Model comparison
GLM-5V-Turbo vs GPT-4o
GLM-5V-Turbo is the stronger model overall, scoring 43.1 to 28.5 on the Noometry Index.
Last verified . 17 shared benchmarks.
Summary
- They share 17 benchmarks with published results for both. GLM-5V-Turbo scores higher in 9 categories and GPT-4o in 0 categories; 9 gaps are clear of the uncertainty.
- The widest gap is in math, where GLM-5V-Turbo leads 36.6 to 10.2.
- GLM-5V-Turbo is cheaper at $1.20 / $4 per million input/output tokens, against $2.50 / $10 for GPT-4o.
- GLM-5V-Turbo accepts more context: 200K tokens versus 128K.
Side by side
| GLM-5V-Turbo | GPT-4o | |
|---|---|---|
| Provider | Z.ai (Zhipu) | OpenAI |
| Noometry Index | 43.1 | 28.5 |
| Released | 2026-04-01 | 2024-05-13 |
| Weights | Proprietary | Proprietary |
| Context window | 200K | 128K |
| Max output | 131K | 16K |
| Input $ / M tokens | $1.20 | $2.50 |
| Output $ / M tokens | $4 | $10 |
| Results tracked | 19 | 72 |
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Category by category
Coding GLM-5V-Turbo leads
GLM-5V-Turbo: 41.8 (#105), GPT-4o: 25.1 (#323)
| Benchmark | GLM-5V-Turbo | GPT-4o |
|---|---|---|
| LMArena Coding | 1467 | 1297 |
| SWE-bench Verified | — | 31% |
| SWE-bench Verified (bash only) | — | 21.6% |
| Aider Polyglot | — | 45.3% |
| LMArena WebDev | 1400 | — |
| GSO | — | 0% |
| WeirdML | — | 25.1% |
| BigCodeBench Instruct | — | 51.1% |
| LiveBench Coding | — | 51.4% |
| BigCodeBench Complete | — | 61.1% |
| CadEval | — | 26% |
| HumanEval+ | — | 87.2% |
| MBPP+ | — | 72.2% |
Agentic & Tool Use Not comparable
GLM-5V-Turbo: —, GPT-4o: 20.8 (#133)
| Benchmark | GLM-5V-Turbo | GPT-4o |
|---|---|---|
| GDPval | — | 9.9% |
| TheAgentCompany | — | 8.6% |
| Cybench | — | 12.5% |
| BALROG | — | 32.3% |
| LMArena Search | — | 1006 |
| METR Time Horizons | — | 40.8% |
Reasoning GLM-5V-Turbo leads
GLM-5V-Turbo: 28.5 (#87), GPT-4o: 9.4 (#338)
| Benchmark | GLM-5V-Turbo | GPT-4o |
|---|---|---|
| LMArena Hard Prompts | 1443 | 1281 |
| ARC-AGI-2 | — | 0% |
| SimpleBench | — | 17.8% |
| ARC-AGI-1 | — | 4.5% |
| CritPt | — | 0% |
| Chess Puzzles | — | 13% |
| EnigmaEval | — | 0.8% |
| LiveBench Reasoning | — | 55.8% |
| DTBench | — | 64.5% |
| LiveBench Data Analysis | — | 60.9% |
| LMCA | — | 16.6% |
| Epoch Capabilities Index | — | 128.97 |
| ForecastBench | — | 57.7 |
| LiveBench | — | 55.3% |
Math GLM-5V-Turbo leads
GLM-5V-Turbo: 36.6 (#109), GPT-4o: 10.2 (#303)
| Benchmark | GLM-5V-Turbo | GPT-4o |
|---|---|---|
| LMArena Math | 1440 | 1285 |
| FrontierMath (Tiers 1-3) | — | 0.4% |
| OTIS Mock AIME 2024-2025 | — | 6.4% |
| Omni-MATH | — | 29.3% |
| LiveBench Math | — | 49.5% |
| MATH Level 5 | — | 53.3% |
