GLM-4.5-Air vs GPT-4o
Wins 4 of 6 areas
Coding · Agents · Reasoning · Following instructions
Wins 2 of 6 areas
Facts · Long documents
GLM-4.5-Air is the stronger all-rounder.GPT-4o is better at facts.
Scores updated · 31 tests both models report · How we compare
Where each one wins
Tests won in each of the six areas where both have results. Each piece is one test, so a longer bar means more evidence; grey means the two scored within a point of each other.
- ReasoningHard problems that need careful thinking20GLM-4.5-Air2 of 3 tests · 1 tie
- CodingWriting and fixing software21GLM-4.5-Air2 of 3 tests
- AgentsCarrying out multi-step tasks on its own10GLM-4.5-Air1 of 1 test
- Following instructionsDoing exactly what it is asked10GLM-4.5-Air1 of 1 test
- FactsGetting facts right instead of making them up02GPT-4o2 of 3 tests · 1 tie
- Long documentsFinding answers in very long texts01GPT-4o1 of 1 test
Agents, long documents and following instructions rest on a single test each.
What it costs
Prices per million tokens, roughly 750,000 words. The bars show the cost of a million tokens read plus a million written.
GLM-4.5-Air costs 94% less for the same work.
The biggest differences
The three tests each model wins by the widest margin. Scores are out of 100.
Where GLM-4.5-Air pulls ahead
- Fixes real GitHub issues in Python projectsSWE-bench Verified+24.4points ahead
- Graduate-level biology, physics and chemistry questionsGPQA Diamond+20.7points ahead
- Hard command-line tasks in a real terminalTerminal-Bench Hard+12.2points ahead
Where GPT-4o pulls ahead
- Avoids making up answers it doesn't knowAA-Omniscience · Non-hallucination+55points ahead
- Reasons across sets of long documentsAA-LCR+9.3points ahead
- Answers hard knowledge questions correctlyAA-Omniscience · Accuracy+7.4points ahead
Every test, side by side
All 31 tests both models report. The winning score is in its model's colour; marks a score checked independently.
CodingGLM-4.5-Air
- SWE-bench VerifiedGLM-4.5-Air by 24.457.633.2+24.4
- Terminal-Bench HardGLM-4.5-Air by 12.220.58.3+12.2
- SciCodeGPT-4o by 2.730.633.3+2.7
ReasoningGLM-4.5-Air
- GPQA DiamondGLM-4.5-Air by 20.773.352.6+20.7
- Humanity's Last ExamGLM-4.5-Air by 5.271.8+5.2
- CritPttie00tie
FactsGPT-4o
- AA-Omniscience · Non-hallucinationGPT-4o by 557.162.1+55
- AA-Omniscience · AccuracyGPT-4o by 7.416.323.7+7.4
- Vectara HHEM hallucination ratelower is bettertie9.39.6tie
Following instructionsGLM-4.5-Air
- IFBenchGLM-4.5-Air by 1.637.636+1.6
Other results19 tests, not counted
Tests outside the eight areas. They are not counted above: several are summary scores built from other tests, or the same test under another name.
- AIME 2025GLM-4.5-Air by 71.683.311.7+71.6
- AA-OmniscienceGPT-4o by 51-61.5-10.5+51
- LiveCodeBenchGLM-4.5-Air by 32.470.738.3+32.4
- HarmBenchGPT-4o by 26.756.182.9+26.7
- MATH-500 (EM)GLM-4.5-Air by 23.598.174.6+23.5
- TAU-bench (airline)GLM-4.5-Air by 1860.842.8+18
- TAU-bench (retail)GLM-4.5-Air by 17.677.960.3+17.6
- τ²-Bench Telecom (AA run)GLM-4.5-Air by 17.646.528.9+17.6
- vectara_avg_summary_lengthGPT-4o by 1670.686.6+16
- AA Agentic IndexGLM-4.5-Air by 12.6218.4+12.6
- MMLU-ProGLM-4.5-Air by 6.781.474.7+6.7
- AIR-Bench 2024GPT-4o by 5.357.162.4+5.3
- vectara_answer_rateGLM-4.5-Air by 4.398.193.8+4.3
- AA IntelligenceGLM-4.5-Air by 3.811.17.3+3.8
- XSTestGLM-4.5-Air by 1.398.697.3+1.3
- simple_safety_teststie9998.5tie
- Artificial Analysis Coding Indextie23.824.2tie
- vectara_factual_consistencytie90.790.4tie
- anthropic_red_teamtie9999.1tie
Questions people ask
Which is better, GLM-4.5-Air or GPT-4o?
GLM-4.5-Air wins four of the six areas where both have results: coding, agents, reasoning and following instructions. GPT-4o wins facts and long documents.
Which is better for coding?
GLM-4.5-Air. It wins 2 of the 3 coding tests both models report; GPT-4o wins 1.
Which is cheaper?
GLM-4.5-Air costs $0.17 per million input tokens and $0.98 per million output tokens; GPT-4o costs $5.00 and $15.00. That makes GLM-4.5-Air about 94% cheaper for the same work.
How do you compare the two?
We use the 31 benchmark tests both models have published scores on. The verdict counts the 12 tests in the eight capability areas, and a gap under one point (ten on rating-style scales) counts as a tie. The other 19 are listed but not counted, because several are summary scores or repeat a test. Each score is the one shown on the model's own page.