Gemini 2.5 Pro vs GLM 5V Turbo
Updated October 21, 2026. 54 benchmarks have a result for both. Coding is ranked on the Vibe Coding Index; every other board is shown as published.
Decision reading
Pick Gemini 2.5 Pro for coding: it scores 37.0 on the Vibe Coding Index against 28.8 for GLM 5V Turbo.
Pick GLM 5V Turbo when output tokens cost 2.5x less, or when what matters is LMArena WebDev or Terminal-Bench Hard (Artificial Analysis run), where it leads.
- Shared results
- 54
- Gemini 2.5 Pro only
- 33
- GLM 5V Turbo only
- 11
- Like-for-like categories
- 8 of 9
Shared results can support a head-to-head reading. Results only one model has describe coverage, not superiority.
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, four public coding benchmarks
Gemini 2.5 Pro
Gemini 2.5 Pro scores 37.0 against 28.8.
2 and 1 benchmarks behind the scores
Intelligence
AA Intelligence Index
GLM 5V Turbo
GLM 5V Turbo leads, 23.5 against 16.1.
Same board, both measured
Agentic work
AA Agentic Index
No call
Only Gemini 2.5 Pro has a AA Agentic Index result, 1.6.
Directional only
Web design
Design Arena: websites
GLM 5V Turbo
GLM 5V Turbo leads, 1230 against 1167.
Same board, both measured
Long documents
Listed context window
Gemini 2.5 Pro
Gemini 2.5 Pro takes 1.05M tokens against 203K.
Listed by OpenRouter
Everyday cost
1K input + 500 output tokens
GLM 5V Turbo
Gemini 2.5 Pro $0.0063, GLM 5V Turbo $0.0032 per turn.
List prices
Cost per solved task
One SWE-bench Verified task, solved
No call
Only Gemini 2.5 Pro has the number, $0.64.
Directional only
At a glance
- Coding index
- Gemini 2.5 Pro 37.0 from 2 benchmarks, GLM 5V Turbo 28.8 from 1 benchmark.
- Widest category
- Agentic work, 44.4 points apart on average over 1 shared benchmark.
- Widest single gap
- τ²-Bench Telecom: Gemini 2.5 Pro 54.1% against GLM 5V Turbo 98.5%, 44.4 points apart on a 0 to 100 scale.
- Output price
- Gemini 2.5 Pro $10.00 against GLM 5V Turbo $4.00 per million output tokens, 2.5x apart.
- Context window
- Gemini 2.5 Pro takes 1.05M tokens, GLM 5V Turbo 203K.
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 Pro | Bars | GLM 5V Turbo | Ties |
|---|---|---|---|---|
| Coding | 0 | 6 | ||
| Intelligence | 0 | 1 | ||
| Agentic work | 0 | 1 | ||
| Reasoning | 4 | 3 | ||
| Math | 2 | 0 | ||
| Knowledge | 4 | 0 | ||
| Web design | 1 | 5 | ||
| General | 21 | 6 | ||
| All shared boards | 32 | 22 |
CodingLike-for-likeFour of these boards feed the Vibe Coding Index06
| Benchmark | Gemini 2.5 Pro | GLM 5V Turbo | Leader |
|---|---|---|---|
| SWE-bench Verified | 53.6% | Not measured | Only Gemini 2.5 Pro measured |
| LMArena WebDev | 1226 | 1402 | GLM 5V Turbo |
| AA Coding Index | 33.3 | Not measured | Only Gemini 2.5 Pro measured |
| SWE-bench Verified (Vals AI) | 54.4% | Not measured | Only Gemini 2.5 Pro measured |
| Vibe Code Bench (Vals AI) | 0.4% | Not measured | Only Gemini 2.5 Pro measured |
| LiveCodeBench (Artificial Analysis run) | 80.1% | Not measured | Only Gemini 2.5 Pro measured |
| SciCode | 46.3% | Not measured | Only Gemini 2.5 Pro measured |
| Terminal-Bench Hard (Artificial Analysis run) | 26.5% | 32.6% | GLM 5V Turbo |
