Model comparison
GLM-5V-Turbo vs Llama 4 Maverick
GLM-5V-Turbo is the stronger model overall, scoring 43.8 to 30.9 on the Noometry Index. Llama 4 Maverick costs 6.3× less per token, which makes it the better buy when GLM-5V-Turbo's lead doesn't matter for your workload.
Last verified . 17 shared benchmarks.
MetaSummary
- They share 17 benchmarks with published results for both. GLM-5V-Turbo scores higher in 9 categories and Llama 4 Maverick in 0 categories; 9 gaps are clear of the uncertainty.
- The widest gap is in writing & preference, where GLM-5V-Turbo leads 62.5 to 38.8.
- Llama 4 Maverick is cheaper at $0.19 / $0.65 per million input/output tokens, against $1.20 / $4 for GLM-5V-Turbo.
- GLM-5V-Turbo accepts more context: 200K tokens versus 128K.
- Llama 4 Maverick has downloadable open weights; the other is API-only.
Side by side
| GLM-5V-Turbo | Llama 4 Maverick | |
|---|---|---|
| Provider | Z.ai (Zhipu) | Meta |
| Noometry Index | 43.8 | 30.9 |
| Released | 2026-04-01 | 2025-04-05 |
| Weights | Proprietary | Open |
| Context window | 200K | 128K |
| Max output | 131K | 4K |
| Input $ / M tokens | $1.20 | $0.19 |
| Output $ / M tokens | $4 | $0.65 |
| Results tracked | 19 | 54 |
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Category by category
Coding GLM-5V-Turbo leads
GLM-5V-Turbo: 42.1 (#111), Llama 4 Maverick: 26.6 (#324)
| Benchmark | GLM-5V-Turbo | Llama 4 Maverick |
|---|---|---|
| LMArena Coding | 1466 | 1302 |
| SWE-bench Verified (bash only) | — | 21% |
| Aider Polyglot | — | 15.6% |
| LMArena WebDev | 1401 | — |
| SciCode | — | 33.1% |
| WeirdML | — | 24.5% |
| BigCodeBench Instruct | — | 49.7% |
| BigCodeBench Complete | — | 61.4% |
| ALE-Bench | — | 172.97 |
Agentic & Tool Use Not comparable
GLM-5V-Turbo: —, Llama 4 Maverick: 28.2 (#91)
| Benchmark | GLM-5V-Turbo | Llama 4 Maverick |
|---|---|---|
| Berkeley Function Calling Leaderboard | — | 37.3% |
Reasoning GLM-5V-Turbo leads
GLM-5V-Turbo: 29.7 (#89), Llama 4 Maverick: 10.1 (#342)
| Benchmark | GLM-5V-Turbo | Llama 4 Maverick |
|---|---|---|
| LMArena Hard Prompts | 1443 | 1281 |
| ARC-AGI-2 | — | 0% |
| SimpleBench | — | 27.7% |
| Kagi LLM Benchmark | — | 55.9% |
| NYT Connections (extended) | — | 8% |
| ARC-AGI-1 | — | 4.4% |
| CritPt | — | 0% |
| EnigmaEval | — | 0.6% |
| DTBench | — | 61.9% |
| LMCA | — | 15.9% |
| Epoch Capabilities Index | — | 132.2 |
| ForecastBench | — | 57.5 |
Math GLM-5V-Turbo leads
GLM-5V-Turbo: 39.4 (#106), Llama 4 Maverick: 26.0 (#262)
| Benchmark | GLM-5V-Turbo | Llama 4 Maverick |
|---|---|---|
| LMArena Math | 1441 | 1299 |
| OTIS Mock AIME 2024-2025 | — | 20.6% |
| Omni-MATH | — | 42.2% |
| MATH Level 5 | — | 73% |
| FrontierMath (Feb 2025 set) | — | 0.7% |
Knowledge GLM-5V-Turbo leads
