Gemini 3.5 Flash Lite vs GLM 5.2
GLM 5.2 leads Gemini 3.5 Flash Lite on coding, 61.1 to 49.0 on the Vibe Coding Index, and Gemini 3.5 Flash Lite costs 1.8x less per output token ($2.50 vs $4.40 per million). Updated October 22, 2026; 68 benchmarks have a result for both.
Gemini 3.5 Flash Lite or GLM 5.2: which to pick
Pick GLM 5.2 for coding: it scores 61.1 on the Vibe Coding Index against 49.0 for Gemini 3.5 Flash Lite.
Pick Gemini 3.5 Flash Lite for output tokens 1.8x cheaper ($2.50 vs $4.40 per million) and a lower cost per solved task ($0.41 against $0.86).
- Shared results
- 68
- Gemini 3.5 Flash Lite only
- 17
- GLM 5.2 only
- 30
- Like-for-like categories
- 7 of 9
Only benchmarks that tested both models count toward a pick; a result only one model has is shown but not compared.
Which one for your work
Each card is decided by one number both models carry. Where only one has it, the card says so and makes no call.
Coding
Vibe Coding Index, six public coding benchmarks
GLM 5.2
GLM 5.2 scores 61.1 against 49.0.
3 and 4 benchmarks behind the scores
Intelligence
AA Intelligence Index
GLM 5.2
GLM 5.2 leads, 33.7 against 22.2.
Same board, both measured
Agentic work
AA Agentic Index
GLM 5.2
GLM 5.2 leads, 38.4 against 14.3.
Same board, both measured
Reasoning
GPQA Diamond
GLM 5.2
GLM 5.2 leads, 85.6% against 83.8%.
Same board, both measured
Knowledge
MMLU Pro
GLM 5.2
GLM 5.2 leads, 86.7% against 85.8%.
Same board, both measured
Web design
Design Arena: websites
No call
Only GLM 5.2 has a Design Arena: websites result, 1285.
Directional only
Long documents
Listed context window
No call
Both take 1.05M tokens.
Listed by OpenRouter
Everyday cost
1K input + 500 output tokens
Gemini 3.5 Flash Lite
Gemini 3.5 Flash Lite $0.0015, GLM 5.2 $0.0036 per turn.
List prices
Cost per solved task
One SWE-bench Verified task, solved
Gemini 3.5 Flash Lite
Gemini 3.5 Flash Lite $0.41, GLM 5.2 $0.86.
Published attempt cost and pass rate
At a glance
- Coding index
- Gemini 3.5 Flash Lite 49.0 from 3 benchmarks, GLM 5.2 61.1 from 4 benchmarks.
- Widest category
- Math, 19.5 points apart on average over 6 shared benchmarks.
- Widest single gap
- FrontierMath, tiers 1 to 3: Gemini 3.5 Flash Lite 26.0% against GLM 5.2 59.2%, 33.2 points apart on a 0 to 100 scale.
- Output price
- Gemini 3.5 Flash Lite $2.50 against GLM 5.2 $4.40 per million output tokens, 1.8x apart.
- Context window
- Both take 1.05M tokens.
Benchmark by benchmark
First the score: boards each model leads, per category, where both have a result. Then every board, a category to a fold; bars are each result on a 0 to 100 scale, so compare the two in a row, not one row with another.
