Comparison · OpenAI and Z.ai
GPT-5.4 Nano vs GLM 5.3 FlashX
Listed API prices of GPT-5.4 Nano and GLM 5.3 FlashX turned into the cost of the same three standard tasks and what each provider’s API documentation says about features that break on a switch. Output quality, speed and answer length are not compared.
Calculated impact cost per task and per month
For an L2 task (deep analysis over a 50,000-token document, 3 steps), GPT-5.4 Nano costs $0.036 and GLM 5.3 FlashX $0.063 at the prices listed in the United States on , so GPT-5.4 Nano is 43.2 % less than GLM 5.3 FlashX, counting visible output only, without cache discounts or hidden reasoning.
| Task | GPT-5.4 Nano, per task | GLM 5.3 FlashX, per task | GPT-5.4 Nano, per month | GLM 5.3 FlashX, per month | GPT-5.4 Nano vs GLM 5.3 FlashX, per task |
|---|---|---|---|---|---|
| L1Micro-task (classification or strict JSON extraction) | $0.0006per L1 task | $0.0008per L1 task | $8.03per month | $11.75per month | −31.7 % |
| L2Deep analysis over a 50,000-token document | $0.036per L2 task | $0.063per L2 task | $519.03per month | $913.67per month | −43.2 % |
| L3Agentic coding loop, 15 steps | $0.274per L3 task | $0.498per L3 task | $4,005.51per month | $7,270.58per month | −44.9 % |
Calculated Per month: 20 tasks an hour around the clock, 730 hours.
Prices USD per 1M tokens
| Price | GPT-5.4 Nano | GLM 5.3 FlashX |
|---|---|---|
| Input, per 1M tokens | $0.200 | $0.370 |
| Output, per 1M tokens | $1.25 | $1.25 |
| Price from | OpenRouter · source page (data) Published | OpenRouter · source page (data) Published |
| Read | · the United States | · the United States |
| Context window | 400,000 tokens | 1,048,576 tokens |
What breaks when you switch Published provider documentation
Moving from OpenAI to Z.ai, 4 of the 5 features may not carry over, by each provider’s documentation:
- Strict JSON schemas — OpenAI: yes; Z.ai: partly. Code that parses answers without checks starts failing where a provider promises only valid JSON, not your schema.
- Parallel tool calls — OpenAI: yes; Z.ai: not stated. An agent built around several calls per turn gets one call per turn: more round trips, more input tokens, slower runs.
- Streamed tool arguments — OpenAI: yes; Z.ai: partly. An interface that shows arguments as they are written sees nothing until the whole call is ready.
- Cache covers tool definitions — OpenAI: yes; Z.ai: not stated. Where the cache does not cover tool definitions, a long tool list is paid as fresh input on every request.
Moving from Z.ai to OpenAI: every feature that Z.ai’s documentation lists as supported is also listed as supported by OpenAI.
| Feature of the API | OpenAI | Z.ai |
|---|---|---|
| Strict JSON schemas | Yes | Partly |
| Parallel tool calls | Yes | Not stated |
| Streamed tool arguments | Yes | Partly |
| Reasoning with tools | Yes | Yes |
| Cache covers tool definitions | Yes | Not stated |
What each provider’s own API documentation says, read ; “not stated” is not the same as “no”. Quotes and sources: what breaks when you switch AI APIs.