Model comparison
GLM-4.6V vs Mistral
GLM-4.6V is the stronger model overall, scoring 41.3 to 29.9 on the Noometry Index.
Last verified . 11 shared benchmarks.
Mistral AISummary
- They share 11 benchmarks with published results for both. GLM-4.6V scores higher in 7 categories and Mistral in 0 categories; 7 gaps are clear of the uncertainty.
- The widest gap is in knowledge, where GLM-4.6V leads 38.0 to 16.6.
- GLM-4.6V has downloadable open weights; the other is API-only.
Side by side
| GLM-4.6V | Mistral | |
|---|---|---|
| Provider | Z.ai (Zhipu) | Mistral AI |
| Noometry Index | 41.3 | 29.9 |
| Released | 2025-12-08 | — |
| Weights | Open | Proprietary |
| Context window | 128K | — |
| Max output | 33K | — |
| Input $ / M tokens | $0.30 | — |
| Output $ / M tokens | $0.90 | — |
| Results tracked | 12 | 22 |
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Category by category
Coding GLM-4.6V leads
GLM-4.6V: 40.9 (#128), Mistral: 33.8 (#250)
| Benchmark | GLM-4.6V | Mistral |
|---|---|---|
| LMArena Coding | 1390 | 1162 |
Reasoning GLM-4.6V leads
GLM-4.6V: 27.6 (#115), Mistral: 22.2 (#200)
| Benchmark | GLM-4.6V | Mistral |
|---|---|---|
| LMArena Hard Prompts | 1368 | 1149 |
Math Not comparable
GLM-4.6V: —, Mistral: 22.3 (#278)
| Benchmark | GLM-4.6V | Mistral |
|---|---|---|
| Omni-MATH | — | 7.2% |
| LMArena Math | — | 1180 |
Knowledge GLM-4.6V leads
GLM-4.6V: 38.0 (#149), Mistral: 16.6 (#288)
| Benchmark | GLM-4.6V | Mistral |
|---|---|---|
| LMArena Expert | 1371 | 1125 |
| MMLU-Pro | — | 27.7% |
| GPQA (HELM) | — | 30.3% |
Multimodal Not comparable
GLM-4.6V: 34.8 (#90), Mistral: —
| Benchmark | GLM-4.6V | Mistral |
|---|---|---|
| LMArena Vision | 1164 | — |
Multilingual GLM-4.6V leads
GLM-4.6V: 48.6 (#141), Mistral: 32.8 (#254)
| Benchmark | GLM-4.6V | Mistral |
|---|---|---|
| LMArena Non-English | 1359 | 1129 |
| LMArena Chinese | 1425 | 1109 |
| LMArena Russian | 1340 | 1168 |
| LMArena French | — | 1180 |
| LMArena German | — | 1155 |
| LMArena Japanese | — | 1013 |
| LMArena Korean | — | 1032 |
| LMArena Spanish | — | 1143 |
Instruction Following GLM-4.6V leads
GLM-4.6V: 71.4 (#151), Mistral: 52.6 (#288)
| Benchmark | GLM-4.6V | Mistral |
|---|---|---|
| LMArena Instruction Following | 1352 | 1152 |
| IFEval | — | 56.8% |
Long Context GLM-4.6V leads
GLM-4.6V: 41.3 (#143), Mistral: 35.0 (#245)
| Benchmark | GLM-4.6V | Mistral |
|---|---|---|
| LMArena Longer Query | 1358 | 1153 |
Writing & Preference GLM-4.6V leads
GLM-4.6V: 56.6 (#137), Mistral: 37.0 (#260)
| Benchmark | GLM-4.6V | Mistral |
|---|---|---|
| LMArena Text | 1377 | 1165 |
| LMArena Creative Writing | 1347 | 1158 |
| LMArena Multi-Turn | 1360 | 1147 |
| WildBench | — | 66% |
Frequently asked questions
Is GLM-4.6V better than Mistral?
GLM-4.6V is the stronger model overall, scoring 41.3 to 29.9 on the Noometry Index.
Is GLM-4.6V or Mistral better for coding?
GLM-4.6V scores higher on coding benchmarks: 40.9 versus 33.8 in the Noometry coding category.
How many benchmarks do GLM-4.6V and Mistral share?
11 benchmarks have published results for both models. GLM-4.6V has 12 scored results on Noometry and Mistral has 22.