Model comparison
GLM-4.6 vs Mistral
GLM-4.6 is the stronger model overall, scoring 41.4 to 29.9 on the Noometry Index.
Last verified . 17 shared benchmarks.
Mistral AISummary
- They share 17 benchmarks with published results for both. GLM-4.6 scores higher in 8 categories and Mistral in 0 categories; 8 gaps are clear of the uncertainty.
- The widest gap is in writing & preference, where GLM-4.6 leads 61.1 to 37.0.
- GLM-4.6 has downloadable open weights; the other is API-only.
Side by side
| GLM-4.6 | Mistral | |
|---|---|---|
| Provider | Z.ai (Zhipu) | Mistral AI |
| Noometry Index | 41.4 | 29.9 |
| Released | 2025-09-30 | — |
| Weights | Open | Proprietary |
| Context window | 205K | — |
| Max output | 131K | — |
| Input $ / M tokens | $0.60 | — |
| Output $ / M tokens | $2.20 | — |
| Results tracked | 29 | 22 |
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Category by category
Coding GLM-4.6 leads
GLM-4.6: 40.1 (#148), Mistral: 33.8 (#250)
| Benchmark | GLM-4.6 | Mistral |
|---|---|---|
| LMArena Coding | 1449 | 1162 |
| SWE-bench Verified (bash only) | 55.4% | — |
| LMArena WebDev | 1340 | — |
| SciCode | 38.4% | — |
| ALE-Bench | 340.82 | — |
Agentic & Tool Use Not comparable
GLM-4.6: 32.3 (#66), Mistral: —
| Benchmark | GLM-4.6 | Mistral |
|---|---|---|
| Terminal-Bench | 24.5% | — |
| Berkeley Function Calling Leaderboard | 72.4% | — |
Reasoning GLM-4.6 leads
GLM-4.6: 23.7 (#172), Mistral: 22.2 (#200)
| Benchmark | GLM-4.6 | Mistral |
|---|---|---|
| LMArena Hard Prompts | 1440 | 1149 |
| Kagi LLM Benchmark | 47.4% | — |
| CritPt | 1.1% | — |
Math GLM-4.6 leads
GLM-4.6: 39.1 (#111), Mistral: 22.3 (#278)
| Benchmark | GLM-4.6 | Mistral |
|---|---|---|
| LMArena Math | 1432 | 1180 |
| Omni-MATH | — | 7.2% |
| FrontierMath (Feb 2025 set) | 3.8% | — |
| FrontierMath Tier 4 (v1) | 2.1% | — |
Knowledge GLM-4.6 leads
GLM-4.6: 40.2 (#124), Mistral: 16.6 (#288)
| Benchmark | GLM-4.6 | Mistral |
|---|---|---|
| LMArena Expert | 1431 | 1125 |
| MMLU-Pro | — | 27.7% |
| Vectara Hallucination Rate | 9.5% | — |
| GPQA (HELM) | — | 30.3% |
Multilingual GLM-4.6 leads
GLM-4.6: 53.5 (#66), Mistral: 32.8 (#254)
| Benchmark | GLM-4.6 | Mistral |
|---|---|---|
| LMArena Non-English | 1426 | 1129 |
| LMArena Chinese | 1499 | 1109 |
| LMArena French | 1459 | 1180 |
| LMArena German | 1447 | 1155 |
| LMArena Japanese | 1393 | 1013 |
| LMArena Korean | 1400 | 1032 |
| LMArena Russian | 1419 | 1168 |
| LMArena Spanish | 1436 | 1143 |
Instruction Following GLM-4.6 leads
GLM-4.6: 74.3 (#98), Mistral: 52.6 (#288)
| Benchmark | GLM-4.6 | Mistral |
|---|---|---|
| LMArena Instruction Following | 1410 | 1152 |
| IFEval | — | 56.8% |
Long Context GLM-4.6 leads
GLM-4.6: 43.4 (#94), Mistral: 35.0 (#245)
| Benchmark | GLM-4.6 | Mistral |
|---|---|---|
| LMArena Longer Query | 1422 | 1153 |
Writing & Preference GLM-4.6 leads
GLM-4.6: 61.1 (#90), Mistral: 37.0 (#260)
| Benchmark | GLM-4.6 | Mistral |
|---|---|---|
| LMArena Text | 1440 | 1165 |
| LMArena Creative Writing | 1411 | 1158 |
| LMArena Multi-Turn | 1427 | 1147 |
| EQ-Bench Creative Writing | 1411 | — |
| WildBench | — | 66% |
Frequently asked questions
Is GLM-4.6 better than Mistral?
GLM-4.6 is the stronger model overall, scoring 41.4 to 29.9 on the Noometry Index.
Is GLM-4.6 or Mistral better for coding?
GLM-4.6 scores higher on coding benchmarks: 40.1 versus 33.8 in the Noometry coding category.
How many benchmarks do GLM-4.6 and Mistral share?
17 benchmarks have published results for both models. GLM-4.6 has 29 scored results on Noometry and Mistral has 22.