Model comparison
GLM-4.5 vs Llama 3.1-70B
GLM-4.5 is the stronger model overall, scoring 42.0 to 29.6 on the Noometry Index. Llama 3.1-70B costs 2.5× less per token, which makes it the better buy when GLM-4.5's lead doesn't matter for your workload.
Last verified . 19 shared benchmarks.
MetaSummary
- They share 19 benchmarks with published results for both. GLM-4.5 scores higher in 8 categories and Llama 3.1-70B in 0 categories; 7 gaps are clear of the uncertainty.
- The widest gap is in math, where GLM-4.5 leads 39.0 to 13.5.
- The biggest single-benchmark swing is WeirdML: 40.6% for GLM-4.5 and 9% for Llama 3.1-70B.
- Llama 3.1-70B is cheaper at $0.40 / $0.40 per million input/output tokens, against $0.60 / $2.20 for GLM-4.5.
- GLM-4.5 accepts more context: 131K tokens versus 128K.
Side by side
| GLM-4.5 | Llama 3.1-70B | |
|---|---|---|
| Provider | Z.ai (Zhipu) | Meta |
| Noometry Index | 42.0 | 29.6 |
| Released | 2025-07-27 | 2024-07-23 |
| Weights | Open | Open |
| Context window | 131K | 128K |
| Max output | 98K | 4K |
| Input $ / M tokens | $0.60 | $0.40 |
| Output $ / M tokens | $2.20 | $0.40 |
| Results tracked | 27 | 35 |
Sponsored placements are available on pages like this one. Advertise on Noometry
Category by category
Coding GLM-4.5 leads
GLM-4.5: 41.4 (#125), Llama 3.1-70B: 30.3 (#296)
| Benchmark | GLM-4.5 | Llama 3.1-70B |
|---|---|---|
| WeirdML | 40.6% | 9% |
| LMArena Coding | 1434 | 1260 |
| SWE-bench Verified (bash only) | 54.2% | — |
| BigCodeBench Instruct | — | 46.1% |
| BigCodeBench Complete | — | 54.8% |
| ALE-Bench | 344.82 | — |
| AlgoTune | 1.52 | — |
Agentic & Tool Use Not comparable
GLM-4.5: —, Llama 3.1-70B: 25.1 (#112)
| Benchmark | GLM-4.5 | Llama 3.1-70B |
|---|---|---|
| TheAgentCompany | — | 6.9% |
| BALROG | — | 27.9% |
Reasoning GLM-4.5 leads
GLM-4.5: 28.6 (#100), Llama 3.1-70B: 21.6 (#220)
| Benchmark | GLM-4.5 | Llama 3.1-70B |
|---|---|---|
| LMArena Hard Prompts | 1429 | 1241 |
| Kagi LLM Benchmark | 57.9% | — |
| DTBench | — | 60% |
| LMCA | — | 14.8% |
| Epoch Capabilities Index | — | 125.92 |
Math GLM-4.5 leads
GLM-4.5: 39.0 (#116), Llama 3.1-70B: 13.5 (#304)
| Benchmark | GLM-4.5 | Llama 3.1-70B |
|---|---|---|
| LMArena Math | 1427 | 1252 |
| OTIS Mock AIME 2024-2025 | — | 3.6% |
| Omni-MATH | — | 21% |
| MATH Level 5 | — | 36.7% |
Knowledge GLM-4.5 leads
GLM-4.5: 35.9 (#179), Llama 3.1-70B: 24.2 (#269)
| Benchmark | GLM-4.5 | Llama 3.1-70B |
|---|---|---|
| LMArena Expert | 1433 | 1209 |
| GPQA Diamond | — | 44.2% |
| Humanity's Last Exam | 8.3% | — |
| MMLU-Pro | — | 65.3% |
| Confabulations | 11.3% | — |
| GPQA (HELM) | — | 42.6% |
| MMLU | — | 80.1% |
Multilingual GLM-4.5 leads
GLM-4.5: 52.8 (#77), Llama 3.1-70B: 38.8 (#225)
| Benchmark | GLM-4.5 | Llama 3.1-70B |
|---|---|---|
| LMArena Non-English | 1417 | 1219 |
| LMArena Chinese | 1465 | 1215 |
| LMArena French | 1418 | 1261 |
| LMArena German | 1407 | 1222 |
| LMArena Japanese | 1415 | 1132 |
| LMArena Korean | 1380 | 1140 |
| LMArena Russian | 1414 | 1234 |
| LMArena Spanish | 1454 | 1253 |
Instruction Following GLM-4.5 leads
GLM-4.5: 74.1 (#104), Llama 3.1-70B: 65.3 (#223)
| Benchmark | GLM-4.5 | Llama 3.1-70B |
|---|---|---|
| LMArena Instruction Following | 1404 | 1231 |
| IFEval | — | 82.1% |
Long Context Too close to call
GLM-4.5: 38.2 (#201), Llama 3.1-70B: 37.6 (#214)
| Benchmark | GLM-4.5 | Llama 3.1-70B |
|---|---|---|
| LMArena Longer Query | 1412 | 1241 |
| Fiction.LiveBench | 58.3% | — |
Writing & Preference GLM-4.5 leads
GLM-4.5: 57.5 (#127), Llama 3.1-70B: 35.4 (#267)
| Benchmark | GLM-4.5 | Llama 3.1-70B |
|---|---|---|
| LMArena Text | 1430 | 1261 |
| LMArena Creative Writing | 1395 | 1232 |
| EQ-Bench Creative Writing | 1343 | 784 |
| LMArena Multi-Turn | 1415 | 1256 |
| Short-Story Creative Writing | 73.4% | — |
| WildBench | — | 75.8% |
Frequently asked questions
Is GLM-4.5 better than Llama 3.1-70B?
GLM-4.5 is the stronger model overall, scoring 42.0 to 29.6 on the Noometry Index. Llama 3.1-70B costs 2.5× less per token, which makes it the better buy when GLM-4.5's lead doesn't matter for your workload.
Which is cheaper, GLM-4.5 or Llama 3.1-70B?
Llama 3.1-70B is cheaper. It lists at $0.40 per million input tokens and $0.40 per million output tokens; GLM-4.5 lists at $0.60 and $2.20.
Is GLM-4.5 or Llama 3.1-70B better for coding?
GLM-4.5 scores higher on coding benchmarks: 41.4 versus 30.3 in the Noometry coding category.
Which has the bigger context window?
GLM-4.5 does, with 131K tokens against 128K.
How many benchmarks do GLM-4.5 and Llama 3.1-70B share?
19 benchmarks have published results for both models. GLM-4.5 has 27 scored results on Noometry and Llama 3.1-70B has 35.