| Category | Gemini 3.5 Flash Lite | Bars | GLM 5.2 | Ties |
|---|---|---|---|---|
| Coding | 1 | 13 | ||
| Intelligence | 0 | 2 | ||
| Agentic work | 0 | 5 | ||
| Reasoning | 0 | 10 | 1 tie | |
| Math | 0 | 6 | ||
| Knowledge | 1 | 7 | 1 tie | |
| General | 0 | 21 | ||
| All shared boards | 2 | 64 | 2 ties |
CodingLike-for-likeSix of these boards feed the Vibe Coding Index113
| Benchmark | Gemini 3.5 Flash Lite | GLM 5.2 | Leader |
|---|---|---|---|
| LMArena WebDev | 1435 | 1604 | GLM 5.2 |
| AA Coding Index | 49.3 | 68.8 | GLM 5.2 |
| LiveCodeBench (Vals AI) | 79.0% | 69.5% | Gemini 3.5 Flash Lite |
| SWE-bench Verified (Vals AI) | 75.0% | 82.8% | GLM 5.2 |
| Vibe Code Bench (Vals AI) | 37.2% | 64.0% | GLM 5.2 |
| Code migration (Vals AI) | 6.2% | 37.9% | GLM 5.2 |
| ProgramBench (Vals AI) | 0.0% | 0.5% | GLM 5.2 |
| Terminal-Bench 2.1 (Vals AI) | 50.2% | 67.8% | GLM 5.2 |
| SkillsBench (Vals AI) | Not measured | 45.1% | Only GLM 5.2 measured |
| CyberBench (Vals AI) | 59.1% | Not measured | Only Gemini 3.5 Flash Lite measured |
| SciCode | 41.3% | 51.2% | GLM 5.2 |
| Terminal-Bench Hard (Artificial Analysis run) | Not measured | 50.8% | Only GLM 5.2 measured |
| FrontierCode | Not measured | 24.5% | Only GLM 5.2 measured |
| WeirdML | 39.0% | 70.1% | GLM 5.2 |
| ALE-Bench | 765.3 | 1047.0 | GLM 5.2 |
| LMArena Text: coding | 1453 | 1487 | GLM 5.2 |
| LMArena Text: software and IT | 1451 | 1486 | GLM 5.2 |
| LMArena WebDev: React | 1408 | 1617 | GLM 5.2 |
| LMArena WebDev: HTML | Not measured | 1565 | Only GLM 5.2 measured |
| LMArena WebDev: from an image | 1448 | Not measured | Only Gemini 3.5 Flash Lite measured |
| SciCode | 6.2% | Not measured | Only Gemini 3.5 Flash Lite measured |
| Neither model has a result on the other 18 boards here | |||
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index02
| Benchmark | Gemini 3.5 Flash Lite | GLM 5.2 | Leader |
|---|---|---|---|
| AA Intelligence Index | 22.2 | 33.7 | GLM 5.2 |
| Epoch Capabilities Index | 144.9 | 151.9 | GLM 5.2 |
Agentic workLike-for-likePublic boards, shown as published, kept out of the index05
| Benchmark | Gemini 3.5 Flash Lite | GLM 5.2 | Leader |
|---|---|---|---|
| AA Agentic Index | 14.3 | 38.4 | GLM 5.2 |
| Design Arena: agents building web apps | Not measured | 1222 | Only GLM 5.2 measured |
| Design Arena: agents building full-stack apps | Not measured | 1241 | Only GLM 5.2 measured |
| Design Arena: agents building mobile apps | Not measured | 1159 | Only GLM 5.2 measured |
| Design Arena: agents building Android apps | Not measured | 1178 | Only GLM 5.2 measured |
| Design Arena: agents building Godot games | Not measured | 1142 | Only GLM 5.2 measured |
| Design Arena: agents building games | Not measured | 1206 | Only GLM 5.2 measured |
| Design Arena: HTML slides | Not measured | 1125 | Only GLM 5.2 measured |
| Design Arena: PowerPoint slides | Not measured | 1170 | Only GLM 5.2 measured |
| SREBench (Vals AI) | Not measured | 0.0% | Only GLM 5.2 measured |
| Finance Agent (Vals AI) | 47.4% | 49.7% | GLM 5.2 |
| Tax Agent Bench (Vals AI) | 7.2% | Not measured | Only Gemini 3.5 Flash Lite measured |
| Legal Research Bench (Vals AI) | 13.9% | 31.3% | GLM 5.2 |
| Excel Modeling Benchmark (Vals AI) | 43.2% | 61.5% | GLM 5.2 |
| τ²-Bench Telecom | Not measured | 99.1% | Only GLM 5.2 measured |
| APEX-Agents | 29.3% | 45.2% | GLM 5.2 |
| PostTrainBench | Not measured | 31.7% | Only GLM 5.2 measured |
| Vending-Bench 2 | Not measured | $8,314 | Only GLM 5.2 measured |
| Neither model has a result on the other 23 boards here | |||
ReasoningLike-for-likePublic boards, shown as published, kept out of the index010
| Benchmark | Gemini 3.5 Flash Lite | GLM 5.2 | Leader |
|---|---|---|---|
| GPQA Diamond | 83.8% | 85.6% | GLM 5.2 |
| MMMU Pro (Vals AI) | 83.6% | Not measured | Only Gemini 3.5 Flash Lite measured |
