GLM-5.3-Flash vs Llama 4 Scout
Comparing GLM-5.3-Flash and Llama 4 Scout across benchmarks, pricing, and capabilities.
Zhipu AI · Meta · Updated for 2026
Which is better?
GLM-5.3-Flash and Llama 4 Scout trade strengths across price, capabilities, and technical limits. The better choice depends on the workload.
On price, Llama 4 Scout is roughly 1.8x cheaper per token on a blended 3:1 input/output basis, which adds up quickly at production volume.
Llama 4 Scout also accepts a larger context window (10,000,000 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 want the most recent training data — it shipped Aug 2026
Choose Llama 4 Scout
- cost matters — it's about 1.8x cheaper per token
- you process long inputs — it offers a 10,000,000 token context window
At a glance
The differences that matter most.
Performance Benchmarks
Comparative analysis across standard metrics
GLM-5.3-Flash and Llama 4 Scoutdon'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 1.9x more expensive than Llama 4 Scout ($0.08/1M tokens).
For output processing, GLM-5.3-Flash ($0.50/1M tokens) is 1.7x more expensive than Llama 4 Scout ($0.30/1M tokens).
In conclusion, GLM-5.3-Flash is more expensive than Llama 4 Scout.*
* Using a 3:1 ratio of input to output tokens
Model Size
Parameter count comparison
GLM-5.3-Flash has 211.0B more parameters than Llama 4 Scout, making it 193.6% larger.
Context Window
Maximum input and output token capacity
Llama 4 Scout accepts 10,000,000 input tokens compared to GLM-5.3-Flash's 1,000,000 tokens. Llama 4 Scout can generate longer responses up to 10,000,000 tokens, while GLM-5.3-Flash is limited to 131,072 tokens.
Input Capabilities
Supported data types and modalities
Both GLM-5.3-Flash and Llama 4 Scout support multimodal inputs.
They are both capable of processing various types of data, offering versatility in application.
GLM-5.3-Flash
Llama 4 Scout
License
Usage and distribution terms
GLM-5.3-Flash is licensed under MIT, while Llama 4 Scout uses Llama 4 Community License Agreement.
License differences may affect how you can use these models in commercial or open-source projects.
MIT
Open weights
Llama 4 Community License Agreement
Open weights
Release Timeline
When each model was launched
GLM-5.3-Flash was released on 2026-08-26, while Llama 4 Scout was released on 2025-04-05.
GLM-5.3-Flash is 17 months newer than Llama 4 Scout.
Aug 26, 2026
0 days ago
1.4yr newerApr 5, 2025
1.4 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 ZAI. Llama 4 Scout is available from DeepInfra, Lambda, Novita, Groq, Fireworks, Together.
GLM-5.3-Flash
Llama 4 Scout
Outputs Comparison
Judge for yourself.
Run your own prompts against GLM-5.3-Flash and Llama 4 Scout side-by-side, then vote on the output you prefer.
FAQ
Common questions about GLM-5.3-Flash vs Llama 4 Scout.