Model comparison
GLM-4.6V vs Magistral Medium
GLM-4.6V is the stronger model overall, scoring 41.3 to 35.2 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 Magistral Medium in 0 categories; 7 gaps are clear of the uncertainty.
- The widest gap is in reasoning, where GLM-4.6V leads 27.6 to 8.6.
- GLM-4.6V is cheaper at $0.30 / $0.90 per million input/output tokens, against $2 / $5 for Magistral Medium.
- Magistral Medium accepts more context: 262K tokens versus 128K.
Side by side
| GLM-4.6V | Magistral Medium | |
|---|---|---|
| Provider | Z.ai (Zhipu) | Mistral AI |
| Noometry Index | 41.3 | 35.2 |
| Released | 2025-12-08 | 2025-03-17 |
| Weights | Open | Open |
| Context window | 128K | 262K |
| Max output | 33K | 16K |
| Input $ / M tokens | $0.30 | $2 |
| Output $ / M tokens | $0.90 | $5 |
| Results tracked | 12 | 22 |
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Category by category
Coding GLM-4.6V leads
GLM-4.6V: 40.9 (#128), Magistral Medium: 39.1 (#161)
| Benchmark | GLM-4.6V | Magistral Medium |
|---|---|---|
| LMArena Coding | 1390 | 1319 |
| SciCode | — | 39.2% |
Reasoning GLM-4.6V leads
GLM-4.6V: 27.6 (#115), Magistral Medium: 8.6 (#348)
| Benchmark | GLM-4.6V | Magistral Medium |
|---|---|---|
| LMArena Hard Prompts | 1368 | 1267 |
| ARC-AGI-2 | — | 0% |
| Kagi LLM Benchmark | — | 16.2% |
| ARC-AGI-1 | — | 6.1% |
| CritPt | — | 0.3% |
Math Not comparable
GLM-4.6V: —, Magistral Medium: 35.1 (#189)
| Benchmark | GLM-4.6V | Magistral Medium |
|---|---|---|
| LMArena Math | — | 1250 |
Knowledge GLM-4.6V leads
GLM-4.6V: 38.0 (#149), Magistral Medium: 33.5 (#202)
| Benchmark | GLM-4.6V | Magistral Medium |
|---|---|---|
| LMArena Expert | 1371 | 1223 |
Multimodal Not comparable
GLM-4.6V: 34.8 (#90), Magistral Medium: —
| Benchmark | GLM-4.6V | Magistral Medium |
|---|---|---|
| LMArena Vision | 1164 | — |
Multilingual GLM-4.6V leads
GLM-4.6V: 48.6 (#141), Magistral Medium: 39.6 (#224)
| Benchmark | GLM-4.6V | Magistral Medium |
|---|---|---|
| LMArena Non-English | 1359 | 1232 |
| LMArena Chinese | 1425 | 1227 |
| LMArena Russian | 1340 | 1224 |
| LMArena French | — | 1267 |
| LMArena German | — | 1248 |
| LMArena Japanese | — | 1175 |
| LMArena Korean | — | 1125 |
| LMArena Spanish | — | 1271 |
Instruction Following GLM-4.6V leads
GLM-4.6V: 71.4 (#151), Magistral Medium: 66.0 (#211)
| Benchmark | GLM-4.6V | Magistral Medium |
|---|---|---|
| LMArena Instruction Following | 1352 | 1254 |
Long Context GLM-4.6V leads
GLM-4.6V: 41.3 (#143), Magistral Medium: 39.3 (#183)
| Benchmark | GLM-4.6V | Magistral Medium |
|---|---|---|
| LMArena Longer Query | 1358 | 1295 |
Writing & Preference GLM-4.6V leads
GLM-4.6V: 56.6 (#137), Magistral Medium: 46.3 (#219)
| Benchmark | GLM-4.6V | Magistral Medium |
|---|---|---|
| LMArena Text | 1377 | 1255 |
| LMArena Creative Writing | 1347 | 1245 |
| LMArena Multi-Turn | 1360 | 1275 |
Frequently asked questions
Is GLM-4.6V better than Magistral Medium?
GLM-4.6V is the stronger model overall, scoring 41.3 to 35.2 on the Noometry Index.
Which is cheaper, GLM-4.6V or Magistral Medium?
GLM-4.6V is cheaper. It lists at $0.30 per million input tokens and $0.90 per million output tokens; Magistral Medium lists at $2 and $5.
Is GLM-4.6V or Magistral Medium better for coding?
GLM-4.6V scores higher on coding benchmarks: 40.9 versus 39.1 in the Noometry coding category.
Which has the bigger context window?
Magistral Medium does, with 262K tokens against 128K.
How many benchmarks do GLM-4.6V and Magistral Medium share?
11 benchmarks have published results for both models. GLM-4.6V has 12 scored results on Noometry and Magistral Medium has 22.