Model comparison
GLM-5.2 vs GPT-5-Codex
GLM-5.2 is the stronger model overall, scoring 50.9 to 37.3 on the Noometry Index.
Last verified . 2 shared benchmarks.
Summary
- They share 2 benchmarks with published results for both. GLM-5.2 scores higher in 3 categories and GPT-5-Codex in 0 categories; 2 gaps are clear of the uncertainty.
- The widest gap is in reasoning, where GLM-5.2 leads 42.1 to 30.0.
- The biggest single-benchmark swing is WeirdML: 70.1% for GLM-5.2 and 54.5% for GPT-5-Codex.
- GLM-5.2 is cheaper at $1.40 / $4.40 per million input/output tokens, against $1.25 / $10 for GPT-5-Codex.
- GLM-5.2 accepts more context: 1M tokens versus 400K.
- GLM-5.2 has downloadable open weights; the other is API-only.
Side by side
| GLM-5.2 | GPT-5-Codex | |
|---|---|---|
| Provider | Z.ai (Zhipu) | OpenAI |
| Noometry Index | 50.9 | 37.3 |
| Released | 2026-06-13 | 2025-09-15 |
| Weights | Open | Proprietary |
| Context window | 1M | 400K |
| Max output | 131K | 128K |
| Input $ / M tokens | $1.40 | $1.25 |
| Output $ / M tokens | $4.40 | $10 |
| Results tracked | 50 | 3 |
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Category by category
Coding GLM-5.2 leads
GLM-5.2: 50.9 (#37), GPT-5-Codex: 41.9 (#100)
| Benchmark | GLM-5.2 | GPT-5-Codex |
|---|---|---|
| WeirdML | 70.1% | 54.5% |
| SWE-bench Verified | 78.7% | — |
| DeepSWE | 43.8% | — |
| FrontierCode | 24.5% | — |
| LMArena WebDev | 1604 | — |
| SciCode | 50.5% | — |
| LMArena Coding | 1484 | — |
| ALE-Bench | 1,047 | — |
Agentic & Tool Use Too close to call
GLM-5.2: 31.6 (#63), GPT-5-Codex: 30.8 (#66)
| Benchmark | GLM-5.2 | GPT-5-Codex |
|---|---|---|
| Terminal-Bench | — | 44.3% |
| τ²-bench Banking | 37.1% | — |
| PostTrainBench | 31.7% | — |
| GBAEval | 0% | — |
| Vending-Bench 2 | 8,314 | — |
Reasoning GLM-5.2 leads
GLM-5.2: 42.1 (#46), GPT-5-Codex: 30.0 (#80)
| Benchmark | GLM-5.2 | GPT-5-Codex |
|---|---|---|
| Kagi LLM Benchmark | 62.6% | 70.3% |
| ARC-AGI-2 | 22.8% | — |
| SimpleBench | 58.8% | — |
| NYT Connections (extended) | 74.3% | — |
| ARC-AGI-1 | 77% | — |
| CritPt | 20.9% | — |
| Chess Puzzles | 21% | — |
| EBR-Bench | 9.5% | — |
| LMArena Hard Prompts | 1480 | — |
| Mystery Game Puzzles | 19% | — |
| DTBench | 93.6% | — |
| LMCA | 45.8% | — |
| Surface Evolver Bench | 55.6% | — |
| Epoch Capabilities Index | 151.76 | — |
Math Not comparable
GLM-5.2: 55.4 (#35), GPT-5-Codex: —
| Benchmark | GLM-5.2 | GPT-5-Codex |
|---|---|---|
| FrontierMath (Tiers 1-3) | 59.2% | — |
| FrontierMath Tier 4 | 29.3% | — |
| MathArena Final-Answer Competitions | 67.6% | — |
| OTIS Mock AIME 2024-2025 | 86.4% | — |
| ProofBench | 35% | — |
| LMArena Math | 1482 | — |
Knowledge Not comparable
GLM-5.2: 57.1 (#36), GPT-5-Codex: —
| Benchmark | GLM-5.2 | GPT-5-Codex |
|---|---|---|
| GPQA Diamond | 91.9% | — |
| SimpleQA Verified | 34.2% | — |
| LMArena Expert | 1484 | — |
Multilingual Not comparable
GLM-5.2: 56.0 (#25), GPT-5-Codex: —
| Benchmark | GLM-5.2 | GPT-5-Codex |
|---|---|---|
| LMArena Non-English | 1459 | — |
| LMArena Chinese | 1518 | — |
| LMArena French | 1476 | — |
| LMArena German | 1470 | — |
| LMArena Japanese | 1451 | — |
| LMArena Korean | 1445 | — |
| LMArena Russian | 1467 | — |
| LMArena Spanish | 1477 | — |
Instruction Following Not comparable
GLM-5.2: 77.1 (#32), GPT-5-Codex: —
| Benchmark | GLM-5.2 | GPT-5-Codex |
|---|---|---|
| LMArena Instruction Following | 1465 | — |
Long Context Not comparable
GLM-5.2: 45.3 (#43), GPT-5-Codex: —
| Benchmark | GLM-5.2 | GPT-5-Codex |
|---|---|---|
| LMArena Longer Query | 1479 | — |
Writing & Preference Not comparable
GLM-5.2: 70.7 (#20), GPT-5-Codex: —
| Benchmark | GLM-5.2 | GPT-5-Codex |
|---|---|---|
| LMArena Text | 1470 | — |
| LMArena Creative Writing | 1465 | — |
| EQ-Bench Creative Writing | 1757 | — |
| EQ-Bench 4 | 1222 | — |
| LMArena Multi-Turn | 1468 | — |
Frequently asked questions
Is GLM-5.2 better than GPT-5-Codex?
GLM-5.2 is the stronger model overall, scoring 50.9 to 37.3 on the Noometry Index.
Which is cheaper, GLM-5.2 or GPT-5-Codex?
GLM-5.2 is cheaper. It lists at $1.40 per million input tokens and $4.40 per million output tokens; GPT-5-Codex lists at $1.25 and $10.
Is GLM-5.2 or GPT-5-Codex better for coding?
GLM-5.2 scores higher on coding benchmarks: 50.9 versus 41.9 in the Noometry coding category.
Which has the bigger context window?
GLM-5.2 does, with 1M tokens against 400K.
How many benchmarks do GLM-5.2 and GPT-5-Codex share?
2 benchmarks have published results for both models. GLM-5.2 has 50 scored results on Noometry and GPT-5-Codex has 3.