Model comparison
Gemma 3n E4b IT vs GLM-5.2
GLM-5.2 is the stronger model overall, scoring 50.9 to 36.7 on the Noometry Index. Gemma 3n E4b IT costs 29× less per token, which makes it the better buy when GLM-5.2's lead doesn't matter for your workload.
Last verified . 18 shared benchmarks.
GoogleSummary
- They share 18 benchmarks with published results for both. Gemma 3n E4b IT scores higher in 0 categories and GLM-5.2 in 8 categories; 8 gaps are clear of the uncertainty.
- The widest gap is in knowledge, where GLM-5.2 leads 57.1 to 33.6.
- The biggest single-benchmark swing is Kagi LLM Benchmark: 31.5% for Gemma 3n E4b IT and 62.6% for GLM-5.2.
- Gemma 3n E4b IT is cheaper at $0.06 / $0.12 per million input/output tokens, against $1.40 / $4.40 for GLM-5.2.
- GLM-5.2 accepts more context: 1M tokens versus 33K.
Side by side
| Gemma 3n E4b IT | GLM-5.2 | |
|---|---|---|
| Provider | Z.ai (Zhipu) | |
| Noometry Index | 36.7 | 50.9 |
| Released | 2025-05-20 | 2026-06-13 |
| Weights | Open | Open |
| Context window | 33K | 1M |
| Max output | 33K | 131K |
| Input $ / M tokens | $0.06 | $1.40 |
| Output $ / M tokens | $0.12 | $4.40 |
| Results tracked | 18 | 50 |
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Category by category
Coding GLM-5.2 leads
Gemma 3n E4b IT: 36.4 (#193), GLM-5.2: 50.9 (#37)
| Benchmark | Gemma 3n E4b IT | GLM-5.2 |
|---|---|---|
| LMArena Coding | 1269 | 1484 |
| SWE-bench Verified | — | 78.7% |
| DeepSWE | — | 43.8% |
| FrontierCode | — | 24.5% |
| LMArena WebDev | — | 1604 |
| SciCode | — | 50.5% |
| WeirdML | — | 70.1% |
| ALE-Bench | — | 1,047 |
Agentic & Tool Use Not comparable
Gemma 3n E4b IT: —, GLM-5.2: 31.6 (#63)
| Benchmark | Gemma 3n E4b IT | GLM-5.2 |
|---|---|---|
| τ²-bench Banking | — | 37.1% |
| PostTrainBench | — | 31.7% |
| GBAEval | — | 0% |
| Vending-Bench 2 | — | 8,314 |
Reasoning GLM-5.2 leads
Gemma 3n E4b IT: 19.2 (#239), GLM-5.2: 42.1 (#46)
| Benchmark | Gemma 3n E4b IT | GLM-5.2 |
|---|---|---|
| Kagi LLM Benchmark | 31.5% | 62.6% |
| LMArena Hard Prompts | 1284 | 1480 |
| 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% |
| Mystery Game Puzzles | — | 19% |
| DTBench | — | 93.6% |
| LMCA | — | 45.8% |
| Surface Evolver Bench | — | 55.6% |
| Epoch Capabilities Index | — | 151.76 |
Math GLM-5.2 leads
Gemma 3n E4b IT: 32.5 (#186), GLM-5.2: 55.4 (#35)
| Benchmark | Gemma 3n E4b IT | GLM-5.2 |
|---|---|---|
| LMArena Math | 1251 | 1482 |
| 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% |
Knowledge GLM-5.2 leads
Gemma 3n E4b IT: 33.6 (#193), GLM-5.2: 57.1 (#36)
| Benchmark | Gemma 3n E4b IT | GLM-5.2 |
|---|---|---|
| LMArena Expert | 1245 | 1484 |
| GPQA Diamond | — | 91.9% |
| SimpleQA Verified | — | 34.2% |
Multilingual GLM-5.2 leads
Gemma 3n E4b IT: 43.5 (#179), GLM-5.2: 56.0 (#25)
| Benchmark | Gemma 3n E4b IT | GLM-5.2 |
|---|---|---|
| LMArena Non-English | 1285 | 1459 |
| LMArena Chinese | 1310 | 1518 |
| LMArena French | 1330 | 1476 |
| LMArena German | 1312 | 1470 |
| LMArena Japanese | 1274 | 1451 |
| LMArena Korean | 1259 | 1445 |
| LMArena Russian | 1288 | 1467 |
| LMArena Spanish | 1305 | 1477 |
Instruction Following GLM-5.2 leads
Gemma 3n E4b IT: 66.3 (#205), GLM-5.2: 77.1 (#32)
| Benchmark | Gemma 3n E4b IT | GLM-5.2 |
|---|---|---|
| LMArena Instruction Following | 1255 | 1465 |
Long Context GLM-5.2 leads
Gemma 3n E4b IT: 38.8 (#185), GLM-5.2: 45.3 (#43)
| Benchmark | Gemma 3n E4b IT | GLM-5.2 |
|---|---|---|
| LMArena Longer Query | 1277 | 1479 |
Writing & Preference GLM-5.2 leads
Gemma 3n E4b IT: 50.3 (#181), GLM-5.2: 70.7 (#20)
| Benchmark | Gemma 3n E4b IT | GLM-5.2 |
|---|---|---|
| LMArena Text | 1306 | 1470 |
| LMArena Creative Writing | 1287 | 1465 |
| LMArena Multi-Turn | 1276 | 1468 |
| EQ-Bench Creative Writing | — | 1757 |
| EQ-Bench 4 | — | 1222 |
Frequently asked questions
Is Gemma 3n E4b IT better than GLM-5.2?
GLM-5.2 is the stronger model overall, scoring 50.9 to 36.7 on the Noometry Index. Gemma 3n E4b IT costs 29× less per token, which makes it the better buy when GLM-5.2's lead doesn't matter for your workload.
Which is cheaper, Gemma 3n E4b IT or GLM-5.2?
Gemma 3n E4b IT is cheaper. It lists at $0.06 per million input tokens and $0.12 per million output tokens; GLM-5.2 lists at $1.40 and $4.40.
Is Gemma 3n E4b IT or GLM-5.2 better for coding?
GLM-5.2 scores higher on coding benchmarks: 50.9 versus 36.4 in the Noometry coding category.
Which has the bigger context window?
GLM-5.2 does, with 1M tokens against 33K.
How many benchmarks do Gemma 3n E4b IT and GLM-5.2 share?
18 benchmarks have published results for both models. Gemma 3n E4b IT has 18 scored results on Noometry and GLM-5.2 has 50.