| GPQA Diamond (Artificial Analysis run) | 83.8% | 89.5% | GLM 5.2 |
| Humanity's Last Exam (Artificial Analysis run) | 18.8% | 41.1% | GLM 5.2 |
| GPQA Diamond (Epoch AI run) | 83.3% | 91.9% | GLM 5.2 |
| ARC-AGI | 53.5% | 77.0% | GLM 5.2 |
| ARC-AGI-2 | 10.3% | 22.8% | GLM 5.2 |
| SimpleBench | Not measured | 58.8% | Only GLM 5.2 measured |
| Chess puzzles | 21.0% | 22.0% | GLM 5.2 |
| Mystery game puzzles | 19.0% | 19.0% | Tie |
| EBR-bench | Not measured | 9.5% | Only GLM 5.2 measured |
| LMArena Text: hard prompts | 1441 | 1481 | GLM 5.2 |
| LMArena Text: expert | 1434 | 1487 | GLM 5.2 |
| LMArena Text: hard prompts in English | 1440 | 1481 | GLM 5.2 |
| LMArena Vision: diagrams | 1284 | Not measured | Only Gemini 3.5 Flash Lite measured |
| LMArena Vision: homework | 1291 | Not measured | Only Gemini 3.5 Flash Lite measured |
| Kagi LLM Benchmark | Not measured | 62.6% | Only GLM 5.2 measured |
| Neither model has a result on the other 5 boards here | |||
MathLike-for-likePublic boards, shown as published, kept out of the index06
| Benchmark | Gemini 3.5 Flash Lite | GLM 5.2 | Leader |
|---|---|---|---|
| OTIS Mock AIME | 71.1% | 86.4% | GLM 5.2 |
| FrontierMath, tiers 1 to 3 | 26.0% | 59.2% | GLM 5.2 |
| FrontierMath, tier 4 | 0.0% | 29.3% | GLM 5.2 |
| ProofBench | 13.0% | 35.0% | GLM 5.2 |
| LMArena Text: math | 1434 | 1483 | GLM 5.2 |
| LMArena Text: mathematical work | 1433 | 1489 | GLM 5.2 |
| Neither model has a result on the other 7 boards here | |||
KnowledgeLike-for-likePublic boards, shown as published, kept out of the index17
| Benchmark | Gemini 3.5 Flash Lite | GLM 5.2 | Leader |
|---|---|---|---|
| MMLU Pro | 85.8% | 86.7% | GLM 5.2 |
| LegalBench (Vals AI) | 84.1% | 84.1% | Tie |
| CorpFin (Vals AI) | 60.7% | 66.1% | GLM 5.2 |
| TaxEval (Vals AI) | 72.6% | 73.3% | GLM 5.2 |
| MortgageTax (Vals AI) | 68.7% | Not measured | Only Gemini 3.5 Flash Lite measured |
| MedCode (Vals AI) | 43.5% | 40.8% | Gemini 3.5 Flash Lite |
| SimpleQA Verified | Not measured | 34.2% | Only GLM 5.2 measured |
| LMArena Text: science | 1451 | 1489 | GLM 5.2 |
| LMArena Text: medicine and healthcare | 1438 | 1475 | GLM 5.2 |
| LMArena Text: legal and government | 1431 | 1486 | GLM 5.2 |
| LMArena Text: business and finance | 1423 | 1451 | GLM 5.2 |
| FACTS Benchmark Suite | 53.5% | Not measured | Only Gemini 3.5 Flash Lite measured |
| Neither model has a result on the other 6 boards here | |||
Web designDirectional onlyPublic boards, shown as published, kept out of the index8 boards, none shared
| Benchmark | Gemini 3.5 Flash Lite | GLM 5.2 | Leader |
|---|---|---|---|
| Design Arena: websites | Not measured | 1285 | Only GLM 5.2 measured |
| Design Arena: UI components | Not measured | 1294 | Only GLM 5.2 measured |
| Design Arena: game dev | Not measured | 1268 | Only GLM 5.2 measured |
| Design Arena: data viz | Not measured | 1285 | Only GLM 5.2 measured |
| Design Arena: 3D | Not measured | 1287 | Only GLM 5.2 measured |
| Design Arena: all code categories | Not measured | 1287 | Only GLM 5.2 measured |
| Design Arena: SVG | Not measured | 1213 | Only GLM 5.2 measured |
| Design Arena: ASCII art | Not measured | 1191 | Only GLM 5.2 measured |
| Neither model has a result on the other 1 board here | |||
GeneralLike-for-likePublic boards, shown as published, kept out of the index021
| Benchmark | Gemini 3.5 Flash Lite | GLM 5.2 | Leader |
|---|---|---|---|
| Public Benefits Bench (Vals AI) | 51.8% | Not measured | Only Gemini 3.5 Flash Lite measured |
| SAGE (Vals AI) | 47.3% | Not measured | Only Gemini 3.5 Flash Lite measured |
| MedScribe (Vals AI) | 70.9% | 83.5% | GLM 5.2 |
| IFBench | Not measured | 73.3% | Only GLM 5.2 measured |
| Long context reasoning (AA-LCR) | 76.0% | 78.3% | GLM 5.2 |
| DTBench | 83.5% | 93.6% | GLM 5.2 |
| LMCA | 37.6% | 45.8% | GLM 5.2 |
