Cheaper overall
GLM 4.7 FlashX
67% lower blended rate
Higher benchmark scores
GPT-5.4 Nano
leads on 8 of 9 figures
Bigger context window
GPT-5.4 Nano
400,000 vs 202,752 tokens
Cheaper cached input
GLM 4.7 FlashX
$0.01 vs $0.02, 50% less
Where each one wins
GPT-5.4 Nano
- Larger context window 400,000 tokens
- Higher graduate-level science (GPQA Diamond) 81.7 vs 58.1
- Higher expert-exam performance (Humanity's Last Exam) 28.3 vs 7.6
- Higher instruction following (IFBench) 75.9 vs 60.8
- Ahead on 5 more benchmark figures
- Offers Batch and Flex pricing not listed for GLM 4.7 FlashX
GLM 4.7 FlashX
- Cheaper input tokens $0.07 vs $0.20, 65% less
- Cheaper output tokens $0.40 vs $1.25, 68% less
- Cheaper cached input $0.01 vs $0.02, 50% less
- Cheaper on all four workloads
- Higher support-agent performance (ฯยฒ-Bench Telecom) 98.8 vs 76
What four workloads cost
One run, and the same run a thousand times.
GLM 4.7 FlashX is cheaper on all four workloads, by much the same margin each time โ about 2.9 times, from $0.0003 against $0.0008 on a chat turn to $0.0144 against $0.0375 on a long document.
| Workload | GPT-5.4 Nano | GLM 4.7 FlashX | ร1,000 | Difference |
|---|---|---|---|---|
| Chat turn 1,000 in / 500 out | $0.0008 | $0.0003 | $0.8250 / $0.2700 | GLM 4.7 FlashX is 67% cheaper |
| RAG answer 10,000 in / 800 out | $0.0030 | $0.0010 | $3.00 / $1.02 | GLM 4.7 FlashX is 66% cheaper |
| Agent loop 32,000 in / 700 out ร 20 calls | $0.0375 | $0.0144 | $37.50 / $14.40 | GLM 4.7 FlashX is 62% cheaper |
| Long document 400,000 in / 3,000 out | GLM 4.7 FlashX's context window holds 202,752 tokens, so a 400,000-token prompt does not fit. | |||
Price per 1M tokens
Above 272,000 input tokens the rates change, and the new rate applies to the whole request, not just the tokens past that point. It does not change which of the two is cheaper.
| Context band | Price | GPT-5.4 Nano | GLM 4.7 FlashX | Difference |
|---|---|---|---|---|
| Prompts up to 272,000 tokens | Input | $0.20 | $0.07 | GLM 4.7 FlashX is 65% cheaper |
| Prompts up to 272,000 tokens | Cached input | $0.02 | $0.01 | GLM 4.7 FlashX is 50% cheaper |
| Prompts up to 272,000 tokens | Output | $1.25 | $0.40 | GLM 4.7 FlashX is 68% cheaper |
| Prompts over 272,000 tokens | Input | $0.20 | $0.07 | GLM 4.7 FlashX is 65% cheaper |
| Prompts over 272,000 tokens | Cached input | $0.02 | $0.01 | GLM 4.7 FlashX is 50% cheaper |
| Prompts over 272,000 tokens | Output | $1.25 | $0.40 | GLM 4.7 FlashX is 68% cheaper |
Blended: GPT-5.4 Nano $0.4625, GLM 4.7 FlashX $0.1525 per 1M โ one rate at 3:1 input to output, for comparing two models at a glance.
GPT-5.4 Nano priced by OpenAI, GLM 4.7 FlashX by Z.ai. Standard tier, pay-as-you-go.
Other pricing tiers
Only GPT-5.4 Nano lists Batch and Flex, at up to 50% off its own standard rate; GLM 4.7 FlashX offers none of them.
