expensive than Llama 3.1 8B Instruct ($0.03/1M tokens).
For output processing, GLM-5.3-Flash ($0.50/1M tokens) is 16.7x more expensive than Llama 3.1 8B Instruct ($0.03/1M tokens).
In conclusion, GLM-5.3-Flash is more expensive than Llama 3.1 8B Instruct.*
* Using a 3:1 ratio of input to output tokens
Model Size
Parameter count comparison
GLM-5.3-Flash has 312.0B more parameters than Llama 3.1 8B Instruct, making it 3900.0% larger.
Context Window
Maximum input and output token capacity
GLM-5.3-Flash accepts 1,000,000 input tokens compared to Llama 3.1 8B Instruct's 131,072 tokens. Both models can generate responses up to 131,072 tokens.
Input Capabilities
Supported data types and modalities
GLM-5.3-Flash supports multimodal inputs, whereas Llama 3.1 8B 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 3.1 8B Instruct
License
Usage and distribution terms
GLM-5.3-Flash is licensed under MIT, while Llama 3.1 8B Instruct uses Llama 3.1 Community License.
License differences may affect how you can use these models in commercial or open-source projects.
MIT
Open weights
Llama 3.1 Community License
Open weights
Release Timeline
When each model was launched
GLM-5.3-Flash was released on 2026-08-26, while Llama 3.1 8B Instruct was released on 2024-07-23.
GLM-5.3-Flash is 25 months newer than Llama 3.1 8B Instruct.
Aug 26, 2026
0 days ago
2.1yr newerJul 23, 2024
2.1 years ago
Knowledge Cutoff
When training data ends
Llama 3.1 8B 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 3.1 8B 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 ZAI. Llama 3.1 8B Instruct is available from Lambda, DeepInfra, Groq, Sambanova, Cerebras, Hyperbolic, Together, Fireworks, Bedrock.
GLM-5.3-Flash
Llama 3.1 8B Instruct
Outputs Comparison
Judge for yourself.
Run your own prompts against GLM-5.3-Flash and Llama 3.1 8B Instruct side-by-side, then vote on the output you prefer.
FAQ
Common questions about GLM-5.3-Flash vs Llama 3.1 8B Instruct.