| Surface Evolver Bench | Not measured | 55.6% | Only GLM 5.2 measured |
| LMArena Text | 1435 | 1470 | GLM 5.2 |
| LMArena Text: instruction following | 1419 | 1466 | GLM 5.2 |
| LMArena Text: creative writing | 1421 | 1463 | GLM 5.2 |
| LMArena Vision | 1269 | Not measured | Only Gemini 3.5 Flash Lite measured |
| LMArena Text: English | 1438 | 1475 | GLM 5.2 |
| LMArena Text: non-English | 1427 | 1459 | GLM 5.2 |
| LMArena Text: Chinese | 1468 | 1522 | GLM 5.2 |
| LMArena Text: German | 1454 | 1470 | GLM 5.2 |
| LMArena Text: Japanese | 1426 | 1450 | GLM 5.2 |
| LMArena Text: Korean | 1407 | 1440 | GLM 5.2 |
| LMArena Text: French | 1451 | 1479 | GLM 5.2 |
| LMArena Text: Spanish | 1441 | 1478 | GLM 5.2 |
| LMArena Text: Russian | 1443 | 1468 | GLM 5.2 |
| LMArena Text: Polish | 1437 | 1456 | GLM 5.2 |
| LMArena Text: multi-turn | 1445 | 1469 | GLM 5.2 |
| LMArena Text: longer queries | 1435 | 1480 | GLM 5.2 |
| LMArena Text: writing and language | 1428 | 1463 | GLM 5.2 |
| LMArena Text: entertainment and media | 1414 | 1450 | GLM 5.2 |
| LMArena Vision: English | 1269 | Not measured | Only Gemini 3.5 Flash Lite measured |
| LMArena Vision: Chinese | 1311 | Not measured | Only Gemini 3.5 Flash Lite measured |
| LMArena Vision: reading text | 1280 | Not measured | Only Gemini 3.5 Flash Lite measured |
| LMArena Vision: humor | 1287 | Not measured | Only Gemini 3.5 Flash Lite measured |
| LMArena Vision: creative writing | 1260 | Not measured | Only Gemini 3.5 Flash Lite measured |
| Neither model has a result on the other 15 boards here | |||
Image generationNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
| Benchmark | Gemini 3.5 Flash Lite | GLM 5.2 | Leader |
|---|---|---|---|
| Neither model has a result on 5 boards here | |||
What each workload costs
Three fixed token mixes at each model's listed price, so per-token rates become a bill.
Chat turn
1K input + 500 output tokens
Gemini 3.5 Flash Lite costs less
Repository review
50K input + 3K output tokens
Gemini 3.5 Flash Lite costs less
Agent loop
200K input + 10K output tokens
Gemini 3.5 Flash Lite costs less
Listed OpenRouter rates, without cache or batch discounts. A workload that does not fit a model's context window would need splitting.
Specification differences
The leading value in a row is marked; a row with a missing value names no leader. Our two rows are marked in red.
| Specification | Google Gemini 3.5 Flash Lite | Z.ai GLM 5.2 |
|---|---|---|
| Maker | Z.ai | |
| Weights | No public weights listed | Open weights |
| Released | July 21, 2026 | June 16, 2026 |
| Context window | 1.05M | 1.05M |
| Input $/Mtok | $0.30 | $1.40 |
| Output $/Mtok | $2.50 | $4.40 |
| Coding index | 49.0 | 61.1 |
| Independent measurements behind it | 3 | 4 |
| Cost per solved task | $0.41 | $0.86 |
| Source | OpenRouter listing | OpenRouter listing |
Questions
Is Gemini 3.5 Flash Lite better than GLM 5.2 for coding?
Pick GLM 5.2 for coding: it scores 61.1 on the Vibe Coding Index against 49.0 for Gemini 3.5 Flash Lite. Pick Gemini 3.5 Flash Lite for output tokens 1.8x cheaper ($2.50 vs $4.40 per million) and a lower cost per solved task ($0.41 against $0.86).
Which is cheaper, Gemini 3.5 Flash Lite or GLM 5.2?
Gemini 3.5 Flash Lite costs $0.30 per million input tokens and $2.50 per million output tokens; GLM 5.2 costs $1.40 and $4.40. Per solved SWE-bench Verified task, Gemini 3.5 Flash Lite costs $0.41 and GLM 5.2 $0.86.
Which has the bigger context window, Gemini 3.5 Flash Lite or GLM 5.2?
Neither: both take 1.05M tokens.
How many benchmarks is the Gemini 3.5 Flash Lite vs GLM 5.2 comparison based on?
68 benchmarks have a result for both models as of October 22, 2026. Gemini 3.5 Flash Lite's coding index rests on 3 independent benchmarks and GLM 5.2's on 4. Where only one model has a result, the page says so instead of naming a winner.