Model comparison
GLM-4.5 vs o4-mini
GLM-4.5 and o4-mini score almost the same on the Noometry Index (42.0 vs 41.6), so choose on price, context window or the category you care about most.
Last verified . 26 shared benchmarks.
Summary
- They share 26 benchmarks with published results for both. GLM-4.5 scores higher in 4 categories and o4-mini in 4 categories; 7 gaps are clear of the uncertainty.
- The widest gap is in knowledge, where o4-mini leads 43.6 to 35.9.
- The biggest single-benchmark swing is Fiction.LiveBench: 58.3% for GLM-4.5 and 77.8% for o4-mini.
- GLM-4.5 is cheaper at $0.60 / $2.20 per million input/output tokens, against $1.10 / $4.40 for o4-mini.
- o4-mini accepts more context: 200K tokens versus 131K.
- GLM-4.5 has downloadable open weights; the other is API-only.
Side by side
| GLM-4.5 | o4-mini | |
|---|---|---|
| Provider | Z.ai (Zhipu) | OpenAI |
| Noometry Index | 42.0 | 41.6 |
| Released | 2025-07-27 | 2025-04-16 |
| Weights | Open | Proprietary |
| Context window | 131K | 200K |
| Max output | 98K | 100K |
| Input $ / M tokens | $0.60 | $1.10 |
| Output $ / M tokens | $2.20 | $4.40 |
| Results tracked | 27 | 60 |
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Category by category
Coding Too close to call
GLM-4.5: 41.4 (#125), o4-mini: 40.9 (#127)
| Benchmark | GLM-4.5 | o4-mini |
|---|---|---|
| SWE-bench Verified (bash only) | 54.2% | 45% |
| WeirdML | 40.6% | 52.6% |
| LMArena Coding | 1434 | 1368 |
| ALE-Bench | 344.82 | 826.17 |
| AlgoTune | 1.52 | 1.72 |
| Aider Polyglot | — | 72% |
| GSO | — | 3.6% |
| CadEval | — | 62% |
Agentic & Tool Use Not comparable
GLM-4.5: —, o4-mini: 32.6 (#61)
| Benchmark | GLM-4.5 | o4-mini |
|---|---|---|
| Berkeley Function Calling Leaderboard | — | 53.2% |
| GDPval | — | 25.3% |
| METR Time Horizons | — | 63.9% |
Reasoning GLM-4.5 leads
GLM-4.5: 28.6 (#100), o4-mini: 24.6 (#162)
| Benchmark | GLM-4.5 | o4-mini |
|---|---|---|
| Kagi LLM Benchmark | 57.9% | 67.6% |
| LMArena Hard Prompts | 1429 | 1351 |
| ARC-AGI-2 | — | 6.1% |
| SimpleBench | — | 38.7% |
| ARC-AGI-1 | — | 58.7% |
| CritPt | — | 0.6% |
| Chess Puzzles | — | 26% |
| EnigmaEval | — | 9.2% |
| Mystery Game Puzzles | — | 5% |
| DTBench | — | 77.6% |
| LMCA | — | 26.5% |
| Epoch Capabilities Index | — | 145.64 |
| ForecastBench | — | 61.8 |
Math o4-mini leads
GLM-4.5: 39.0 (#116), o4-mini: 40.8 (#89)
| Benchmark | GLM-4.5 | o4-mini |
|---|---|---|
| LMArena Math | 1427 | 1389 |
| FrontierMath (Tiers 1-3) | — | 36.1% |
| FrontierMath Tier 4 | — | 4.9% |
| OTIS Mock AIME 2024-2025 | — | 81.7% |
| Omni-MATH | — | 72% |
| MATH Level 5 | — | 97.8% |
| FrontierMath (Feb 2025 set) | — | 24.8% |
| FrontierMath Tier 4 (v1) | — | 6.3% |
Knowledge o4-mini leads
GLM-4.5: 35.9 (#179), o4-mini: 43.6 (#91)
| Benchmark | GLM-4.5 | o4-mini |
|---|---|---|
| Humanity's Last Exam | 8.3% | 18.1% |
| Confabulations | 11.3% | 15.8% |
| LMArena Expert | 1433 | 1343 |
| GPQA Diamond | — | 79.6% |
| SimpleQA Verified | — | 19.6% |
| MMLU-Pro | — | 82% |
| Vectara Hallucination Rate | — | 18.6% |
| GPQA (HELM) | — | 73.5% |
Multimodal Not comparable
GLM-4.5: —, o4-mini: 40.2 (#49)
| Benchmark | GLM-4.5 | o4-mini |
|---|---|---|
| LMArena Vision | — | 1194 |
| GeoBench | — | 64% |
| VPCT | — | 57.5% |
Multilingual GLM-4.5 leads
GLM-4.5: 52.8 (#77), o4-mini: 47.0 (#154)
| Benchmark | GLM-4.5 | o4-mini |
|---|---|---|
| LMArena Non-English | 1417 | 1337 |
| LMArena Chinese | 1465 | 1354 |
| LMArena French | 1418 | 1364 |
| LMArena German | 1407 | 1336 |
| LMArena Japanese | 1415 | 1308 |
| LMArena Korean | 1380 | 1312 |
| LMArena Russian | 1414 | 1334 |
| LMArena Spanish | 1454 | 1347 |
Instruction Following o4-mini leads
GLM-4.5: 74.1 (#104), o4-mini: 75.2 (#68)
| Benchmark | GLM-4.5 | o4-mini |
|---|---|---|
| LMArena Instruction Following | 1404 | 1321 |
| IFEval | — | 92.8% |
Long Context o4-mini leads
GLM-4.5: 38.2 (#201), o4-mini: 45.5 (#33)
| Benchmark | GLM-4.5 | o4-mini |
|---|---|---|
| Fiction.LiveBench | 58.3% | 77.8% |
| LMArena Longer Query | 1412 | 1315 |
Writing & Preference GLM-4.5 leads
GLM-4.5: 57.5 (#127), o4-mini: 54.0 (#152)
| Benchmark | GLM-4.5 | o4-mini |
|---|---|---|
| LMArena Text | 1430 | 1353 |
| LMArena Creative Writing | 1395 | 1294 |
| Short-Story Creative Writing | 73.4% | 75% |
| LMArena Multi-Turn | 1415 | 1350 |
| EQ-Bench Creative Writing | 1343 | — |
| WildBench | — | 85.4% |
Frequently asked questions
Is GLM-4.5 better than o4-mini?
GLM-4.5 and o4-mini score almost the same on the Noometry Index (42.0 vs 41.6), so choose on price, context window or the category you care about most.
Which is cheaper, GLM-4.5 or o4-mini?
GLM-4.5 is cheaper. It lists at $0.60 per million input tokens and $2.20 per million output tokens; o4-mini lists at $1.10 and $4.40.
Is GLM-4.5 or o4-mini better for coding?
They score almost the same on coding (41.4 vs 40.9); test both on your own repository before choosing.
Which has the bigger context window?
o4-mini does, with 200K tokens against 131K.
How many benchmarks do GLM-4.5 and o4-mini share?
26 benchmarks have published results for both models. GLM-4.5 has 27 scored results on Noometry and o4-mini has 60.