GLM-5.3-Flash vs GPT OSS 120B High
Comparing GLM-5.3-Flash and GPT OSS 120B High across benchmarks, pricing, and capabilities.
Zhipu AI · OpenAI · Updated for 2026
Which is better?
GLM-5.3-Flash and GPT OSS 120B High trade strengths across price, capabilities, and technical limits. The better choice depends on the workload.
On price, GPT OSS 120B High is roughly 1.2x 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 GPT OSS 120B High
- cost matters — it's about 1.2x cheaper per token
At a glance
The differences that matter most.
Performance Benchmarks
Comparative analysis across standard metrics
GLM-5.3-Flash and GPT OSS 120B Highdon'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 1.5x more expensive than GPT OSS 120B High ($0.10/1M tokens).
For output processing, GLM-5.3-Flash ($0.50/1M tokens) costs the same as GPT OSS 120B High ($0.50/1M tokens).
In conclusion, GLM-5.3-Flash is more expensive than GPT OSS 120B High.*
* Using a 3:1 ratio of input to output tokens
Model Size
Parameter count comparison
GLM-5.3-Flash has 203.2B more parameters than GPT OSS 120B High, making it 174.0% larger.
Context Window
Maximum input and output token capacity
GLM-5.3-Flash accepts 1,048,576 input tokens compared to GPT OSS 120B High'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 GPT OSS 120B High 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
GPT OSS 120B High
License
Usage and distribution terms
GLM-5.3-Flash is licensed under MIT, while GPT OSS 120B High uses Apache 2.0.
License differences may affect how you can use these models in commercial or open-source projects.
MIT
Open weights
Apache 2.0
Open weights
Release Timeline
When each model was launched
GLM-5.3-Flash was released on 2026-08-26, while GPT OSS 120B High was released on 2025-08-05.
GLM-5.3-Flash is 13 months newer than GPT OSS 120B High.
Aug 26, 2026
0 days ago
1.1yr newerAug 5, 2025
1.1 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. GPT OSS 120B High is available from OpenAI, Fireworks.
GLM-5.3-Flash
GPT OSS 120B High
Outputs Comparison
Judge for yourself.
Run your own prompts against GLM-5.3-Flash and GPT OSS 120B High side-by-side, then vote on the output you prefer.
FAQ
Common questions about GLM-5.3-Flash vs GPT OSS 120B High.