GPT-5.4 Mini vs GLM 5

GPT-5.4 Mini and GLM 5 pull in opposite directions: GPT-5.4 Mini is cheaper to send tokens to, $0.75 per 1M against $1.00, while GLM 5 is cheaper to get tokens back from, $3.20 per 1M against $4.50. Which one you want depends on how long the answers are. The worked costs below do not agree on a winner: GPT-5.4 Mini is cheaper on a RAG answer and an agent loop, GLM 5 on a chat turn.

On graduate-level science (GPQA Diamond), GPT-5.4 Mini is ahead, 87.5 (xhigh) against 82 (Reasoning). With the costs split between them, that is the tie-breaker.

Standard pay-as-you-go prices, as of 11 Feb 2026. Last updated 29 Sep 2026.

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Cheaper overall

GLM 5

8% lower blended rate

Higher benchmark scores

GPT-5.4 Mini

leads on 6 of 9 figures

Bigger context window

GPT-5.4 Mini

400,000 vs 204,800 tokens

Cheaper cached input

GPT-5.4 Mini

$0.075 vs $0.20, 63% less

Where each one wins

GPT-5.4 Mini

  • Cheaper input tokens $0.75 vs $1.00, 25% less
  • Cheaper cached input $0.075 vs $0.20, 63% less
  • Larger context window 400,000 tokens
  • Higher graduate-level science (GPQA Diamond) 87.5 vs 82
  • Higher instruction following (IFBench) 73.3 vs 72.3
  • Higher long-context reasoning (AA-LCR) 77 vs 75.7
  • Ahead on 3 more benchmark figures
  • Offers Batch and Flex pricing not listed for GLM 5

GLM 5

  • Cheaper output tokens $3.20 vs $4.50, 29% less
  • Higher expert-exam performance (Humanity's Last Exam) 29.3 vs 28.1
  • Higher support-agent performance (ฯ„ยฒ-Bench Telecom) 98.2 vs 83.3
  • Higher answer reliability (Omniscience Non-Hallucination) 64.7 vs 10.2

What four workloads cost

One run, and the same run a thousand times.

Caching is what decides it: over twenty calls GPT-5.4 Mini costs $0.1380 against $0.2048, a difference of $66.80 across a thousand loops.

Workload GPT-5.4 Mini GLM 5 ร—1,000 Difference
Chat turn 1,000 in / 500 out $0.0030 $0.0026 $3.00 / $2.60 GLM 5 is 13% cheaper
RAG answer 10,000 in / 800 out $0.0111 $0.0126 $11.10 / $12.56 GPT-5.4 Mini is 12% cheaper
Agent loop 32,000 in / 700 out ร— 20 calls $0.1380 $0.2048 $138.00 / $204.80 GPT-5.4 Mini is 33% cheaper
Long document 400,000 in / 3,000 out GLM 5's context window holds 204,800 tokens, so a 400,000-token prompt does not fit.

Price your own token counts for these two โ†’

Price per 1M tokens

Neither model changes its rate with prompt length, so these rates apply to every request.

Context band Price GPT-5.4 Mini GLM 5 Difference
Any prompt length Input $0.75 $1.00 GPT-5.4 Mini is 25% cheaper
Any prompt length Cached input $0.075 $0.20 GPT-5.4 Mini is 63% cheaper
Any prompt length Output $4.50 $3.20 GLM 5 is 29% cheaper

Blended: GPT-5.4 Mini $1.6875, GLM 5 $1.55 per 1M โ€” one rate at 3:1 input to output, for comparing two models at a glance.

GPT-5.4 Mini priced by OpenAI, GLM 5 by Z.ai. Standard tier, pay-as-you-go.

Other pricing tiers

Only GPT-5.4 Mini lists Batch and Flex, at up to 50% off its own standard rate; GLM 5 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 Mini GLM 5 Cheaper
Batch only on GPT-5.4 Mini $0.375 in / $2.25 out 50% off Standard Not offered —
Flex only on GPT-5.4 Mini $0.375 in / $2.25 out 50% off Standard Not offered —

Benchmarks

They share 9 figures: GPT-5.4 Mini leads on 6, GLM 5 on 3. The widest gap is 54.5 points, on answer reliability (Omniscience Non-Hallucination).

Graduate-level science

GPQA Diamond โ€” Graduate-level questions in biology, chemistry & physics

GPT-5.4 Mini 87.5
GLM 5 82

GPT-5.4 Mini ahead by 5.5

Expert-exam performance

Humanity's Last Exam โ€” Expert-level questions across many academic domains

GPT-5.4 Mini 28.1
GLM 5 29.3

GLM 5 ahead by 1.2

Instruction following

IFBench โ€” Precise following of detailed instructions

GPT-5.4 Mini 73.3
GLM 5 72.3

GPT-5.4 Mini ahead by 1

Support-agent performance

ฯ„ยฒ-Bench Telecom โ€” Tool-using agent tasks in a telecom support setting

GPT-5.4 Mini 83.3
GLM 5 98.2

GLM 5 ahead by 14.9

Long-context reasoning

AA-LCR โ€” Long-context reasoning across large inputs

GPT-5.4 Mini 77
GLM 5 75.7

GPT-5.4 Mini ahead by 1.3

Command-line work

Terminal-Bench Hard โ€” Complex command-line and terminal workflows

GPT-5.4 Mini 52.3
GLM 5 43.2

GPT-5.4 Mini ahead by 9.1

Physics research reasoning

CritPt โ€” Unpublished physics research reasoning problems

GPT-5.4 Mini 10
GLM 5 2

GPT-5.4 Mini ahead by 8

Factual accuracy

Omniscience Accuracy โ€” Breadth of factual knowledge across domains

GPT-5.4 Mini 37.5
GLM 5 26.3

GPT-5.4 Mini ahead by 11.2

Answer reliability

Omniscience Non-Hallucination โ€” How reliably the model avoids fabricated answers

GPT-5.4 Mini 10.2
GLM 5 64.7

GLM 5 ahead by 54.5

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 Mini holds 195,200 more input tokens in one request. GPT-5.4 Mini also takes file and image.

Specification GPT-5.4 Mini GLM 5
Context window 400,000 tokens 204,800 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 11 Feb 2026
Status Active Active
Sold by OpenAI, Perplexity Z.ai

FAQs

Is GPT-5.4 Mini cheaper than GLM 5?
No โ€” the other way round. A 1,000-token prompt with a 500-token reply costs $0.0030 on GPT-5.4 Mini and $0.0026 on GLM 5.
How much do GPT-5.4 Mini and GLM 5 cost per 1M tokens?
GPT-5.4 Mini costs $0.75 for input and $4.50 for output. GLM 5 costs $1.00 and $3.20. Standard pay-as-you-go rates, as of 11 Feb 2026.
Which is better, GPT-5.4 Mini or GLM 5?
On published benchmarks, GPT-5.4 Mini. It leads on 6 of the 9 figures both models report, including graduate-level science (GPQA Diamond), where it scores 87.5 against 82.
Does GPT-5.4 Mini or GLM 5 offer batch pricing?
GPT-5.4 Mini only. Its batch input costs $0.375, 50% off its standard rate, and GLM 5 lists no batch tier at all.
Does GPT-5.4 Mini or GLM 5 have a bigger context window?
GPT-5.4 Mini, at 400,000 tokens against 204,800. That is 195,200 more input tokens in a single request.

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