Model comparison
Gemini 2.5 Flash-Lite vs GLM-5.3
GLM-5.3 is the stronger model overall, scoring 54.8 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-5.3's lead doesn't matter for your workload.
Last verified . 22 shared benchmarks.
GoogleSummary
- They share 22 benchmarks with published results for both. Gemini 2.5 Flash-Lite scores higher in 0 categories and GLM-5.3 in 9 categories; 9 gaps are clear of the uncertainty.
- The widest gap is in knowledge, where GLM-5.3 leads 58.3 to 32.5.
- The biggest single-benchmark swing is WeirdML: 35.2% for Gemini 2.5 Flash-Lite and 75.4% for GLM-5.3.
- Gemini 2.5 Flash-Lite is cheaper at $0.10 / $0.40 per million input/output tokens, against $1.40 / $4.40 for GLM-5.3.
- Gemini 2.5 Flash-Lite accepts more context: 1.05M tokens versus 1M.
- GLM-5.3 has downloadable open weights; the other is API-only.
Side by side
| Gemini 2.5 Flash-Lite | GLM-5.3 | |
|---|---|---|
| Provider | Z.ai (Zhipu) | |
| Noometry Index | 37.0 | 54.8 |
| Released | 2025-06-17 | 2026-08-14 |
| 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 | 42 |
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Category by category
Coding GLM-5.3 leads
Gemini 2.5 Flash-Lite: 38.5 (#173), GLM-5.3: 59.5 (#14)
| Benchmark | Gemini 2.5 Flash-Lite | GLM-5.3 |
|---|---|---|
| WeirdML | 35.2% | 75.4% |
| LMArena Coding | 1373 | 1496 |
| ALE-Bench | 325.9 | 1,317 |
| DeepSWE | — | 69% |
| FrontierCode | — | 40.1% |
| CursorBench | — | 42.6% |
| LMArena WebDev | — | 1622 |
| FrontierSWE | — | 30.2% |
| SciCode | — | 59% |
Agentic & Tool Use GLM-5.3 leads
Gemini 2.5 Flash-Lite: 28.0 (#96), GLM-5.3: 36.4 (#38)
| Benchmark | Gemini 2.5 Flash-Lite | GLM-5.3 |
|---|---|---|
| APEX-Agents | — | 56.6% |
| Berkeley Function Calling Leaderboard | 36.9% | — |
| Vending-Bench 2 | — | 8,164 |
Reasoning GLM-5.3 leads
Gemini 2.5 Flash-Lite: 22.2 (#205), GLM-5.3: 46.1 (#46)
| Benchmark | Gemini 2.5 Flash-Lite | GLM-5.3 |
|---|---|---|
| LMArena Hard Prompts | 1377 | 1489 |
| DTBench | 62.8% | 87.7% |
| LMCA | 18.1% | 55.5% |
| Epoch Capabilities Index | 133.94 | 155.61 |
| Kagi LLM Benchmark | 40.5% | — |
| NYT Connections (extended) | — | 74.2% |
| CritPt | — | 19.1% |
| Chess Puzzles | — | 21% |
| Mystery Game Puzzles | — | 33% |
| Bench to the Future 3 | — | 0.15 |
Math GLM-5.3 leads
Gemini 2.5 Flash-Lite: 38.0 (#144), GLM-5.3: 62.3 (#33)
| Benchmark | Gemini 2.5 Flash-Lite | GLM-5.3 |
|---|---|---|
| LMArena Math | 1373 | 1489 |
| FrontierMath (Tiers 1-3) | — | 68.8% |
| FrontierMath Tier 4 | — | 29.3% |
| OTIS Mock AIME 2024-2025 | — | 91.1% |
| ProofBench | — | 49% |
| Omni-MATH | 48% | — |
Knowledge GLM-5.3 leads
Gemini 2.5 Flash-Lite: 32.5 (#210), GLM-5.3: 58.3 (#37)
| Benchmark | Gemini 2.5 Flash-Lite | GLM-5.3 |
|---|---|---|
| LMArena Expert | 1373 | 1516 |
| GPQA Diamond | — | 90.9% |
| SimpleQA Verified | — | 41% |
| 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-5.3: —
| Benchmark | Gemini 2.5 Flash-Lite | GLM-5.3 |
|---|---|---|
| LMArena Vision | 1198 | — |
| VPCT | 30% | — |
Multilingual GLM-5.3 leads
Gemini 2.5 Flash-Lite: 49.3 (#134), GLM-5.3: 55.7 (#28)
| Benchmark | Gemini 2.5 Flash-Lite | GLM-5.3 |
|---|---|---|
| LMArena Non-English | 1369 | 1457 |
| LMArena Chinese | 1404 | 1528 |
| LMArena French | 1388 | 1499 |
| LMArena German | 1389 | 1499 |
| LMArena Japanese | 1359 | 1453 |
| LMArena Korean | 1360 | 1472 |
| LMArena Russian | 1373 | 1463 |
| LMArena Spanish | 1396 | 1460 |
Instruction Following GLM-5.3 leads
Gemini 2.5 Flash-Lite: 70.0 (#168), GLM-5.3: 77.5 (#23)
| Benchmark | Gemini 2.5 Flash-Lite | GLM-5.3 |
|---|---|---|
| LMArena Instruction Following | 1367 | 1477 |
| IFEval | 81% | — |
Long Context GLM-5.3 leads
Gemini 2.5 Flash-Lite: 33.3 (#262), GLM-5.3: 45.4 (#41)
| Benchmark | Gemini 2.5 Flash-Lite | GLM-5.3 |
|---|---|---|
| LMArena Longer Query | 1373 | 1482 |
| Fiction.LiveBench | 47.2% | — |
Writing & Preference GLM-5.3 leads
Gemini 2.5 Flash-Lite: 56.8 (#135), GLM-5.3: 75.7 (#6)
| Benchmark | Gemini 2.5 Flash-Lite | GLM-5.3 |
|---|---|---|
| LMArena Text | 1379 | 1471 |
| LMArena Creative Writing | 1367 | 1457 |
| LMArena Multi-Turn | 1366 | 1472 |
| EQ-Bench Creative Writing | — | 2075 |
| WildBench | 81.8% | — |
Frequently asked questions
Is Gemini 2.5 Flash-Lite better than GLM-5.3?
GLM-5.3 is the stronger model overall, scoring 54.8 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-5.3's lead doesn't matter for your workload.
Which is cheaper, Gemini 2.5 Flash-Lite or GLM-5.3?
Gemini 2.5 Flash-Lite is cheaper. It lists at $0.10 per million input tokens and $0.40 per million output tokens; GLM-5.3 lists at $1.40 and $4.40.
Is Gemini 2.5 Flash-Lite or GLM-5.3 better for coding?
GLM-5.3 scores higher on coding benchmarks: 59.5 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-5.3 share?
22 benchmarks have published results for both models. Gemini 2.5 Flash-Lite has 33 scored results on Noometry and GLM-5.3 has 42.