deepseek-v4-pro vs glm-5.1 speed comparison

Based on 69 anonymous user runs.

Verdict: deepseek-v4-pro has faster output (median 81 vs 53 tok/s); deepseek-v4-pro has faster TTFT (1.41s vs 4.80s).
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[![deepseek-v4-pro is faster than glm-5.1: 81 tok/s on TOKRACE](https://tokrace.com/api/badge/compare/deepseek-v4-pro-vs-glm-5-1?locale=en)](https://tokrace.com/en/compare/deepseek-v4-pro-vs-glm-5-1)
Median output tok/s8153
Average output tok/s8764
TTFT1.41s4.80s
Peak tok/s293594
Samples3336

· Data comes from voluntary anonymous sharing; medians reduce jitter · Updates every 5 minutes

· Speed is affected by network, time of day and provider load · Methodology

How to use this comparison

Writing/long output: Prioritize median output tok/s and peak speed.

Chat/agents: TTFT usually has a bigger UX impact.

Model selection: Rerun your real Prompt and inspect output quality too.

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FAQ

Which model outputs faster, deepseek-v4-pro or glm-5.1?

deepseek-v4-pro has faster output (median 81 vs 53 tok/s); deepseek-v4-pro has faster TTFT (1.41s vs 4.80s).

Why can output speed and TTFT have different winners?

Output tok/s measures sustained generation speed, while TTFT measures the wait until the first token. A model can generate long text faster while still taking longer to start.

How should I rerun this comparison?

Use the arena with the same Prompt, temperature and network conditions, then repeat a few times and combine the speed data with output quality.

Can I embed this comparison in GitHub or an article?

Yes. This page provides Markdown and HTML badges. The badge image URL is https://tokrace.com/api/badge/compare/deepseek-v4-pro-vs-glm-5-1?locale=en.