Model comparison
Gemini 2.5 Flash-Lite vs GLM-5.2
GLM-5.2 is the stronger model overall, scoring 51.1 to 37.0 on the Noometry Index. Gemini 2.5 Flash-Lite costs 12× less per token, which makes it the better buy when GLM-5.2's lead doesn't matter for your workload.
Last verified . 23 shared benchmarks.
GoogleSummary
- They share 23 benchmarks with published results for both. Gemini 2.5 Flash-Lite scores higher in 0 categories and GLM-5.2 in 9 categories; 9 gaps are clear of the uncertainty.
- The widest gap is in knowledge, where GLM-5.2 leads 57.1 to 32.5.
- The biggest single-benchmark swing is WeirdML: 35.2% for Gemini 2.5 Flash-Lite and 70.1% for GLM-5.2.
- Gemini 2.5 Flash-Lite is cheaper at $0.10 / $0.40 per million input/output tokens, against $1.40 / $4.40 for GLM-5.2.
- Gemini 2.5 Flash-Lite accepts more context: 1.05M tokens versus 1M.
- GLM-5.2 has downloadable open weights; the other is API-only.
Side by side
| Gemini 2.5 Flash-Lite | GLM-5.2 | |
|---|---|---|
| Provider | Z.ai (Zhipu) | |
| Noometry Index | 37.0 | 51.1 |
| Released | 2025-06-17 | 2026-06-13 |
| Weights | Proprietary | Open |
| Context window | 1.05M | 1M |
| Max output | 66K | 131K |
| Input $ / M tokens | $0.10 | $1.40 |
| Output $ / M tokens | $0.40 | $4.40 |
| Results tracked | 33 | 51 |
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Category by category
Coding GLM-5.2 leads
Gemini 2.5 Flash-Lite: 38.5 (#173), GLM-5.2: 51.3 (#41)
| Benchmark | Gemini 2.5 Flash-Lite | GLM-5.2 |
|---|---|---|
| WeirdML | 35.2% | 70.1% |
| LMArena Coding | 1373 | 1485 |
| ALE-Bench | 325.9 | 1,047 |
| SWE-bench Verified | — | 78.7% |
| DeepSWE | — | 43.8% |
| FrontierCode | — | 24.5% |
| LMArena WebDev | — | 1603 |
| SciCode | — | 50.5% |
Agentic & Tool Use GLM-5.2 leads
Gemini 2.5 Flash-Lite: 28.0 (#96), GLM-5.2: 32.4 (#63)
| Benchmark | Gemini 2.5 Flash-Lite | GLM-5.2 |
|---|---|---|
| APEX-Agents | — | 45.2% |
| Berkeley Function Calling Leaderboard | 36.9% | — |
| τ²-bench Banking | — | 37.1% |
| PostTrainBench | — | 31.7% |
| GBAEval | — | 0% |
| Vending-Bench 2 | — | 8,314 |
Reasoning GLM-5.2 leads
Gemini 2.5 Flash-Lite: 22.2 (#205), GLM-5.2: 42.3 (#52)
| Benchmark | Gemini 2.5 Flash-Lite | GLM-5.2 |
|---|---|---|
| Kagi LLM Benchmark | 40.5% | 62.6% |
| LMArena Hard Prompts | 1377 | 1480 |
| DTBench | 62.8% | 93.6% |
| LMCA | 18.1% | 45.8% |
| Epoch Capabilities Index | 133.94 | 151.78 |
| 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% |
| Surface Evolver Bench | — | 55.6% |
Math GLM-5.2 leads
Gemini 2.5 Flash-Lite: 38.0 (#144), GLM-5.2: 55.7 (#43)
| Benchmark | Gemini 2.5 Flash-Lite | GLM-5.2 |
|---|---|---|
| LMArena Math | 1373 | 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% |
