Gemini 2.5 Flash vs GLM 5.3 Flash
GLM 5.3 Flash leads Gemini 2.5 Flash on the Artificial Analysis Intelligence Index, 41.8 to 15.5, and GLM 5.3 Flash costs 5.0x less per output token ($0.50 vs $2.50 per million). Updated October 22, 2026; 51 benchmarks have a result for both.
Gemini 2.5 Flash or GLM 5.3 Flash: which to pick
Only GLM 5.3 Flash has a coding score, 57.7 on the Vibe Coding Index; Gemini 2.5 Flash has none, so the two cannot be ranked on coding.
Compare them on price, context and the boards below.
- Shared results
- 51
- Gemini 2.5 Flash only
- 22
- GLM 5.3 Flash only
- 51
- 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
No call
Only GLM 5.3 Flash has a coding score, so no call is made.
One side not measured
Intelligence
AA Intelligence Index
GLM 5.3 Flash
GLM 5.3 Flash leads, 41.8 against 15.5.
Same board, both measured
Agentic work
AA Agentic Index
No call
Only GLM 5.3 Flash has a AA Agentic Index result, 50.9.
Directional only
Reasoning
GPQA Diamond
No call
Only GLM 5.3 Flash has a GPQA Diamond result, 86.4%.
Directional only
Knowledge
MMLU Pro
No call
Only GLM 5.3 Flash has a MMLU Pro result, 86.1%.
Directional only
Web design
Design Arena: websites
GLM 5.3 Flash
GLM 5.3 Flash leads, 1272 against 1074.
Same board, both measured
General
Vals Index
No call
Only GLM 5.3 Flash has a Vals Index result, 50.9%.
Directional only
Long documents
Listed context window
No call
Both take 1.05M tokens.
Listed by OpenRouter
Everyday cost
1K input + 500 output tokens
GLM 5.3 Flash
Gemini 2.5 Flash $0.0015, GLM 5.3 Flash $0.0004 per turn.
List prices
Cost per solved task
One SWE-bench Verified task, solved
GLM 5.3 Flash
Gemini 2.5 Flash $0.466, GLM 5.3 Flash $0.02.
Published attempt cost and pass rate
At a glance
- Coding index
- Gemini 2.5 Flash not benchmarked, GLM 5.3 Flash 57.7 from 6 benchmarks.
- Widest category
- Web design, 31.6 points apart on average over 7 shared benchmarks.
- Widest single gap
- ARC-AGI-2: Gemini 2.5 Flash 2.5% against GLM 5.3 Flash 65.8%, 63.3 points apart on a 0 to 100 scale.
- Output price
- Gemini 2.5 Flash $2.50 against GLM 5.3 Flash $0.50 per million output tokens, 5.0x 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 2.5 Flash | Bars | GLM 5.3 Flash | Ties |
|---|---|---|---|---|
| Coding | 0 | 2 | ||
| Intelligence | 0 | 2 | ||
| Reasoning | 0 | 9 | ||
| Math | 0 | 2 | ||
| Knowledge | 0 | 4 | ||
| Web design | 0 | 7 | ||
| General | 0 | 25 | ||
| All shared boards | 0 | 51 |
CodingLike-for-likeSix of these boards feed the Vibe Coding Index02
| Benchmark | Gemini 2.5 Flash | GLM 5.3 Flash | Leader |
|---|---|---|---|
| SWE-bench Verified | 28.7% | Not measured | Only Gemini 2.5 Flash measured |
| LiveBench coding | Not measured | 80.6% | Only GLM 5.3 Flash measured |
| LMArena WebDev | Not measured | 1607 | Only GLM 5.3 Flash measured |
| AA Coding Index | Not measured | 71.5 | Only GLM 5.3 Flash measured |
| LiveCodeBench (Vals AI) | Not measured | 80.5% | Only GLM 5.3 Flash measured |
| SWE-bench Verified (Vals AI) | Not measured | 92.0% | Only GLM 5.3 Flash measured |
| Terminal-Bench 4 (Vals AI) | Not measured | 37.4% | Only GLM 5.3 Flash measured |
| Vibe Code Bench (Vals AI) | Not measured | 30.8% | Only GLM 5.3 Flash measured |
| Code migration (Vals AI) | Not measured | 20.5% | Only GLM 5.3 Flash measured |
| ProgramBench (Vals AI) | Not measured | 0.0% | Only GLM 5.3 Flash measured |
| IOI (Vals AI) | Not measured | 52.5% | Only GLM 5.3 Flash measured |
| Terminal-Bench 2.1 (Vals AI) | Not measured | 62.9% | Only GLM 5.3 Flash measured |
| Vibe Code Bench 1-100 (Vals AI) | Not measured | 16.0% | Only GLM 5.3 Flash measured |
