Model comparison
Amazon Nova Pro vs GLM-5
GLM-5 is the stronger model overall, scoring 46.1 to 31.0 on the Noometry Index.
Last verified . 19 shared benchmarks.
Summary
- They share 19 benchmarks with published results for both. Amazon Nova Pro scores higher in 0 categories and GLM-5 in 9 categories; 9 gaps are clear of the uncertainty.
- The widest gap is in knowledge, where GLM-5 leads 52.3 to 27.4.
- The biggest single-benchmark swing is Vectara Hallucination Rate: 5.1% for Amazon Nova Pro and 10.1% for GLM-5.
- Amazon Nova Pro is cheaper at $0.80 / $3.20 per million input/output tokens, against $1 / $3.20 for GLM-5.
- Amazon Nova Pro accepts more context: 300K tokens versus 205K.
- GLM-5 has downloadable open weights; the other is API-only.
Side by side
| Amazon Nova Pro | GLM-5 | |
|---|---|---|
| Provider | Amazon | Z.ai (Zhipu) |
| Noometry Index | 31.0 | 46.1 |
| Released | 2024-12-03 | 2026-02-11 |
| Weights | Proprietary | Open |
| Context window | 300K | 205K |
| Max output | 10K | 131K |
| Input $ / M tokens | $0.80 | $1 |
| Output $ / M tokens | $3.20 | $3.20 |
| Results tracked | 38 | 45 |
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Category by category
Coding GLM-5 leads
Amazon Nova Pro: 35.1 (#229), GLM-5: 49.0 (#52)
| Benchmark | Amazon Nova Pro | GLM-5 |
|---|---|---|
| LMArena Coding | 1270 | 1461 |
| SWE-bench Verified | — | 72.1% |
| SWE-bench Verified (bash only) | — | 72.8% |
| LMArena WebDev | — | 1434 |
| SWE-bench Multilingual | — | 69.7% |
| WeirdML | — | 48.2% |
| LiveBench Coding | 38.1% | — |
| ALE-Bench | — | 765.62 |
Agentic & Tool Use GLM-5 leads
Amazon Nova Pro: 16.7 (#147), GLM-5: 31.1 (#71)
| Benchmark | Amazon Nova Pro | GLM-5 |
|---|---|---|
| Terminal-Bench | — | 52.4% |
| Berkeley Function Calling Leaderboard | 25% | — |
| TheAgentCompany | 1.7% | — |
| 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-5 leads
Amazon Nova Pro: 20.0 (#243), GLM-5: 27.6 (#116)
| Benchmark | Amazon Nova Pro | GLM-5 |
|---|---|---|
| LMArena Hard Prompts | 1246 | 1452 |
| Epoch Capabilities Index | 123.8 | 145.83 |
| 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% |
| LiveBench Reasoning | 32.6% | — |
| LiveBench Data Analysis | 48.3% | — |
| ForecastBench | — | 61 |
| LiveBench | 43.5% | — |
Math GLM-5 leads
Amazon Nova Pro: 28.5 (#243), GLM-5: 46.4 (#71)
| Benchmark | Amazon Nova Pro | GLM-5 |
|---|---|---|
| LMArena Math | 1252 | 1440 |
| MathArena Final-Answer Competitions | — | 65.7% |
| OTIS Mock AIME 2024-2025 | — | 80% |
| Omni-MATH | 24.2% | — |
| LiveBench Math | 38% | — |
| FrontierMath (Feb 2025 set) | — | 16.4% |
| FrontierMath Tier 4 (v1) | — | 2.1% |
Knowledge GLM-5 leads
Amazon Nova Pro: 27.4 (#250), GLM-5: 52.3 (#64)
| Benchmark | Amazon Nova Pro | GLM-5 |
|---|---|---|
| Vectara Hallucination Rate | 5.1% | 10.1% |
| LMArena Expert | 1211 | 1454 |
| GPQA Diamond | — | 87.8% |
| Humanity's Last Exam | 4.4% | — |
| MMLU-Pro | 67.3% | — |
| Confabulations | 30.1% | — |
| GPQA (HELM) | 44.6% | — |
| MMLU | 82% | — |
Multimodal Not comparable
Amazon Nova Pro: 25.0 (#126), GLM-5: —
| Benchmark | Amazon Nova Pro | GLM-5 |
|---|---|---|
| LMArena Vision | 980 | — |
Multilingual GLM-5 leads
Amazon Nova Pro: 39.7 (#223), GLM-5: 53.7 (#58)
| Benchmark | Amazon Nova Pro | GLM-5 |
|---|---|---|
| LMArena Non-English | 1234 | 1430 |
| LMArena Chinese | 1244 | 1511 |
| LMArena French | 1271 | 1455 |
| LMArena German | 1243 | 1445 |
| LMArena Japanese | 1200 | 1416 |
| LMArena Korean | 1203 | 1423 |
| LMArena Russian | 1240 | 1436 |
| LMArena Spanish | 1182 | 1454 |
Instruction Following GLM-5 leads
Amazon Nova Pro: 64.9 (#226), GLM-5: 75.2 (#67)
| Benchmark | Amazon Nova Pro | GLM-5 |
|---|---|---|
| LMArena Instruction Following | 1235 | 1428 |
| LiveBench Instruction Following | 67.1% | — |
| IFEval | 81.5% | — |
Long Context GLM-5 leads
Amazon Nova Pro: 38.1 (#205), GLM-5: 44.7 (#60)
| Benchmark | Amazon Nova Pro | GLM-5 |
|---|---|---|
| LMArena Longer Query | 1255 | 1446 |
| CL-bench | — | 18.7% |
Writing & Preference GLM-5 leads
Amazon Nova Pro: 43.9 (#226), GLM-5: 66.0 (#38)
| Benchmark | Amazon Nova Pro | GLM-5 |
|---|---|---|
| LMArena Text | 1259 | 1446 |
| LMArena Creative Writing | 1212 | 1439 |
| LMArena Multi-Turn | 1246 | 1456 |
| Short-Story Creative Writing | 60.5% | — |
| EQ-Bench Creative Writing | — | 1601 |
| WildBench | 77.7% | — |
| LiveBench Language | 37% | — |
Frequently asked questions
Is Amazon Nova Pro better than GLM-5?
GLM-5 is the stronger model overall, scoring 46.1 to 31.0 on the Noometry Index.
Which is cheaper, Amazon Nova Pro or GLM-5?
Amazon Nova Pro is cheaper. It lists at $0.80 per million input tokens and $3.20 per million output tokens; GLM-5 lists at $1 and $3.20.
Is Amazon Nova Pro or GLM-5 better for coding?
GLM-5 scores higher on coding benchmarks: 49.0 versus 35.1 in the Noometry coding category.
Which has the bigger context window?
Amazon Nova Pro does, with 300K tokens against 205K.
How many benchmarks do Amazon Nova Pro and GLM-5 share?
19 benchmarks have published results for both models. Amazon Nova Pro has 38 scored results on Noometry and GLM-5 has 45.