Benchmark profile
Multilingual Grade School Math (MGSM)
A multilingual benchmark that translates 250 grade school math problems from GSM8K into 10 typologically diverse languages: Bengali, German, Spanish, French, Japanese, Russian, Swahili, Telugu, Thai, and Chinese.
Data verifiedBenchmark score on MGSM — July 20, 2026
BenchLM mirrors the published score view for MGSM. DeepSeek V4 Flash Base leads the public snapshot at 85.7% , followed by DeepSeek V4 Pro Base (84.4%). BenchLM does not use these results to rank models overall.
DeepSeek V4 Flash Base
DeepSeek
deepseek-v4-flash-base
DeepSeek V4 Pro Base
DeepSeek
deepseek-v4-pro-base
Benchmark score table (2 models)
ScoreAbout MGSM
Year
2022
Tasks
250 problems × 11 languages
Format
Math word problems
Difficulty
Grade school math, multilingual
MGSM evaluates mathematical reasoning across languages, revealing that performance can vary significantly across languages, with lower-resource languages (Bengali, Swahili, Telugu) typically showing the largest gaps.
BenchLM freshness & provenance
Version
MGSM 2022
Refresh cadence
Static
Staleness state
Stale
Question availability
Public benchmark set
BenchLM uses freshness metadata to decide whether a benchmark should still be treated as a strong differentiator, a benchmark to watch, or a display-only reference. For the full scoring policy, see the BenchLM methodology page.
FAQ
What does MGSM measure?
A multilingual benchmark that translates 250 grade school math problems from GSM8K into 10 typologically diverse languages: Bengali, German, Spanish, French, Japanese, Russian, Swahili, Telugu, Thai, and Chinese.
Which model scores highest on MGSM?
DeepSeek V4 Flash Base by DeepSeek currently leads with a score of 85.7% on MGSM.
How many models are evaluated on MGSM?
2 AI models have been evaluated on MGSM on BenchLM.
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