| SkillsBench (Vals AI) | Not measured | 40.2% | Only GLM 5.3 Flash measured |
| CyberBench (Vals AI) | Not measured | 67.9% | Only GLM 5.3 Flash measured |
| LiveCodeBench (Artificial Analysis run) | 69.5% | Not measured | Only Gemini 2.5 Flash measured |
| SciCode | Not measured | 51.6% | Only GLM 5.3 Flash measured |
| Terminal-Bench Hard (Artificial Analysis run) | 13.6% | Not measured | Only Gemini 2.5 Flash measured |
| Terminal-Bench | 17.1% | Not measured | Only Gemini 2.5 Flash measured |
| FrontierCode | Not measured | 31.8% | Only GLM 5.3 Flash measured |
| FrontierSWE | Not measured | 18.1% | Only GLM 5.3 Flash measured |
| ALE-Bench | Not measured | 303.6 | Only GLM 5.3 Flash measured |
| LMArena Text: coding | 1423 | 1507 | GLM 5.3 Flash |
| LMArena Text: software and IT | 1425 | 1500 | GLM 5.3 Flash |
| LMArena WebDev: React | Not measured | 1624 | Only GLM 5.3 Flash measured |
| LMArena WebDev: HTML | Not measured | 1577 | Only GLM 5.3 Flash measured |
| LMArena WebDev: from an image | Not measured | 1578 | Only GLM 5.3 Flash measured |
| Neither model has a result on the other 12 boards here | |||
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index02
| Benchmark | Gemini 2.5 Flash | GLM 5.3 Flash | Leader |
|---|---|---|---|
| AA Intelligence Index | 15.5 | 41.8 | GLM 5.3 Flash |
| Epoch Capabilities Index | 142.9 | 153.1 | GLM 5.3 Flash |
Agentic workDirectional onlyPublic boards, shown as published, kept out of the index17 boards, none shared
| Benchmark | Gemini 2.5 Flash | GLM 5.3 Flash | Leader |
|---|---|---|---|
| AA Agentic Index | Not measured | 50.9 | Only GLM 5.3 Flash measured |
| LiveBench research | Not measured | 70.1% | Only GLM 5.3 Flash measured |
| LiveBench browser | Not measured | 84.0% | Only GLM 5.3 Flash measured |
| LiveBench long agentic | Not measured | 28.4% | Only GLM 5.3 Flash measured |
| SREBench (Vals AI) | Not measured | 0.8% | Only GLM 5.3 Flash measured |
| Finance Agent (Vals AI) | Not measured | 57.9% | Only GLM 5.3 Flash measured |
| Tax Agent Bench (Vals AI) | Not measured | 31.6% | Only GLM 5.3 Flash measured |
| Legal Research Bench (Vals AI) | Not measured | 45.2% | Only GLM 5.3 Flash measured |
| Harvey's Legal Agent Benchmark (Vals AI) | Not measured | 10.4% | Only GLM 5.3 Flash measured |
| Excel Modeling Benchmark (Vals AI) | Not measured | 55.9% | Only GLM 5.3 Flash measured |
| Terminal-Bench-Science (Vals AI) | Not measured | 2.9% | Only GLM 5.3 Flash measured |
| τ²-Bench Telecom | 31.6% | Not measured | Only Gemini 2.5 Flash measured |
| APEX-Agents | Not measured | 52.8% | Only GLM 5.3 Flash measured |
| BALROG | 33.5% | Not measured | Only Gemini 2.5 Flash measured |
| Vending-Bench 2 | $549 | Not measured | Only Gemini 2.5 Flash measured |
| Berkeley Function Calling Leaderboard (BFCL) | 56.2% | Not measured | Only Gemini 2.5 Flash measured |
| BrowseComp-Plus | 39.9% | Not measured | Only Gemini 2.5 Flash measured |
| Neither model has a result on the other 24 boards here | |||
ReasoningLike-for-likePublic boards, shown as published, kept out of the index09
| Benchmark | Gemini 2.5 Flash | GLM 5.3 Flash | Leader |
|---|---|---|---|
| GPQA Diamond | Not measured | 86.4% | Only GLM 5.3 Flash measured |
| LiveBench reasoning | Not measured | 77.6% | Only GLM 5.3 Flash measured |
| MMMU Pro (Vals AI) | Not measured | 86.0% | Only GLM 5.3 Flash measured |
| GPQA Diamond (Artificial Analysis run) | 79.0% | 91.2% | GLM 5.3 Flash |
| Humanity's Last Exam (Artificial Analysis run) | 12.1% | 39.9% | GLM 5.3 Flash |
| GPQA Diamond (Epoch AI run) | Not measured | 90.2% | Only GLM 5.3 Flash measured |
| ARC-AGI | 33.3% | 91.0% | GLM 5.3 Flash |
