Model comparison
GLM-5.3 vs Llama 3-70B
GLM-5.3 is the stronger model overall, scoring 54.8 to 28.8 on the Noometry Index.
Last verified . 21 shared benchmarks.
MetaSummary
- They share 21 benchmarks with published results for both. GLM-5.3 scores higher in 9 categories and Llama 3-70B in 0 categories; 9 gaps are clear of the uncertainty.
- The widest gap is in math, where GLM-5.3 leads 62.3 to 12.8.
- The biggest single-benchmark swing is OTIS Mock AIME 2024-2025: 91.1% for GLM-5.3 and 4.3% for Llama 3-70B.
Side by side
| GLM-5.3 | Llama 3-70B | |
|---|---|---|
| Provider | Z.ai (Zhipu) | Meta |
| Noometry Index | 54.8 | 28.8 |
| Released | 2026-08-14 | 2024-04-18 |
| Weights | Open | Open |
| Context window | 1M | — |
| Max output | 131K | — |
| Input $ / M tokens | $1.40 | — |
| Output $ / M tokens | $4.40 | — |
| Results tracked | 42 | 31 |
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Category by category
Coding GLM-5.3 leads
GLM-5.3: 59.5 (#14), Llama 3-70B: 35.8 (#218)
| Benchmark | GLM-5.3 | Llama 3-70B |
|---|---|---|
| LMArena Coding | 1496 | 1206 |
| DeepSWE | 69% | — |
| FrontierCode | 40.1% | — |
| CursorBench | 42.6% | — |
| LMArena WebDev | 1622 | — |
| FrontierSWE | 30.2% | — |
| SciCode | 59% | — |
| WeirdML | 75.4% | — |
| BigCodeBench Instruct | — | 43.6% |
| BigCodeBench Complete | — | 54.5% |
| ALE-Bench | 1,317 | — |
| HumanEval+ | — | 72% |
| MBPP+ | — | 69% |
Agentic & Tool Use GLM-5.3 leads
GLM-5.3: 36.4 (#38), Llama 3-70B: 21.1 (#139)
| Benchmark | GLM-5.3 | Llama 3-70B |
|---|---|---|
| APEX-Agents | 56.6% | — |
| Cybench | — | 5% |
| Vending-Bench 2 | 8,164 | — |
Reasoning GLM-5.3 leads
GLM-5.3: 46.1 (#46), Llama 3-70B: 18.0 (#288)
| Benchmark | GLM-5.3 | Llama 3-70B |
|---|---|---|
| LMArena Hard Prompts | 1489 | 1195 |
| DTBench | 87.7% | 54.2% |
| Epoch Capabilities Index | 155.61 | 122.93 |
| Kagi LLM Benchmark | — | 35.1% |
| NYT Connections (extended) | 74.2% | — |
| CritPt | 19.1% | — |
| Chess Puzzles | 21% | — |
| Mystery Game Puzzles | 33% | — |
| LMCA | 55.5% | — |
| Bench to the Future 3 | 0.15 | — |
| ForecastBench | — | 57.1 |
| WinoGrande | — | 83.5% |
Math GLM-5.3 leads
GLM-5.3: 62.3 (#33), Llama 3-70B: 12.8 (#305)
| Benchmark | GLM-5.3 | Llama 3-70B |
|---|---|---|
| OTIS Mock AIME 2024-2025 | 91.1% | 4.3% |
| LMArena Math | 1489 | 1218 |
| FrontierMath (Tiers 1-3) | 68.8% | — |
| FrontierMath Tier 4 | 29.3% | — |
| ProofBench | 49% | — |
| MATH Level 5 | — | 22.6% |
Knowledge GLM-5.3 leads
GLM-5.3: 58.3 (#37), Llama 3-70B: 20.8 (#277)
| Benchmark | GLM-5.3 | Llama 3-70B |
|---|---|---|
| GPQA Diamond | 90.9% | 40.6% |
| LMArena Expert | 1516 | 1149 |
| SimpleQA Verified | 41% | — |
| MMLU | — | 79.3% |
Multilingual GLM-5.3 leads
GLM-5.3: 55.7 (#28), Llama 3-70B: 33.6 (#251)
| Benchmark | GLM-5.3 | Llama 3-70B |
|---|---|---|
| LMArena Non-English | 1457 | 1142 |
| LMArena Chinese | 1528 | 1114 |
| LMArena French | 1499 | 1232 |
| LMArena German | 1499 | 1169 |
| LMArena Japanese | 1453 | 1017 |
| LMArena Korean | 1472 | 1017 |
| LMArena Russian | 1463 | 1159 |
| LMArena Spanish | 1460 | 1241 |
Instruction Following GLM-5.3 leads
GLM-5.3: 77.5 (#23), Llama 3-70B: 62.5 (#238)
| Benchmark | GLM-5.3 | Llama 3-70B |
|---|---|---|
| LMArena Instruction Following | 1477 | 1194 |
Long Context GLM-5.3 leads
GLM-5.3: 45.4 (#41), Llama 3-70B: 35.6 (#240)
| Benchmark | GLM-5.3 | Llama 3-70B |
|---|---|---|
| LMArena Longer Query | 1482 | 1174 |
Writing & Preference GLM-5.3 leads
GLM-5.3: 75.7 (#6), Llama 3-70B: 42.8 (#231)
| Benchmark | GLM-5.3 | Llama 3-70B |
|---|---|---|
| LMArena Text | 1471 | 1221 |
| LMArena Creative Writing | 1457 | 1210 |
| LMArena Multi-Turn | 1472 | 1223 |
| EQ-Bench Creative Writing | 2075 | — |
Frequently asked questions
Is GLM-5.3 better than Llama 3-70B?
GLM-5.3 is the stronger model overall, scoring 54.8 to 28.8 on the Noometry Index.
Is GLM-5.3 or Llama 3-70B better for coding?
GLM-5.3 scores higher on coding benchmarks: 59.5 versus 35.8 in the Noometry coding category.
How many benchmarks do GLM-5.3 and Llama 3-70B share?
21 benchmarks have published results for both models. GLM-5.3 has 42 scored results on Noometry and Llama 3-70B has 31.