| Omni-MATH | 48% | — |
Knowledge GLM-5.2 leads
Gemini 2.5 Flash-Lite: 32.5 (#210), GLM-5.2: 57.1 (#40)
| Benchmark | Gemini 2.5 Flash-Lite | GLM-5.2 |
|---|---|---|
| LMArena Expert | 1373 | 1486 |
| GPQA Diamond | — | 91.9% |
| SimpleQA Verified | — | 34.2% |
| MMLU-Pro | 53.7% | — |
| Vectara Hallucination Rate | 3.3% | — |
| GPQA (HELM) | 30.9% | — |
Multimodal Not comparable
Gemini 2.5 Flash-Lite: 29.1 (#114), GLM-5.2: —
| Benchmark | Gemini 2.5 Flash-Lite | GLM-5.2 |
|---|---|---|
| LMArena Vision | 1198 | — |
| VPCT | 30% | — |
Multilingual GLM-5.2 leads
Gemini 2.5 Flash-Lite: 49.3 (#134), GLM-5.2: 55.8 (#26)
| Benchmark | Gemini 2.5 Flash-Lite | GLM-5.2 |
|---|---|---|
| LMArena Non-English | 1369 | 1459 |
| LMArena Chinese | 1404 | 1519 |
| LMArena French | 1388 | 1479 |
| LMArena German | 1389 | 1468 |
| LMArena Japanese | 1359 | 1451 |
| LMArena Korean | 1360 | 1445 |
| LMArena Russian | 1373 | 1466 |
| LMArena Spanish | 1396 | 1477 |
Instruction Following GLM-5.2 leads
Gemini 2.5 Flash-Lite: 70.0 (#168), GLM-5.2: 76.9 (#34)
| Benchmark | Gemini 2.5 Flash-Lite | GLM-5.2 |
|---|---|---|
| LMArena Instruction Following | 1367 | 1465 |
| IFEval | 81% | — |
Long Context GLM-5.2 leads
Gemini 2.5 Flash-Lite: 33.3 (#262), GLM-5.2: 45.3 (#43)
| Benchmark | Gemini 2.5 Flash-Lite | GLM-5.2 |
|---|---|---|
| LMArena Longer Query | 1373 | 1479 |
| Fiction.LiveBench | 47.2% | — |
Writing & Preference GLM-5.2 leads
Gemini 2.5 Flash-Lite: 56.8 (#135), GLM-5.2: 70.4 (#21)
| Benchmark | Gemini 2.5 Flash-Lite | GLM-5.2 |
|---|---|---|
| LMArena Text | 1379 | 1470 |
| LMArena Creative Writing | 1367 | 1462 |
| LMArena Multi-Turn | 1366 | 1469 |
| EQ-Bench Creative Writing | — | 1757 |
| WildBench | 81.8% | — |
| EQ-Bench 4 | — | 1222 |
Frequently asked questions
Is Gemini 2.5 Flash-Lite better than GLM-5.2?
GLM-5.2 is the stronger model overall, scoring 51.1 to 37.0 on the Noometry Index. Gemini 2.5 Flash-Lite costs 12× less per token, which makes it the better buy when GLM-5.2's lead doesn't matter for your workload.
Which is cheaper, Gemini 2.5 Flash-Lite or GLM-5.2?
Gemini 2.5 Flash-Lite is cheaper. It lists at $0.10 per million input tokens and $0.40 per million output tokens; GLM-5.2 lists at $1.40 and $4.40.
Is Gemini 2.5 Flash-Lite or GLM-5.2 better for coding?
GLM-5.2 scores higher on coding benchmarks: 51.3 versus 38.5 in the Noometry coding category.
Which has the bigger context window?
Gemini 2.5 Flash-Lite does, with 1.05M tokens against 1M.
How many benchmarks do Gemini 2.5 Flash-Lite and GLM-5.2 share?
23 benchmarks have published results for both models. Gemini 2.5 Flash-Lite has 33 scored results on Noometry and GLM-5.2 has 51.