Model comparison
Gemini 1.5 Flash (May 2024) vs GLM-5.2
GLM-5.2 is the stronger model overall, scoring 50.9 to 32.9 on the Noometry Index.
Last verified . 22 shared benchmarks.
GoogleSummary
- They share 22 benchmarks with published results for both. Gemini 1.5 Flash (May 2024) scores higher in 0 categories and GLM-5.2 in 9 categories; 9 gaps are clear of the uncertainty.
- The widest gap is in math, where GLM-5.2 leads 55.4 to 20.8.
- The biggest single-benchmark swing is OTIS Mock AIME 2024-2025: 16.3% for Gemini 1.5 Flash (May 2024) and 86.4% for GLM-5.2.
- GLM-5.2 has downloadable open weights; the other is API-only.
Side by side
| Gemini 1.5 Flash (May 2024) | GLM-5.2 | |
|---|---|---|
| Provider | Z.ai (Zhipu) | |
| Noometry Index | 32.9 | 50.9 |
| Released | 2024-05-14 | 2026-06-13 |
| Weights | Proprietary | Open |
| Context window | — | 1M |
| Max output | — | 131K |
| Input $ / M tokens | — | $1.40 |
| Output $ / M tokens | — | $4.40 |
| Results tracked | 42 | 50 |
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Category by category
Coding GLM-5.2 leads
Gemini 1.5 Flash (May 2024): 33.9 (#233), GLM-5.2: 50.9 (#37)
| Benchmark | Gemini 1.5 Flash (May 2024) | GLM-5.2 |
|---|---|---|
| WeirdML | 24.9% | 70.1% |
| LMArena Coding | 1262 | 1484 |
| SWE-bench Verified | — | 78.7% |
| DeepSWE | — | 43.8% |
| FrontierCode | — | 24.5% |
| LMArena WebDev | — | 1604 |
| SciCode | — | 50.5% |
| BigCodeBench Instruct | 43.5% | — |
| BigCodeBench Complete | 55.1% | — |
| ALE-Bench | — | 1,047 |
| HumanEval+ | 75.6% | — |
| MBPP+ | 67.5% | — |
Agentic & Tool Use GLM-5.2 leads
Gemini 1.5 Flash (May 2024): 26.3 (#97), GLM-5.2: 31.6 (#63)
| Benchmark | Gemini 1.5 Flash (May 2024) | GLM-5.2 |
|---|---|---|
| τ²-bench Banking | — | 37.1% |
| PostTrainBench | — | 31.7% |
| BALROG | 14.6% | — |
| GBAEval | — | 0% |
| Vending-Bench 2 | — | 8,314 |
Reasoning GLM-5.2 leads
Gemini 1.5 Flash (May 2024): 20.8 (#212), GLM-5.2: 42.1 (#46)
| Benchmark | Gemini 1.5 Flash (May 2024) | GLM-5.2 |
|---|---|---|
| LMArena Hard Prompts | 1257 | 1480 |
| DTBench | 53.8% | 93.6% |
| Epoch Capabilities Index | 129.37 | 151.76 |
| ARC-AGI-2 | — | 22.8% |
| SimpleBench | — | 58.8% |
| Kagi LLM Benchmark | — | 62.6% |
| NYT Connections (extended) | — | 74.3% |
| ARC-AGI-1 | — | 77% |
| CritPt | — | 20.9% |
| Chess Puzzles | — | 21% |
| EBR-Bench | — | 9.5% |
| Mystery Game Puzzles | — | 19% |
| LMCA | — | 45.8% |
| Surface Evolver Bench | — | 55.6% |
| ForecastBench | 53.9 | — |
| PIQA | 87.5% | — |
Math GLM-5.2 leads
Gemini 1.5 Flash (May 2024): 20.8 (#274), GLM-5.2: 55.4 (#35)
| Benchmark | Gemini 1.5 Flash (May 2024) | GLM-5.2 |
|---|---|---|