Every tier either model sells is here, so this is the whole price sheet. A saving is measured against that model's own standard rate โ how we read tiers.
| Tier | GPT-5.4 Nano | GLM 4.7 FlashX | Cheaper |
|---|---|---|---|
| Batch only on GPT-5.4 Nano | $0.10 in / $0.625 out 50% off Standard | Not offered | — |
| Flex only on GPT-5.4 Nano | $0.10 in / $0.625 out 50% off Standard | Not offered | — |
Benchmarks
They share 9 figures: GPT-5.4 Nano leads on 8, GLM 4.7 FlashX on 1. The widest gap is 42.8 points, on answer reliability (Omniscience Non-Hallucination).
Graduate-level science
GPQA Diamond โ Graduate-level questions in biology, chemistry & physics
GPT-5.4 Nano ahead by 23.6
Expert-exam performance
Humanity's Last Exam โ Expert-level questions across many academic domains
GPT-5.4 Nano ahead by 20.7
Instruction following
IFBench โ Precise following of detailed instructions
GPT-5.4 Nano ahead by 15.1
Support-agent performance
ฯยฒ-Bench Telecom โ Tool-using agent tasks in a telecom support setting
GLM 4.7 FlashX ahead by 22.8
Long-context reasoning
AA-LCR โ Long-context reasoning across large inputs
GPT-5.4 Nano ahead by 35
Command-line work
Terminal-Bench Hard โ Complex command-line and terminal workflows
GPT-5.4 Nano ahead by 20.4
Physics research reasoning
CritPt โ Unpublished physics research reasoning problems
GPT-5.4 Nano ahead by 9
Factual accuracy
Omniscience Accuracy โ Breadth of factual knowledge across domains
GPT-5.4 Nano ahead by 9.5
Answer reliability
Omniscience Non-Hallucination โ How reliably the model avoids fabricated answers
GPT-5.4 Nano ahead by 42.8
Each figure is that model's best published run, with the effort level named beside it โ where these scores come from.
Specifications
GPT-5.4 Nano holds 197,248 more input tokens in one request. GPT-5.4 Nano also takes file and image.
| Specification | GPT-5.4 Nano | GLM 4.7 FlashX |
|---|---|---|
| Context window | 400,000 tokens | 202,752 tokens |
| Max output | 128,000 tokens | 128,000 tokens |
| Takes in | Text, image, file | Text |
| Puts out | Text | Text |
| Knowledge cutoff | 31 Aug 2025 | โ |
| Released | 17 Mar 2026 | 19 Jan 2026 |
| Status | Active | Active |
| Sold by | OpenAI, Perplexity | Z.ai |
FAQs
- Is GPT-5.4 Nano cheaper than GLM 4.7 FlashX?
- No โ the other way round. A 1,000-token prompt with a 500-token reply costs $0.0008 on GPT-5.4 Nano and $0.0003 on GLM 4.7 FlashX, and the same model is cheaper on every workload on this page.
- How much do GPT-5.4 Nano and GLM 4.7 FlashX cost per 1M tokens?
- GPT-5.4 Nano costs $0.20 for input and $1.25 for output. GLM 4.7 FlashX costs $0.07 and $0.40. Standard pay-as-you-go rates, as of 19 Jan 2026.
- Which is better, GPT-5.4 Nano or GLM 4.7 FlashX?
- On published benchmarks, GPT-5.4 Nano. It leads on 8 of the 9 figures both models report, including graduate-level science (GPQA Diamond), where it scores 81.7 against 58.1.
- Does GPT-5.4 Nano or GLM 4.7 FlashX offer batch pricing?
- GPT-5.4 Nano only. Its batch input costs $0.10, 50% off its standard rate, and GLM 4.7 FlashX lists no batch tier at all.
- Does GPT-5.4 Nano or GLM 4.7 FlashX have a bigger context window?
- GPT-5.4 Nano, at 400,000 tokens against 202,752. That is 197,248 more input tokens in a single request.