Model comparison
GLM-5 vs GLM-5V-Turbo
GLM-5 is the stronger model overall, scoring 46.1 to 43.8 on the Noometry Index.
Last verified . 17 shared benchmarks.
Summary
- They share 17 benchmarks with published results for both. GLM-5 scores higher in 7 categories and GLM-5V-Turbo in 1 category; 5 gaps are clear of the uncertainty.
- The widest gap is in knowledge, where GLM-5 leads 52.3 to 40.6.
- GLM-5 is cheaper at $1 / $3.20 per million input/output tokens, against $1.20 / $4 for GLM-5V-Turbo.
- GLM-5 accepts more context: 205K tokens versus 200K.
- GLM-5 has downloadable open weights; the other is API-only.
Side by side
| GLM-5 | GLM-5V-Turbo | |
|---|---|---|
| Provider | Z.ai (Zhipu) | Z.ai (Zhipu) |
| Noometry Index | 46.1 | 43.8 |
| Released | 2026-02-11 | 2026-04-01 |
| Weights | Open | Proprietary |
| Context window | 205K | 200K |
| Max output | 131K | 131K |
| Input $ / M tokens | $1 | $1.20 |
| Output $ / M tokens | $3.20 | $4 |
| Results tracked | 45 | 19 |
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Category by category
Coding GLM-5 leads
GLM-5: 49.0 (#52), GLM-5V-Turbo: 42.1 (#111)
| Benchmark | GLM-5 | GLM-5V-Turbo |
|---|---|---|
| LMArena WebDev | 1434 | 1401 |
| LMArena Coding | 1461 | 1466 |
| SWE-bench Verified | 72.1% | — |
| SWE-bench Verified (bash only) | 72.8% | — |
| SWE-bench Multilingual | 69.7% | — |
| WeirdML | 48.2% | — |
| ALE-Bench | 765.62 | — |
Agentic & Tool Use Not comparable
GLM-5: 31.1 (#71), GLM-5V-Turbo: —
| Benchmark | GLM-5 | GLM-5V-Turbo |
|---|---|---|
| Terminal-Bench | 52.4% | — |
| τ²-bench Airline | 82.5% | — |
| τ²-bench Banking | 9.8% | — |
| τ²-bench Retail | 73.7% | — |
| τ²-bench Telecom | 86.8% | — |
| Vending-Bench 2 | 4,432 | — |
Reasoning GLM-5V-Turbo leads
GLM-5: 27.6 (#116), GLM-5V-Turbo: 29.7 (#89)
| Benchmark | GLM-5 | GLM-5V-Turbo |
|---|---|---|
| LMArena Hard Prompts | 1452 | 1443 |
| ARC-AGI-2 | 4.9% | — |
| SimpleBench | 53.2% | — |
| Kagi LLM Benchmark | 75% | — |
| NYT Connections (extended) | 74.8% | — |
| ARC-AGI-1 | 44.7% | — |
| Chess Puzzles | 10% | — |
| Epoch Capabilities Index | 145.83 | — |
| ForecastBench | 61 | — |
Math GLM-5 leads
GLM-5: 46.4 (#71), GLM-5V-Turbo: 39.4 (#106)
| Benchmark | GLM-5 | GLM-5V-Turbo |
|---|---|---|
| LMArena Math | 1440 | 1441 |
| MathArena Final-Answer Competitions | 65.7% | — |
| OTIS Mock AIME 2024-2025 | 80% | — |
| FrontierMath (Feb 2025 set) | 16.4% | — |
| FrontierMath Tier 4 (v1) | 2.1% | — |
Knowledge GLM-5 leads
GLM-5: 52.3 (#64), GLM-5V-Turbo: 40.6 (#117)
| Benchmark | GLM-5 | GLM-5V-Turbo |
|---|---|---|
| LMArena Expert | 1454 | 1452 |
| GPQA Diamond | 87.8% | — |
| Vectara Hallucination Rate | 10.1% | — |
Multimodal Not comparable
GLM-5: —, GLM-5V-Turbo: 40.9 (#42)
| Benchmark | GLM-5 | GLM-5V-Turbo |
|---|---|---|
| LMArena Vision | — | 1264 |
| LMArena Document | — | 1416 |
Multilingual Too close to call
GLM-5: 53.7 (#58), GLM-5V-Turbo: 53.0 (#73)
| Benchmark | GLM-5 | GLM-5V-Turbo |
|---|---|---|
| LMArena Non-English | 1430 | 1420 |
| LMArena Chinese | 1511 | 1488 |
| LMArena French | 1455 | 1444 |
| LMArena German | 1445 | 1423 |
| LMArena Korean | 1423 | 1396 |
| LMArena Russian | 1436 | 1431 |
| LMArena Spanish | 1454 | 1450 |
| LMArena Japanese | 1416 | — |
Instruction Following Too close to call
GLM-5: 75.2 (#67), GLM-5V-Turbo: 75.0 (#80)
| Benchmark | GLM-5 | GLM-5V-Turbo |
|---|---|---|
| LMArena Instruction Following | 1428 | 1423 |
Long Context Too close to call
GLM-5: 44.7 (#60), GLM-5V-Turbo: 44.0 (#80)
| Benchmark | GLM-5 | GLM-5V-Turbo |
|---|---|---|
| LMArena Longer Query | 1446 | 1438 |
| CL-bench | 18.7% | — |
Writing & Preference GLM-5 leads
GLM-5: 66.0 (#38), GLM-5V-Turbo: 62.5 (#73)
| Benchmark | GLM-5 | GLM-5V-Turbo |
|---|---|---|
| LMArena Text | 1446 | 1437 |
| LMArena Creative Writing | 1439 | 1416 |
| LMArena Multi-Turn | 1456 | 1432 |
| EQ-Bench Creative Writing | 1601 | — |
Frequently asked questions
Is GLM-5 better than GLM-5V-Turbo?
GLM-5 is the stronger model overall, scoring 46.1 to 43.8 on the Noometry Index.
Which is cheaper, GLM-5 or GLM-5V-Turbo?
GLM-5 is cheaper. It lists at $1 per million input tokens and $3.20 per million output tokens; GLM-5V-Turbo lists at $1.20 and $4.
Is GLM-5 or GLM-5V-Turbo better for coding?
GLM-5 scores higher on coding benchmarks: 49.0 versus 42.1 in the Noometry coding category.
Which has the bigger context window?
GLM-5 does, with 205K tokens against 200K.
How many benchmarks do GLM-5 and GLM-5V-Turbo share?
17 benchmarks have published results for both models. GLM-5 has 45 scored results on Noometry and GLM-5V-Turbo has 19.