| ARC-AGI-2 | 2.5% | 65.8% | GLM 5.3 Flash |
| SimpleBench | 41.2% | Not measured | Only Gemini 2.5 Flash measured |
| Chess puzzles | Not measured | 21.0% | Only GLM 5.3 Flash measured |
| Mystery game puzzles | Not measured | 8.0% | Only GLM 5.3 Flash measured |
| LMArena Text: hard prompts | 1422 | 1490 | GLM 5.3 Flash |
| LMArena Text: expert | 1426 | 1511 | GLM 5.3 Flash |
| LMArena Text: hard prompts in English | 1420 | 1488 | GLM 5.3 Flash |
| LMArena Vision: diagrams | 1245 | 1317 | GLM 5.3 Flash |
| LMArena Vision: homework | 1244 | 1318 | GLM 5.3 Flash |
| Kagi LLM Benchmark | 56.8% | Not measured | Only Gemini 2.5 Flash measured |
| Neither model has a result on the other 5 boards here | |||
MathLike-for-likePublic boards, shown as published, kept out of the index02
| Benchmark | Gemini 2.5 Flash | GLM 5.3 Flash | Leader |
|---|---|---|---|
| AA Math Index | 73.3 | Not measured | Only Gemini 2.5 Flash measured |
| AIME 2025 (Artificial Analysis run) | 73.3% | Not measured | Only Gemini 2.5 Flash measured |
| OTIS Mock AIME | Not measured | 93.9% | Only GLM 5.3 Flash measured |
| FrontierMath, tiers 1 to 3 | Not measured | 55.8% | Only GLM 5.3 Flash measured |
| FrontierMath, tier 4 | Not measured | 17.1% | Only GLM 5.3 Flash measured |
| ProofBench | Not measured | 21.0% | Only GLM 5.3 Flash measured |
| LMArena Text: math | 1411 | 1503 | GLM 5.3 Flash |
| LMArena Text: mathematical work | 1422 | 1497 | GLM 5.3 Flash |
| Neither model has a result on the other 5 boards here | |||
KnowledgeLike-for-likePublic boards, shown as published, kept out of the index04
| Benchmark | Gemini 2.5 Flash | GLM 5.3 Flash | Leader |
|---|---|---|---|
| MMLU Pro | Not measured | 86.1% | Only GLM 5.3 Flash measured |
| LegalBench (Vals AI) | Not measured | 83.9% | Only GLM 5.3 Flash measured |
| TaxEval (Vals AI) | Not measured | 75.6% | Only GLM 5.3 Flash measured |
| MedCode (Vals AI) | 40.4% | Not measured | Only Gemini 2.5 Flash measured |
| MMLU Pro (Artificial Analysis run) | 83.2% | Not measured | Only Gemini 2.5 Flash measured |
| LMArena Text: science | 1433 | 1484 | GLM 5.3 Flash |
| LMArena Text: medicine and healthcare | 1428 | 1475 | GLM 5.3 Flash |
| LMArena Text: legal and government | 1430 | 1473 | GLM 5.3 Flash |
| LMArena Text: business and finance | 1404 | 1460 | GLM 5.3 Flash |
| FACTS Benchmark Suite | 47.2% | Not measured | Only Gemini 2.5 Flash measured |
| Neither model has a result on the other 8 boards here | |||
Web designLike-for-likePublic boards, shown as published, kept out of the index07
| Benchmark | Gemini 2.5 Flash | GLM 5.3 Flash | Leader |
|---|---|---|---|
| Design Arena: websites | 1074 | 1272 | GLM 5.3 Flash |
| Design Arena: UI components | 1002 | 1316 | GLM 5.3 Flash |
| Design Arena: game dev | 1004 | 1278 | GLM 5.3 Flash |
| Design Arena: data viz | 1060 | 1262 | GLM 5.3 Flash |
| Design Arena: 3D | 1020 | 1316 | GLM 5.3 Flash |
| Design Arena: all code categories | 1059 | 1282 | GLM 5.3 Flash |
| Design Arena: SVG | 1020 | 1285 | GLM 5.3 Flash |
| Design Arena: ASCII art | Not measured | 1267 | Only GLM 5.3 Flash measured |
| LiveBench design | Not measured | 77.2% | Only GLM 5.3 Flash measured |
GeneralLike-for-likePublic boards, shown as published, kept out of the index025
| Benchmark | Gemini 2.5 Flash | GLM 5.3 Flash | Leader |
|---|---|---|---|
| Vals Index | Not measured | 50.9% | Only GLM 5.3 Flash measured |
| LiveBench data analysis | Not measured | 76.4% | Only GLM 5.3 Flash measured |
| SAGE (Vals AI) | 44.8% | Not measured | Only Gemini 2.5 Flash measured |
| MedScribe (Vals AI) | 83.0% | 88.9% | GLM 5.3 Flash |
| IFBench | 50.3% | Not measured | Only Gemini 2.5 Flash measured |
