Model comparison
GLM-5V-Turbo vs Mistral Large
GLM-5V-Turbo is the stronger model overall, scoring 43.8 to 31.9 on the Noometry Index.
Last verified . 16 shared benchmarks.
Mistral AISummary
- They share 16 benchmarks with published results for both. GLM-5V-Turbo scores higher in 8 categories and Mistral Large in 0 categories; 8 gaps are clear of the uncertainty.
- The widest gap is in writing & preference, where GLM-5V-Turbo leads 62.5 to 40.7.
- GLM-5V-Turbo is cheaper at $1.20 / $4 per million input/output tokens, against $2 / $6 for Mistral Large.
- GLM-5V-Turbo accepts more context: 200K tokens versus 131K.
- Mistral Large has downloadable open weights; the other is API-only.
Side by side
| GLM-5V-Turbo | Mistral Large | |
|---|---|---|
| Provider | Z.ai (Zhipu) | Mistral AI |
| Noometry Index | 43.8 | 31.9 |
| Released | 2026-04-01 | 2024-02-26 |
| Weights | Proprietary | Open |
| Context window | 200K | 131K |
| Max output | 131K | 16K |
| Input $ / M tokens | $1.20 | $2 |
| Output $ / M tokens | $4 | $6 |
| Results tracked | 19 | 51 |
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Category by category
Coding GLM-5V-Turbo leads
GLM-5V-Turbo: 42.1 (#111), Mistral Large: 34.3 (#240)
| Benchmark | GLM-5V-Turbo | Mistral Large |
|---|---|---|
| LMArena Coding | 1466 | 1277 |
| LMArena WebDev | 1401 | — |
| SciCode | — | 36.2% |
| BigCodeBench Instruct | — | 30% |
| LiveBench Coding | — | 47.1% |
| BigCodeBench Complete | — | 38.3% |
| ALE-Bench | — | 264.7 |
| HumanEval+ | — | 62.2% |
| MBPP+ | — | 59.5% |
Agentic & Tool Use Not comparable
GLM-5V-Turbo: —, Mistral Large: 28.6 (#89)
| Benchmark | GLM-5V-Turbo | Mistral Large |
|---|---|---|
| Berkeley Function Calling Leaderboard | — | 38.4% |
Reasoning GLM-5V-Turbo leads
GLM-5V-Turbo: 29.7 (#89), Mistral Large: 15.8 (#310)
| Benchmark | GLM-5V-Turbo | Mistral Large |
|---|---|---|
| LMArena Hard Prompts | 1443 | 1257 |
| SimpleBench | — | 22.5% |
| CritPt | — | 0% |
| LiveBench Reasoning | — | 43.5% |
| DTBench | — | 65.1% |
| LiveBench Data Analysis | — | 50.1% |
| LMCA | — | 16.7% |
| Epoch Capabilities Index | — | 128.52 |
| ForecastBench | — | 57.1 |
| LiveBench | — | 48.4% |
Math GLM-5V-Turbo leads
GLM-5V-Turbo: 39.4 (#106), Mistral Large: 18.2 (#291)
| Benchmark | GLM-5V-Turbo | Mistral Large |
|---|---|---|
| LMArena Math | 1441 | 1262 |
| OTIS Mock AIME 2024-2025 | — | 8.5% |
| Omni-MATH | — | 28.1% |
| LiveBench Math | — | 42.5% |
| MATH Level 5 | — | 50.3% |
| FrontierMath (Feb 2025 set) | — | 0.3% |
Knowledge GLM-5V-Turbo leads
GLM-5V-Turbo: 40.6 (#117), Mistral Large: 30.1 (#230)
| Benchmark | GLM-5V-Turbo | Mistral Large |
|---|---|---|
| LMArena Expert | 1452 | 1232 |
| GPQA Diamond | — | 51.3% |
| MMLU-Pro | — | 59.9% |
| Confabulations | — | 21.4% |
| Vectara Hallucination Rate | — | 4.5% |
| GPQA (HELM) | — | 43.5% |
| MMLU | — | 80% |
Multimodal Not comparable
GLM-5V-Turbo: 40.9 (#42), Mistral Large: —
| Benchmark | GLM-5V-Turbo | Mistral Large |
|---|---|---|
| LMArena Vision | 1264 | — |
| LMArena Document | 1416 | — |
Multilingual GLM-5V-Turbo leads
GLM-5V-Turbo: 53.0 (#73), Mistral Large: 40.0 (#219)
| Benchmark | GLM-5V-Turbo | Mistral Large |
|---|---|---|
| LMArena Non-English | 1420 | 1237 |
| LMArena Chinese | 1488 | 1240 |
| LMArena French | 1444 | 1325 |
| LMArena German | 1423 | 1254 |
| LMArena Korean | 1396 | 1202 |
| LMArena Russian | 1431 | 1257 |
| LMArena Spanish | 1450 | 1268 |
| LMArena Japanese | — | 1188 |
Instruction Following GLM-5V-Turbo leads
GLM-5V-Turbo: 75.0 (#80), Mistral Large: 67.9 (#191)
| Benchmark | GLM-5V-Turbo | Mistral Large |
|---|---|---|
| LMArena Instruction Following | 1423 | 1249 |
| LiveBench Instruction Following | — | 67.9% |
| IFEval | — | 87.7% |
Long Context GLM-5V-Turbo leads
GLM-5V-Turbo: 44.0 (#80), Mistral Large: 38.3 (#199)
| Benchmark | GLM-5V-Turbo | Mistral Large |
|---|---|---|
| LMArena Longer Query | 1438 | 1261 |
Writing & Preference GLM-5V-Turbo leads
GLM-5V-Turbo: 62.5 (#73), Mistral Large: 40.7 (#242)
| Benchmark | GLM-5V-Turbo | Mistral Large |
|---|---|---|
| LMArena Text | 1437 | 1266 |
| LMArena Creative Writing | 1416 | 1243 |
| LMArena Multi-Turn | 1432 | 1260 |
| Short-Story Creative Writing | — | 69% |
| EQ-Bench Creative Writing | — | 985 |
| WildBench | — | 80.1% |
| LiveBench Language | — | 39.4% |
Frequently asked questions
Is GLM-5V-Turbo better than Mistral Large?
GLM-5V-Turbo is the stronger model overall, scoring 43.8 to 31.9 on the Noometry Index.
Which is cheaper, GLM-5V-Turbo or Mistral Large?
GLM-5V-Turbo is cheaper. It lists at $1.20 per million input tokens and $4 per million output tokens; Mistral Large lists at $2 and $6.
Is GLM-5V-Turbo or Mistral Large better for coding?
GLM-5V-Turbo scores higher on coding benchmarks: 42.1 versus 34.3 in the Noometry coding category.
Which has the bigger context window?
GLM-5V-Turbo does, with 200K tokens against 131K.
How many benchmarks do GLM-5V-Turbo and Mistral Large share?
16 benchmarks have published results for both models. GLM-5V-Turbo has 19 scored results on Noometry and Mistral Large has 51.