| FrontierMath (Feb 2025 set) | — | 0.3% |
Knowledge GLM-5V-Turbo leads
GLM-5V-Turbo: 39.9 (#113), GPT-4o: 28.8 (#235)
| Benchmark | GLM-5V-Turbo | GPT-4o |
|---|---|---|
| LMArena Expert | 1451 | 1250 |
| GPQA Diamond | — | 49.2% |
| Humanity's Last Exam | — | 2.7% |
| SimpleQA Verified | — | 26% |
| MMLU-Pro | — | 71.3% |
| Confabulations | — | 15.3% |
| Vectara Hallucination Rate | — | 9.6% |
| GPQA (HELM) | — | 52% |
| MMLU | — | 88.1% |
Multimodal GLM-5V-Turbo leads
GLM-5V-Turbo: 40.1 (#41), GPT-4o: 33.9 (#85)
| Benchmark | GLM-5V-Turbo | GPT-4o |
|---|---|---|
| LMArena Vision | 1264 | 1137 |
| Video-MME | — | 71.9% |
| GeoBench | — | 71% |
| VPCT | — | 40% |
| LMArena Document | 1416 | — |
| ScienceQA | — | 88.5% |
Multilingual GLM-5V-Turbo leads
GLM-5V-Turbo: 53.2 (#69), GPT-4o: 43.4 (#181)
| Benchmark | GLM-5V-Turbo | GPT-4o |
|---|---|---|
| LMArena Non-English | 1420 | 1283 |
| LMArena Chinese | 1488 | 1277 |
| LMArena French | 1443 | 1303 |
| LMArena German | 1422 | 1282 |
| LMArena Korean | 1399 | 1234 |
| LMArena Russian | 1432 | 1286 |
| LMArena Spanish | 1446 | 1292 |
| LMArena Japanese | — | 1257 |
Instruction Following GLM-5V-Turbo leads
GLM-5V-Turbo: 75.1 (#75), GPT-4o: 66.8 (#202)
| Benchmark | GLM-5V-Turbo | GPT-4o |
|---|---|---|
| LMArena Instruction Following | 1422 | 1278 |
| LiveBench Instruction Following | — | 68.6% |
| IFEval | — | 81.7% |
Long Context GLM-5V-Turbo leads
GLM-5V-Turbo: 44.0 (#76), GPT-4o: 39.4 (#174)
| Benchmark | GLM-5V-Turbo | GPT-4o |
|---|---|---|
| LMArena Longer Query | 1439 | 1289 |
| Fiction.LiveBench | — | 66.7% |
Writing & Preference GLM-5V-Turbo leads
GLM-5V-Turbo: 62.6 (#69), GPT-4o: 52.8 (#160)
| Benchmark | GLM-5V-Turbo | GPT-4o |
|---|---|---|
| LMArena Text | 1437 | 1300 |
| LMArena Creative Writing | 1414 | 1291 |
| LMArena Multi-Turn | 1432 | 1302 |
| Short-Story Creative Writing | — | 81.8% |
| WildBench | — | 82.8% |
| LiveBench Language | — | 47.6% |
Frequently asked questions
Is GLM-5V-Turbo better than GPT-4o?
GLM-5V-Turbo is the stronger model overall, scoring 43.1 to 28.5 on the Noometry Index.
Which is cheaper, GLM-5V-Turbo or GPT-4o?
GLM-5V-Turbo is cheaper. It lists at $1.20 per million input tokens and $4 per million output tokens; GPT-4o lists at $2.50 and $10.
Is GLM-5V-Turbo or GPT-4o better for coding?
GLM-5V-Turbo scores higher on coding benchmarks: 41.8 versus 25.1 in the Noometry coding category.
Which has the bigger context window?
GLM-5V-Turbo does, with 200K tokens against 128K.
How many benchmarks do GLM-5V-Turbo and GPT-4o share?
17 benchmarks have published results for both models. GLM-5V-Turbo has 19 scored results on Noometry and GPT-4o has 72.