| Terminal-Bench | 32.6% | Not measured | Only Gemini 2.5 Pro measured |
| GSO-Bench | 3.9% | Not measured | Only Gemini 2.5 Pro measured |
| WeirdML | 54.0% | Not measured | Only Gemini 2.5 Pro measured |
| LMArena Text: coding | 1452 | 1466 | GLM 5V Turbo |
| LMArena Text: software and IT | 1459 | 1460 | GLM 5V Turbo |
| LMArena WebDev: React | Not measured | 1386 | Only GLM 5V Turbo measured |
| LMArena WebDev: HTML | 1235 | 1356 | GLM 5V Turbo |
| LMArena WebDev: from an image | 1285 | 1425 | GLM 5V Turbo |
| Neither model has a result on the other 22 boards here | |||
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index01
| Benchmark | Gemini 2.5 Pro | GLM 5V Turbo | Leader |
|---|---|---|---|
| AA Intelligence Index | 16.1 | 23.5 | GLM 5V Turbo |
| Epoch Capabilities Index | 145.1 | Not measured | Only Gemini 2.5 Pro measured |
Agentic workLike-for-likePublic boards, shown as published, kept out of the index01
| Benchmark | Gemini 2.5 Pro | GLM 5V Turbo | Leader |
|---|---|---|---|
| AA Agentic Index | 1.6 | Not measured | Only Gemini 2.5 Pro measured |
| Design Arena: agents building web apps | Not measured | 1124 | Only GLM 5V Turbo measured |
| Design Arena: agents building full-stack apps | Not measured | 1149 | Only GLM 5V Turbo measured |
| Design Arena: agents building mobile apps | Not measured | 1134 | Only GLM 5V Turbo measured |
| Design Arena: agents building Android apps | Not measured | 1267 | Only GLM 5V Turbo measured |
| Design Arena: agents building Godot games | Not measured | 957 | Only GLM 5V Turbo measured |
| Design Arena: agents building games | Not measured | 1102 | Only GLM 5V Turbo measured |
| Design Arena: HTML slides | Not measured | 1120 | Only GLM 5V Turbo measured |
| Design Arena: PowerPoint slides | Not measured | 1152 | Only GLM 5V Turbo measured |
| τ²-Bench Telecom | 54.1% | 98.5% | GLM 5V Turbo |
| GDPval | 23.3% | Not measured | Only Gemini 2.5 Pro measured |
| DeepResearch Bench | 41.5% | Not measured | Only Gemini 2.5 Pro measured |
| Vending-Bench 2 | $574 | Not measured | Only Gemini 2.5 Pro measured |
| Neither model has a result on the other 26 boards here | |||
ReasoningLike-for-likePublic boards, shown as published, kept out of the index43
| Benchmark | Gemini 2.5 Pro | GLM 5V Turbo | Leader |
|---|---|---|---|
| GPQA Diamond (Artificial Analysis run) | 84.4% | 80.9% | Gemini 2.5 Pro |
| Humanity's Last Exam (Artificial Analysis run) | 22.5% | 17.1% | Gemini 2.5 Pro |
| GPQA Diamond (Epoch AI run) | 85.3% | Not measured | Only Gemini 2.5 Pro measured |
| ARC-AGI | 41.0% | Not measured | Only Gemini 2.5 Pro measured |
| ARC-AGI-2 | 4.9% | Not measured | Only Gemini 2.5 Pro measured |
| LMArena Text: hard prompts | 1455 | 1443 | Gemini 2.5 Pro |
| LMArena Text: expert | 1452 | 1453 | GLM 5V Turbo |
| LMArena Text: hard prompts in English | 1453 | 1456 | GLM 5V Turbo |
| LMArena Vision: diagrams | 1274 | 1286 | GLM 5V Turbo |
| LMArena Vision: homework | 1281 | 1273 | Gemini 2.5 Pro |
| Neither model has a result on the other 11 boards here | |||
MathLike-for-likePublic boards, shown as published, kept out of the index20