GLM-5V-Turbo: 40.6 (#117), Llama 4 Maverick: 33.4 (#204)
| Benchmark | GLM-5V-Turbo | Llama 4 Maverick |
|---|---|---|
| LMArena Expert | 1452 | 1259 |
| GPQA Diamond | — | 67% |
| Humanity's Last Exam | — | 5.7% |
| MMLU-Pro | — | 81% |
| Confabulations | — | 22.6% |
| Vectara Hallucination Rate | — | 8.2% |
| GPQA (HELM) | — | 65% |
Multimodal GLM-5V-Turbo leads
GLM-5V-Turbo: 40.9 (#42), Llama 4 Maverick: 31.6 (#105)
| Benchmark | GLM-5V-Turbo | Llama 4 Maverick |
|---|---|---|
| LMArena Vision | 1264 | 1142 |
| GeoBench | — | 52% |
| LMArena Document | 1416 | — |
| SpatialViz-Bench | — | 31.8% |
Multilingual GLM-5V-Turbo leads
GLM-5V-Turbo: 53.0 (#73), Llama 4 Maverick: 42.2 (#195)
| Benchmark | GLM-5V-Turbo | Llama 4 Maverick |
|---|---|---|
| LMArena Non-English | 1420 | 1269 |
| LMArena Chinese | 1488 | 1277 |
| LMArena French | 1444 | 1259 |
| LMArena German | 1423 | 1291 |
| LMArena Korean | 1396 | 1203 |
| LMArena Russian | 1431 | 1286 |
| LMArena Spanish | 1450 | 1293 |
| LMArena Japanese | — | 1207 |
Instruction Following GLM-5V-Turbo leads
GLM-5V-Turbo: 75.0 (#80), Llama 4 Maverick: 71.7 (#146)
| Benchmark | GLM-5V-Turbo | Llama 4 Maverick |
|---|---|---|
| LMArena Instruction Following | 1423 | 1267 |
| IFEval | — | 90.8% |
Long Context GLM-5V-Turbo leads
GLM-5V-Turbo: 44.0 (#80), Llama 4 Maverick: 31.4 (#279)
| Benchmark | GLM-5V-Turbo | Llama 4 Maverick |
|---|---|---|
| LMArena Longer Query | 1438 | 1280 |
| Fiction.LiveBench | — | 46.2% |
Writing & Preference GLM-5V-Turbo leads
GLM-5V-Turbo: 62.5 (#73), Llama 4 Maverick: 38.8 (#252)
| Benchmark | GLM-5V-Turbo | Llama 4 Maverick |
|---|---|---|
| LMArena Text | 1437 | 1287 |
| LMArena Creative Writing | 1416 | 1267 |
| LMArena Multi-Turn | 1432 | 1289 |
| Short-Story Creative Writing | — | 62% |
| EQ-Bench Creative Writing | — | 860 |
| WildBench | — | 80% |
Frequently asked questions
Is GLM-5V-Turbo better than Llama 4 Maverick?
GLM-5V-Turbo is the stronger model overall, scoring 43.8 to 30.9 on the Noometry Index. Llama 4 Maverick costs 6.3× less per token, which makes it the better buy when GLM-5V-Turbo's lead doesn't matter for your workload.
Which is cheaper, GLM-5V-Turbo or Llama 4 Maverick?
Llama 4 Maverick is cheaper. It lists at $0.19 per million input tokens and $0.65 per million output tokens; GLM-5V-Turbo lists at $1.20 and $4.
Is GLM-5V-Turbo or Llama 4 Maverick better for coding?
GLM-5V-Turbo scores higher on coding benchmarks: 42.1 versus 26.6 in the Noometry coding category.
Which has the bigger context window?
GLM-5V-Turbo does, with 200K tokens against 128K.
How many benchmarks do GLM-5V-Turbo and Llama 4 Maverick share?
17 benchmarks have published results for both models. GLM-5V-Turbo has 19 scored results on Noometry and Llama 4 Maverick has 54.