Model comparison
GLM-4.7-Flash vs Llama 3.1 Nemotron 70b Instruct
GLM-4.7-Flash is the stronger model overall, scoring 38.8 to 37.6 on the Noometry Index.
Last verified . 12 shared benchmarks.
NVIDIASummary
- They share 12 benchmarks with published results for both. GLM-4.7-Flash scores higher in 6 categories and Llama 3.1 Nemotron 70b Instruct in 2 categories; 6 gaps are clear of the uncertainty.
- The widest gap is in multilingual, where GLM-4.7-Flash leads 46.5 to 40.5.
Side by side
| GLM-4.7-Flash | Llama 3.1 Nemotron 70b Instruct | |
|---|---|---|
| Provider | Z.ai (Zhipu) | NVIDIA |
| Noometry Index | 38.8 | 37.6 |
| Released | 2026-01-19 | 2024-12-18 |
| Weights | Open | Open |
| Context window | 200K | — |
| Max output | 131K | — |
| Input $ / M tokens | $0.06 | — |
| Output $ / M tokens | $0.40 | — |
| Results tracked | 21 | 14 |
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Category by category
Coding GLM-4.7-Flash leads
GLM-4.7-Flash: 40.6 (#135), Llama 3.1 Nemotron 70b Instruct: 35.9 (#216)
| Benchmark | GLM-4.7-Flash | Llama 3.1 Nemotron 70b Instruct |
|---|---|---|
| LMArena Coding | 1383 | 1272 |
| BigCodeBench Instruct | — | 38.7% |
| BigCodeBench Complete | — | 48.2% |
Reasoning Llama 3.1 Nemotron 70b Instruct leads
GLM-4.7-Flash: 20.9 (#229), Llama 3.1 Nemotron 70b Instruct: 25.0 (#152)
| Benchmark | GLM-4.7-Flash | Llama 3.1 Nemotron 70b Instruct |
|---|---|---|
| LMArena Hard Prompts | 1356 | 1266 |
| Chess Puzzles | 0% | — |
Math Too close to call
GLM-4.7-Flash: 36.1 (#173), Llama 3.1 Nemotron 70b Instruct: 35.5 (#182)
| Benchmark | GLM-4.7-Flash | Llama 3.1 Nemotron 70b Instruct |
|---|---|---|
| LMArena Math | 1355 | 1271 |
| OTIS Mock AIME 2024-2025 | 58.3% | — |
Knowledge GLM-4.7-Flash leads
GLM-4.7-Flash: 35.5 (#184), Llama 3.1 Nemotron 70b Instruct: 34.1 (#199)
| Benchmark | GLM-4.7-Flash | Llama 3.1 Nemotron 70b Instruct |
|---|---|---|
| LMArena Expert | 1357 | 1242 |
| GPQA Diamond | 60.5% | — |
| Vectara Hallucination Rate | 9.3% | — |
Multilingual GLM-4.7-Flash leads
GLM-4.7-Flash: 46.5 (#158), Llama 3.1 Nemotron 70b Instruct: 40.5 (#217)
| Benchmark | GLM-4.7-Flash | Llama 3.1 Nemotron 70b Instruct |
|---|---|---|
| LMArena Non-English | 1330 | 1245 |
| LMArena Chinese | 1403 | 1263 |
| LMArena Russian | 1332 | 1227 |
| LMArena French | 1332 | — |
| LMArena German | 1337 | — |
| LMArena Korean | 1283 | — |
| LMArena Spanish | 1350 | — |
Instruction Following GLM-4.7-Flash leads
GLM-4.7-Flash: 70.1 (#167), Llama 3.1 Nemotron 70b Instruct: 65.9 (#213)
| Benchmark | GLM-4.7-Flash | Llama 3.1 Nemotron 70b Instruct |
|---|---|---|
| LMArena Instruction Following | 1327 | 1252 |
Long Context GLM-4.7-Flash leads
GLM-4.7-Flash: 40.9 (#148), Llama 3.1 Nemotron 70b Instruct: 37.6 (#215)
| Benchmark | GLM-4.7-Flash | Llama 3.1 Nemotron 70b Instruct |
|---|---|---|
| LMArena Longer Query | 1345 | 1238 |
Writing & Preference Too close to call
GLM-4.7-Flash: 47.4 (#210), Llama 3.1 Nemotron 70b Instruct: 48.4 (#203)
| Benchmark | GLM-4.7-Flash | Llama 3.1 Nemotron 70b Instruct |
|---|---|---|
| LMArena Text | 1351 | 1283 |
| LMArena Creative Writing | 1297 | 1269 |
| LMArena Multi-Turn | 1342 | 1275 |
| EQ-Bench Creative Writing | 1125 | — |
Frequently asked questions
Is GLM-4.7-Flash better than Llama 3.1 Nemotron 70b Instruct?
GLM-4.7-Flash is the stronger model overall, scoring 38.8 to 37.6 on the Noometry Index.
Is GLM-4.7-Flash or Llama 3.1 Nemotron 70b Instruct better for coding?
GLM-4.7-Flash scores higher on coding benchmarks: 40.6 versus 35.9 in the Noometry coding category.
How many benchmarks do GLM-4.7-Flash and Llama 3.1 Nemotron 70b Instruct share?
12 benchmarks have published results for both models. GLM-4.7-Flash has 21 scored results on Noometry and Llama 3.1 Nemotron 70b Instruct has 14.