DeepSeek-V4-Pro vs GLM-5.3
Both are open flagships built for coding agents. GLM-5.3 is tuned for security and terminal work and reasons on every call; DeepSeek-V4-Pro is the stronger general coder, with a no-thinking mode for quick answers.
Choose DeepSeek-V4-Pro if
- A fast, no-thinking option alongside deep reasoning.
- General coding and maths.
- An MIT licence.
Choose GLM-5.3 if
- Security analysis and cyber-defence — 84.5% on CyberGym.
- Command-line automation agents.
- Every answer reasoned through.
Side by side
| DeepSeek-V4-Pro | GLM-5.3 | |
|---|---|---|
| Made by | DeepSeek | Zhipu AI |
| Released | April 2026 | August 2026 |
| Input price, per 1M tokens | $1.56 | $1.274 |
| Output price, per 1M tokens | $3.12 | $4.004 |
| Cached input, per 1M tokens | $0.234 | $0.3276 |
| Batch (about half price) | No | No |
| Context window | 1M tokens | 1M tokens |
| Longest answer | 384K tokens | 128K tokens |
| Reads | Text | Text |
| Thinks before answering | Yes, adjustable | Always on |
| Open weights | Yes, MIT | Yes, GLM-5.3 License |
| Runs in Sri Lanka | No | No |
Prices are Roar AI’s published rates, live from our price list. Specs are each lab’s own published figures.
What a real job costs
Take 1,000 requests, each about 3,000 tokens in and 1,000 out — a long prompt and a page of answer.
The two cost about the same for this job. Models that think before answering spend extra output tokens doing it, so on hard prompts the real gap can be wider than the rates suggest.
Use both, switch any time
On Roar AI both are on the same key and the same monthly invoice. Trying the other one is a one-word change:
client.chat.completions.create(model="deepseek-v4-pro", …) client.chat.completions.create(model="glm-5.3", …)
Send the same prompts to both for a day and compare the answers on your own work — that settles it faster than any benchmark. Read the docs.