| OTIS Mock AIME 2024-2025 | 16.3% | 86.4% |
| LMArena Math | 1269 | 1482 |
| FrontierMath (Tiers 1-3) | — | 59.2% |
| FrontierMath Tier 4 | — | 29.3% |
| MathArena Final-Answer Competitions | — | 67.6% |
| ProofBench | — | 35% |
| Omni-MATH | 30.4% | — |
| MATH Level 5 | 61.9% | — |
| FrontierMath (Feb 2025 set) | 0% | — |
| GSM8K | 82.4% | — |
Knowledge GLM-5.2 leads
Gemini 1.5 Flash (May 2024): 26.2 (#253), GLM-5.2: 57.1 (#36)
| Benchmark | Gemini 1.5 Flash (May 2024) | GLM-5.2 |
|---|---|---|
| GPQA Diamond | 47.3% | 91.9% |
| LMArena Expert | 1233 | 1484 |
| SimpleQA Verified | — | 34.2% |
| MMLU-Pro | 67.8% | — |
| GPQA (HELM) | 43.7% | — |
| BoolQ | 85.8% | — |
| MMLU | 77.9% | — |
Multimodal Not comparable
Gemini 1.5 Flash (May 2024): 35.3 (#76), GLM-5.2: —
| Benchmark | Gemini 1.5 Flash (May 2024) | GLM-5.2 |
|---|---|---|
| LMArena Vision | 1141 | — |
| Video-MME | 70.3% | — |
| GeoBench | 76% | — |
Multilingual GLM-5.2 leads
Gemini 1.5 Flash (May 2024): 43.1 (#184), GLM-5.2: 56.0 (#25)
| Benchmark | Gemini 1.5 Flash (May 2024) | GLM-5.2 |
|---|---|---|
| LMArena Non-English | 1278 | 1459 |
| LMArena Chinese | 1295 | 1518 |
| LMArena French | 1257 | 1476 |
| LMArena German | 1262 | 1470 |
| LMArena Japanese | 1252 | 1451 |
| LMArena Korean | 1220 | 1445 |
| LMArena Russian | 1288 | 1467 |
| LMArena Spanish | 1242 | 1477 |
Instruction Following GLM-5.2 leads
Gemini 1.5 Flash (May 2024): 67.0 (#199), GLM-5.2: 77.1 (#32)
| Benchmark | Gemini 1.5 Flash (May 2024) | GLM-5.2 |
|---|---|---|
| LMArena Instruction Following | 1258 | 1465 |
| IFEval | 83.1% | — |
Long Context GLM-5.2 leads
Gemini 1.5 Flash (May 2024): 39.0 (#182), GLM-5.2: 45.3 (#43)
| Benchmark | Gemini 1.5 Flash (May 2024) | GLM-5.2 |
|---|---|---|
| LMArena Longer Query | 1284 | 1479 |
Writing & Preference GLM-5.2 leads
Gemini 1.5 Flash (May 2024): 48.9 (#190), GLM-5.2: 70.7 (#20)
| Benchmark | Gemini 1.5 Flash (May 2024) | GLM-5.2 |
|---|---|---|
| LMArena Text | 1287 | 1470 |
| LMArena Creative Writing | 1285 | 1465 |
| LMArena Multi-Turn | 1253 | 1468 |
| EQ-Bench Creative Writing | — | 1757 |
| WildBench | 79.2% | — |
| EQ-Bench 4 | — | 1222 |
Frequently asked questions
Is Gemini 1.5 Flash (May 2024) better than GLM-5.2?
GLM-5.2 is the stronger model overall, scoring 50.9 to 32.9 on the Noometry Index.
Is Gemini 1.5 Flash (May 2024) or GLM-5.2 better for coding?
GLM-5.2 scores higher on coding benchmarks: 50.9 versus 33.9 in the Noometry coding category.
How many benchmarks do Gemini 1.5 Flash (May 2024) and GLM-5.2 share?
22 benchmarks have published results for both models. Gemini 1.5 Flash (May 2024) has 42 scored results on Noometry and GLM-5.2 has 50.