| Benchmark | Gemini 2.5 Pro | GLM 5V Turbo | Leader |
|---|---|---|---|
| AA Math Index | 87.7 | Not measured | Only Gemini 2.5 Pro measured |
| AIME 2025 (Artificial Analysis run) | 87.7% | Not measured | Only Gemini 2.5 Pro measured |
| OTIS Mock AIME | 84.7% | Not measured | Only Gemini 2.5 Pro measured |
| FrontierMath, tiers 1 to 3 | 24.6% | Not measured | Only Gemini 2.5 Pro measured |
| FrontierMath, tier 4 | 0.0% | Not measured | Only Gemini 2.5 Pro measured |
| LMArena Text: math | 1450 | 1442 | Gemini 2.5 Pro |
| LMArena Text: mathematical work | 1454 | 1447 | Gemini 2.5 Pro |
| Neither model has a result on the other 6 boards here | |||
KnowledgeLike-for-likePublic boards, shown as published, kept out of the index40
| Benchmark | Gemini 2.5 Pro | GLM 5V Turbo | Leader |
|---|---|---|---|
| CaseLaw (Vals AI) | 63.9% | Not measured | Only Gemini 2.5 Pro measured |
| CorpFin (Vals AI) | 60.8% | Not measured | Only Gemini 2.5 Pro measured |
| MortgageTax (Vals AI) | 68.9% | Not measured | Only Gemini 2.5 Pro measured |
| MedCode (Vals AI) | 50.6% | Not measured | Only Gemini 2.5 Pro measured |
| MMLU Pro (Artificial Analysis run) | 86.2% | Not measured | Only Gemini 2.5 Pro measured |
| LMArena Text: science | 1480 | 1448 | Gemini 2.5 Pro |
| LMArena Text: medicine and healthcare | 1476 | 1433 | Gemini 2.5 Pro |
| LMArena Text: legal and government | 1480 | 1436 | Gemini 2.5 Pro |
| LMArena Text: business and finance | 1439 | 1435 | Gemini 2.5 Pro |
| Neither model has a result on the other 8 boards here | |||
Web designLike-for-likePublic boards, shown as published, kept out of the index15
| Benchmark | Gemini 2.5 Pro | GLM 5V Turbo | Leader |
|---|---|---|---|
| Design Arena: websites | 1167 | 1230 | GLM 5V Turbo |
| Design Arena: UI components | 1139 | 1213 | GLM 5V Turbo |
| Design Arena: game dev | 1112 | 1219 | GLM 5V Turbo |
| Design Arena: data viz | 1222 | 1202 | Gemini 2.5 Pro |
| Design Arena: 3D | 1080 | 1209 | GLM 5V Turbo |
| Design Arena: all code categories | 1152 | 1228 | GLM 5V Turbo |
| Design Arena: SVG | Not measured | 1151 | Only GLM 5V Turbo measured |
| Design Arena: ASCII art | Not measured | 1118 | Only GLM 5V Turbo measured |
| Neither model has a result on the other 1 board here | |||
GeneralLike-for-likePublic boards, shown as published, kept out of the index216
| Benchmark | Gemini 2.5 Pro | GLM 5V Turbo | Leader |
|---|---|---|---|
| SAGE (Vals AI) | 41.9% | Not measured | Only Gemini 2.5 Pro measured |
| MedScribe (Vals AI) | 73.5% | Not measured | Only Gemini 2.5 Pro measured |
| IFBench | 48.7% | 61.1% | GLM 5V Turbo |
| Long context reasoning (AA-LCR) | 69.0% | 70.3% | GLM 5V Turbo |
| DTBench | 82.4% | Not measured | Only Gemini 2.5 Pro measured |
| LMCA | 34.8% | Not measured | Only Gemini 2.5 Pro measured |
| Creative writing (Lech Mazur) | 83.8% | Not measured | Only Gemini 2.5 Pro measured |
| LMArena Text | 1458 | 1437 | Gemini 2.5 Pro |
| LMArena Text: instruction following | 1437 | 1423 | Gemini 2.5 Pro |
| LMArena Text: creative writing | 1454 | 1417 | Gemini 2.5 Pro |
| LMArena Vision | 1263 | 1264 | GLM 5V Turbo |
| LMArena Text: English | 1458 | 1454 | Gemini 2.5 Pro |
