Model comparison
GLM-5V-Turbo vs Mistral Small
GLM-5V-Turbo is the stronger model overall, scoring 43.8 to 33.4 on the Noometry Index. Mistral Small costs 7.2× less per token, which makes it the better buy when GLM-5V-Turbo's lead doesn't matter for your workload.
Last verified . 17 shared benchmarks.
Mistral AISummary
- They share 17 benchmarks with published results for both. GLM-5V-Turbo scores higher in 9 categories and Mistral Small in 0 categories; 9 gaps are clear of the uncertainty.
- The widest gap is in math, where GLM-5V-Turbo leads 39.4 to 16.4.
- Mistral Small is cheaper at $0.15 / $0.60 per million input/output tokens, against $1.20 / $4 for GLM-5V-Turbo.
- Mistral Small accepts more context: 262K tokens versus 200K.
- Mistral Small has downloadable open weights; the other is API-only.
Side by side
| GLM-5V-Turbo | Mistral Small | |
|---|---|---|
| Provider | Z.ai (Zhipu) | Mistral AI |
| Noometry Index | 43.8 | 33.4 |
| Released | 2026-04-01 | 2024-02-26 |
| Weights | Proprietary | Open |
| Context window | 200K | 262K |
| Max output | 131K | 256K |
| Input $ / M tokens | $1.20 | $0.15 |
| Output $ / M tokens | $4 | $0.60 |
| Results tracked | 19 | 39 |
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Category by category
Coding GLM-5V-Turbo leads
GLM-5V-Turbo: 42.1 (#111), Mistral Small: 34.0 (#247)
| Benchmark | GLM-5V-Turbo | Mistral Small |
|---|---|---|
| LMArena Coding | 1466 | 1362 |
| LMArena WebDev | 1401 | — |
| SciCode | — | 26.5% |
| BigCodeBench Instruct | — | 36.1% |
| LiveBench Coding | — | 36.2% |
| BigCodeBench Complete | — | 46.6% |
| ALE-Bench | — | 497.62 |
Agentic & Tool Use Not comparable
GLM-5V-Turbo: —, Mistral Small: 28.1 (#93)
| Benchmark | GLM-5V-Turbo | Mistral Small |
|---|---|---|
| Berkeley Function Calling Leaderboard | — | 37.1% |
Reasoning GLM-5V-Turbo leads
GLM-5V-Turbo: 29.7 (#89), Mistral Small: 19.8 (#250)
| Benchmark | GLM-5V-Turbo | Mistral Small |
|---|---|---|
| LMArena Hard Prompts | 1443 | 1335 |
| Kagi LLM Benchmark | — | 37.8% |
| CritPt | — | 0% |
| LiveBench Reasoning | — | 44.8% |
| DTBench | — | 70.9% |
| LiveBench Data Analysis | — | 53.7% |
| LMCA | — | 20.6% |
| LiveBench | — | 44% |
Math GLM-5V-Turbo leads
GLM-5V-Turbo: 39.4 (#106), Mistral Small: 16.4 (#293)
| Benchmark | GLM-5V-Turbo | Mistral Small |
|---|---|---|
| LMArena Math | 1441 | 1341 |
| OTIS Mock AIME 2024-2025 | — | 5.8% |
| LiveBench Math | — | 39.9% |
| MATH Level 5 | — | 46.8% |
Knowledge GLM-5V-Turbo leads
GLM-5V-Turbo: 40.6 (#117), Mistral Small: 31.0 (#222)
| Benchmark | GLM-5V-Turbo | Mistral Small |
|---|---|---|
| LMArena Expert | 1452 | 1291 |
| GPQA Diamond | — | 47.5% |
| Vectara Hallucination Rate | — | 5.1% |
| MMLU | — | 68.7% |
Multimodal GLM-5V-Turbo leads
GLM-5V-Turbo: 40.9 (#42), Mistral Small: 33.5 (#96)
| Benchmark | GLM-5V-Turbo | Mistral Small |
|---|---|---|
| LMArena Vision | 1264 | 1142 |
| LMArena Document | 1416 | — |
Multilingual GLM-5V-Turbo leads
GLM-5V-Turbo: 53.0 (#73), Mistral Small: 45.5 (#169)
| Benchmark | GLM-5V-Turbo | Mistral Small |
|---|---|---|
| LMArena Non-English | 1420 | 1315 |
| LMArena Chinese | 1488 | 1340 |
| LMArena French | 1444 | 1337 |
| LMArena German | 1423 | 1340 |
| LMArena Korean | 1396 | 1259 |
| LMArena Russian | 1431 | 1324 |
| LMArena Spanish | 1450 | 1346 |
| LMArena Japanese | — | 1275 |
Instruction Following GLM-5V-Turbo leads
GLM-5V-Turbo: 75.0 (#80), Mistral Small: 66.4 (#209)
| Benchmark | GLM-5V-Turbo | Mistral Small |
|---|---|---|
| LMArena Instruction Following | 1423 | 1310 |
| LiveBench Instruction Following | — | 63.7% |
Long Context GLM-5V-Turbo leads
GLM-5V-Turbo: 44.0 (#80), Mistral Small: 40.4 (#156)
| Benchmark | GLM-5V-Turbo | Mistral Small |
|---|---|---|
| LMArena Longer Query | 1438 | 1327 |
Writing & Preference GLM-5V-Turbo leads
GLM-5V-Turbo: 62.5 (#73), Mistral Small: 52.5 (#171)
| Benchmark | GLM-5V-Turbo | Mistral Small |
|---|---|---|
| LMArena Text | 1437 | 1338 |
| LMArena Creative Writing | 1416 | 1305 |
| LMArena Multi-Turn | 1432 | 1344 |
| LiveBench Language | — | 30.5% |
Frequently asked questions
Is GLM-5V-Turbo better than Mistral Small?
GLM-5V-Turbo is the stronger model overall, scoring 43.8 to 33.4 on the Noometry Index. Mistral Small costs 7.2× less per token, which makes it the better buy when GLM-5V-Turbo's lead doesn't matter for your workload.
Which is cheaper, GLM-5V-Turbo or Mistral Small?
Mistral Small is cheaper. It lists at $0.15 per million input tokens and $0.60 per million output tokens; GLM-5V-Turbo lists at $1.20 and $4.
Is GLM-5V-Turbo or Mistral Small better for coding?
GLM-5V-Turbo scores higher on coding benchmarks: 42.1 versus 34.0 in the Noometry coding category.
Which has the bigger context window?
Mistral Small does, with 262K tokens against 200K.
How many benchmarks do GLM-5V-Turbo and Mistral Small share?
17 benchmarks have published results for both models. GLM-5V-Turbo has 19 scored results on Noometry and Mistral Small has 39.