Model comparison
GLM-5.2 vs Llama 3-8B
GLM-5.2 is the stronger model overall, scoring 51.1 to 25.5 on the Noometry Index.
Last verified . 22 shared benchmarks.
MetaSummary
- They share 22 benchmarks with published results for both. GLM-5.2 scores higher in 8 categories and Llama 3-8B in 0 categories; 8 gaps are clear of the uncertainty.
- The widest gap is in knowledge, where GLM-5.2 leads 57.1 to 7.8.
- The biggest single-benchmark swing is OTIS Mock AIME 2024-2025: 86.4% for GLM-5.2 and 1.9% for Llama 3-8B.
Side by side
| GLM-5.2 | Llama 3-8B | |
|---|---|---|
| Provider | Z.ai (Zhipu) | Meta |
| Noometry Index | 51.1 | 25.5 |
| Released | 2026-06-13 | 2024-04-18 |
| Weights | Open | Open |
| Context window | 1M | — |
| Max output | 131K | — |
| Input $ / M tokens | $1.40 | — |
| Output $ / M tokens | $4.40 | — |
| Results tracked | 51 | 34 |
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Category by category
Coding GLM-5.2 leads
GLM-5.2: 51.3 (#41), Llama 3-8B: 31.0 (#289)
| Benchmark | GLM-5.2 | Llama 3-8B |
|---|---|---|
| LMArena Coding | 1485 | 1152 |
| SWE-bench Verified | 78.7% | — |
| DeepSWE | 43.8% | — |
| FrontierCode | 24.5% | — |
| LMArena WebDev | 1603 | — |
| SciCode | 50.5% | — |
| WeirdML | 70.1% | — |
| BigCodeBench Instruct | — | 31.9% |
| BigCodeBench Complete | — | 36.9% |
| ALE-Bench | 1,047 | — |
| HumanEval+ | — | 56.7% |
| MBPP+ | — | 54.8% |
Agentic & Tool Use Not comparable
GLM-5.2: 32.4 (#63), Llama 3-8B: —
| Benchmark | GLM-5.2 | Llama 3-8B |
|---|---|---|
| APEX-Agents | 45.2% | — |
| τ²-bench Banking | 37.1% | — |
| PostTrainBench | 31.7% | — |
| GBAEval | 0% | — |
| Vending-Bench 2 | 8,314 | — |
Reasoning GLM-5.2 leads
GLM-5.2: 42.3 (#52), Llama 3-8B: 14.3 (#326)
| Benchmark | GLM-5.2 | Llama 3-8B |
|---|---|---|
| Chess Puzzles | 21% | 0% |
| LMArena Hard Prompts | 1480 | 1133 |
| DTBench | 93.6% | 43.9% |
| Epoch Capabilities Index | 151.78 | 116.45 |
| ARC-AGI-2 | 22.8% | — |
| SimpleBench | 58.8% | — |
| Kagi LLM Benchmark | 62.6% | — |
| NYT Connections (extended) | 74.3% | — |
| ARC-AGI-1 | 77% | — |
| CritPt | 20.9% | — |
| EBR-Bench | 9.5% | — |
| Mystery Game Puzzles | 19% | — |
| LMCA | 45.8% | — |
| Surface Evolver Bench | 55.6% | — |
| Adversarial NLI | — | 57.3% |
| ForecastBench | — | 58.6 |
| WinoGrande | — | 75.7% |
Math GLM-5.2 leads
GLM-5.2: 55.7 (#43), Llama 3-8B: 8.8 (#323)
| Benchmark | GLM-5.2 | Llama 3-8B |
|---|---|---|
| OTIS Mock AIME 2024-2025 | 86.4% | 1.9% |
| LMArena Math | 1482 | 1151 |
| FrontierMath (Tiers 1-3) | 59.2% | — |
| FrontierMath Tier 4 | 29.3% | — |
| MathArena Final-Answer Competitions | 67.6% | — |
| ProofBench | 35% | — |
| MATH Level 5 | — | 6.1% |
Knowledge GLM-5.2 leads
GLM-5.2: 57.1 (#40), Llama 3-8B: 7.8 (#308)
| Benchmark | GLM-5.2 | Llama 3-8B |
|---|---|---|
| GPQA Diamond | 91.9% | 26.1% |
| LMArena Expert | 1486 | 1113 |
| SimpleQA Verified | 34.2% | — |
| ARC (AI2) Challenge | — | 82.8% |
| MMLU | — | 68.8% |
| OpenBookQA | — | 82.6% |
| TriviaQA | — | 67.7% |
Multilingual GLM-5.2 leads
GLM-5.2: 55.8 (#26), Llama 3-8B: 30.8 (#261)
| Benchmark | GLM-5.2 | Llama 3-8B |
|---|---|---|
| LMArena Non-English | 1459 | 1098 |
| LMArena Chinese | 1519 | 1076 |
| LMArena French | 1479 | 1159 |
| LMArena German | 1468 | 1104 |
| LMArena Japanese | 1451 | 967 |
| LMArena Korean | 1445 | 1004 |
| LMArena Russian | 1466 | 1109 |
| LMArena Spanish | 1477 | 1173 |
Instruction Following GLM-5.2 leads
GLM-5.2: 76.9 (#34), Llama 3-8B: 58.4 (#260)
| Benchmark | GLM-5.2 | Llama 3-8B |
|---|---|---|
| LMArena Instruction Following | 1465 | 1127 |
Long Context GLM-5.2 leads
GLM-5.2: 45.3 (#43), Llama 3-8B: 34.2 (#251)
| Benchmark | GLM-5.2 | Llama 3-8B |
|---|---|---|
| LMArena Longer Query | 1479 | 1128 |
Writing & Preference GLM-5.2 leads
GLM-5.2: 70.4 (#21), Llama 3-8B: 37.5 (#256)
| Benchmark | GLM-5.2 | Llama 3-8B |
|---|---|---|
| LMArena Text | 1470 | 1166 |
| LMArena Creative Writing | 1462 | 1150 |
| LMArena Multi-Turn | 1469 | 1152 |
| EQ-Bench Creative Writing | 1757 | — |
| EQ-Bench 4 | 1222 | — |
Frequently asked questions
Is GLM-5.2 better than Llama 3-8B?
GLM-5.2 is the stronger model overall, scoring 51.1 to 25.5 on the Noometry Index.
Is GLM-5.2 or Llama 3-8B better for coding?
GLM-5.2 scores higher on coding benchmarks: 51.3 versus 31.0 in the Noometry coding category.
How many benchmarks do GLM-5.2 and Llama 3-8B share?
22 benchmarks have published results for both models. GLM-5.2 has 51 scored results on Noometry and Llama 3-8B has 34.