| LMArena Text: non-English | 1452 | 1420 | Gemini 2.5 Pro |
| LMArena Text: Chinese | 1507 | 1491 | Gemini 2.5 Pro |
| LMArena Text: German | 1487 | 1422 | Gemini 2.5 Pro |
| LMArena Text: Japanese | 1461 | Not measured | Only Gemini 2.5 Pro measured |
| LMArena Text: Korean | 1434 | 1397 | Gemini 2.5 Pro |
| LMArena Text: French | 1473 | 1443 | Gemini 2.5 Pro |
| LMArena Text: Spanish | 1474 | 1452 | Gemini 2.5 Pro |
| LMArena Text: Russian | 1461 | 1432 | Gemini 2.5 Pro |
| LMArena Text: Polish | 1479 | 1432 | Gemini 2.5 Pro |
| LMArena Text: multi-turn | 1453 | 1431 | Gemini 2.5 Pro |
| LMArena Text: longer queries | 1449 | 1438 | Gemini 2.5 Pro |
| LMArena Text: writing and language | 1454 | 1420 | Gemini 2.5 Pro |
| LMArena Text: entertainment and media | 1441 | 1407 | Gemini 2.5 Pro |
| LMArena Vision: English | 1261 | 1274 | GLM 5V Turbo |
| LMArena Vision: Chinese | 1300 | 1329 | GLM 5V Turbo |
| LMArena Vision: reading text | 1270 | 1270 | Gemini 2.5 Pro |
| LMArena Vision: humor | 1262 | 1268 | GLM 5V Turbo |
| LMArena Vision: captioning | 1304 | 1264 | Gemini 2.5 Pro |
| LMArena Vision: recognizing things | 1283 | 1241 | Gemini 2.5 Pro |
| LMArena Vision: creative writing | 1265 | 1252 | Gemini 2.5 Pro |
| LMArena Document | 1421 | 1416 | Gemini 2.5 Pro |
| Neither model has a result on the other 13 boards here | |||
Image generationNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
| Benchmark | Gemini 2.5 Pro | GLM 5V Turbo | 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 5V Turbo costs less
Repository review
50K input + 3K output tokens
GLM 5V Turbo costs less
Agent loop
200K input + 10K output tokens
GLM 5V Turbo 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 Pro | Z.ai GLM 5V Turbo |
|---|---|---|
| Maker | Z.ai | |
| Weights | No public weights listed | No public weights listed |
| Released | June 17, 2025 | April 1, 2026 |
| Context window | 1.05M | 203K |
| Input $/Mtok | $1.25 | $1.20 |
| Output $/Mtok | $10.00 | $4.00 |
| Coding index | 37.0 | 28.8 |
| Independent measurements behind it | 2 | 1 |
| Cost per solved task | $0.64 | Not computable |
| Source | OpenRouter listing | OpenRouter listing |
Questions
Is Gemini 2.5 Pro better than GLM 5V Turbo for coding?
Pick Gemini 2.5 Pro for coding: it scores 37.0 on the Vibe Coding Index against 28.8 for GLM 5V Turbo. Pick GLM 5V Turbo when output tokens cost 2.5x less, or when what matters is LMArena WebDev or Terminal-Bench Hard (Artificial Analysis run), where it leads.
Which is cheaper, Gemini 2.5 Pro or GLM 5V Turbo?
Gemini 2.5 Pro costs $1.25 per million input tokens and $10.00 per million output tokens; GLM 5V Turbo costs $1.20 and $4.00. Cost per solved task is known for Gemini 2.5 Pro only.
Which has the bigger context window, Gemini 2.5 Pro or GLM 5V Turbo?
Gemini 2.5 Pro, with 1.05M tokens against 203K.
How many benchmarks is the Gemini 2.5 Pro vs GLM 5V Turbo comparison based on?
54 benchmarks have a result for both models as of October 21, 2026. Gemini 2.5 Pro's coding index rests on 2 independent benchmarks and GLM 5V Turbo's on 1. Where only one model has a result, the page says so instead of naming a winner.