| Long context reasoning (AA-LCR) | 65.3% | 80.0% | GLM 5.3 Flash |
| DTBench | 76.5% | Not measured | Only Gemini 2.5 Flash measured |
| LMCA | 27.5% | Not measured | Only Gemini 2.5 Flash measured |
| Surface Evolver Bench | Not measured | 52.5% | Only GLM 5.3 Flash measured |
| LMArena Text | 1417 | 1471 | GLM 5.3 Flash |
| LMArena Text: instruction following | 1405 | 1478 | GLM 5.3 Flash |
| LMArena Text: creative writing | 1400 | 1441 | GLM 5.3 Flash |
| LMArena Vision | 1235 | 1294 | GLM 5.3 Flash |
| LMArena Text: English | 1418 | 1474 | GLM 5.3 Flash |
| LMArena Text: non-English | 1409 | 1462 | GLM 5.3 Flash |
| LMArena Text: Chinese | 1449 | 1531 | GLM 5.3 Flash |
| LMArena Text: German | 1417 | 1462 | GLM 5.3 Flash |
| LMArena Text: Japanese | 1396 | 1444 | GLM 5.3 Flash |
| LMArena Text: Korean | 1385 | 1436 | GLM 5.3 Flash |
| LMArena Text: French | 1432 | 1491 | GLM 5.3 Flash |
| LMArena Text: Spanish | 1422 | 1475 | GLM 5.3 Flash |
| LMArena Text: Russian | 1415 | 1465 | GLM 5.3 Flash |
| LMArena Text: Polish | 1413 | 1450 | GLM 5.3 Flash |
| LMArena Text: multi-turn | 1408 | 1469 | GLM 5.3 Flash |
| LMArena Text: longer queries | 1419 | 1481 | GLM 5.3 Flash |
| LMArena Text: writing and language | 1405 | 1455 | GLM 5.3 Flash |
| LMArena Text: entertainment and media | 1393 | 1440 | GLM 5.3 Flash |
| LMArena Vision: English | 1239 | 1295 | GLM 5.3 Flash |
| LMArena Vision: Chinese | 1284 | 1363 | GLM 5.3 Flash |
| LMArena Vision: reading text | 1237 | 1299 | GLM 5.3 Flash |
| LMArena Vision: humor | 1225 | 1279 | GLM 5.3 Flash |
| LMArena Vision: captioning | 1277 | Not measured | Only Gemini 2.5 Flash measured |
| LMArena Vision: recognizing things | 1252 | Not measured | Only Gemini 2.5 Flash measured |
| LMArena Vision: creative writing | 1241 | 1270 | GLM 5.3 Flash |
| Neither model has a result on the other 12 boards here | |||
Image generationNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
| Benchmark | Gemini 2.5 Flash | GLM 5.3 Flash | 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
GLM 5.3 Flash costs less
Repository review
50K input + 3K output tokens
GLM 5.3 Flash costs less
Agent loop
200K input + 10K output tokens
GLM 5.3 Flash 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 2.5 Flash | Z.ai GLM 5.3 Flash |
|---|---|---|
| Maker | Z.ai | |
| Weights | No public weights listed | Open weights |
| Released | June 17, 2025 | August 26, 2026 |
| Context window | 1.05M | 1.05M |
| Input $/Mtok | $0.30 | $0.15 |
| Output $/Mtok | $2.50 | $0.50 |
| Coding index | Not benchmarked | 57.7 |
| Independent measurements behind it | 0 | 6 |
| Cost per solved task | $0.466 | $0.02 |
| Source | OpenRouter listing | OpenRouter listing |
Questions
Is Gemini 2.5 Flash better than GLM 5.3 Flash for coding?
Only GLM 5.3 Flash has a coding score, 57.7 on the Vibe Coding Index; Gemini 2.5 Flash has none, so the two cannot be ranked on coding. Compare them on price, context and the boards below.
Which is cheaper, Gemini 2.5 Flash or GLM 5.3 Flash?
Gemini 2.5 Flash costs $0.30 per million input tokens and $2.50 per million output tokens; GLM 5.3 Flash costs $0.15 and $0.50. Per solved SWE-bench Verified task, Gemini 2.5 Flash costs $0.466 and GLM 5.3 Flash $0.02.
Which has the bigger context window, Gemini 2.5 Flash or GLM 5.3 Flash?
Neither: both take 1.05M tokens.
How many benchmarks is the Gemini 2.5 Flash vs GLM 5.3 Flash comparison based on?
51 benchmarks have a result for both models as of October 22, 2026. Gemini 2.5 Flash's coding index rests on 0 independent benchmarks and GLM 5.3 Flash's on 6. Where only one model has a result, the page says so instead of naming a winner.