# GLM-5.3-Flash vs Mistral Small

> GLM-5.3-Flash is the stronger model overall, scoring 51.8 to 33.4 on the Noometry Index.

- Canonical page: https://noometry.com/compare/glm-5-3-flash-vs-mistral-small
- Last updated: 2026-10-11
- Shared benchmarks: 23

## Summary

- They share 23 benchmarks with published results for both. GLM-5.3-Flash scores higher in 10 categories and Mistral Small in 0 categories; 10 gaps are clear of the uncertainty.
- The widest gap is in math, where GLM-5.3-Flash leads 53.3 to 16.4.
- The biggest single-benchmark swing is OTIS Mock AIME 2024-2025: 93.9% for GLM-5.3-Flash and 5.8% for Mistral Small.
- GLM-5.3-Flash is cheaper at $0.15 / $0.50 per million input/output tokens, against $0.15 / $0.60 for Mistral Small.
- GLM-5.3-Flash accepts more context: 1M tokens versus 262K.

## Snapshot

| | GLM-5.3-Flash | Mistral Small |
|---|---|---|
| Provider | Z.ai (Zhipu) | Mistral AI |
| Noometry Index | 51.8 | 33.4 |
| Rank | 41 | 243 |
| Context | 1M | 262K |
| Input $/M | $0.15 | $0.15 |
| Output $/M | $0.50 | $0.60 |
| Weights | Open | Open |

## Coding

- GLM-5.3-Flash: 53.1 (#31)
- Mistral Small: 34.0 (#247)

| Benchmark | GLM-5.3-Flash | Mistral Small |
|---|---|---|
| SciCode | 51.6% | 26.5% |
| LMArena Coding | 1508 | 1362 |
| ALE-Bench | 303.55 | 497.62 |
| DeepSWE | 63.4% | — |
| FrontierCode | 31.8% | — |
| CursorBench | 36.8% | — |
| LMArena WebDev | 1609 | — |
| FrontierSWE | 18.1% | — |
| BigCodeBench Instruct | — | 36.1% |
| LiveBench Coding | — | 36.2% |
| BigCodeBench Complete | — | 46.6% |

## Agentic & Tool Use

- GLM-5.3-Flash: 34.2 (#47)
- Mistral Small: 28.1 (#93)

| Benchmark | GLM-5.3-Flash | Mistral Small |
|---|---|---|
| APEX-Agents | 52.8% | — |
| Berkeley Function Calling Leaderboard | — | 37.1% |
| GDP.pdf | 14% | — |

## Reasoning

- GLM-5.3-Flash: 48.0 (#42)
- Mistral Small: 19.8 (#250)

| Benchmark | GLM-5.3-Flash | Mistral Small |
|---|---|---|
| CritPt | 15.4% | 0% |
| LMArena Hard Prompts | 1491 | 1335 |
| ARC-AGI-2 | 65.8% | — |
| Kagi LLM Benchmark | — | 37.8% |
| ARC-AGI-1 | 91% | — |
| Chess Puzzles | 14% | — |
| LiveBench Reasoning | — | 44.8% |
| Mystery Game Puzzles | 8% | — |
| DTBench | — | 70.9% |
| LiveBench Data Analysis | — | 53.7% |
| LMCA | — | 20.6% |
| Surface Evolver Bench | 52.5% | — |
| Bench to the Future 3 | 0.15 | — |
| Epoch Capabilities Index | 151.88 | — |
| LiveBench | — | 44% |

## Math

- GLM-5.3-Flash: 53.3 (#47)
- Mistral Small: 16.4 (#293)

| Benchmark | GLM-5.3-Flash | Mistral Small |
|---|---|---|
| OTIS Mock AIME 2024-2025 | 93.9% | 5.8% |
| LMArena Math | 1500 | 1341 |
| FrontierMath (Tiers 1-3) | 55.8% | — |
| FrontierMath Tier 4 | 17.1% | — |
| ProofBench | 21% | — |
| LiveBench Math | — | 39.9% |
| MATH Level 5 | — | 46.8% |

## Knowledge

- GLM-5.3-Flash: 58.4 (#36)
- Mistral Small: 31.0 (#222)

| Benchmark | GLM-5.3-Flash | Mistral Small |
|---|---|---|
| GPQA Diamond | 90.2% | 47.5% |
| LMArena Expert | 1513 | 1291 |
| Vectara Hallucination Rate | — | 5.1% |
| MMLU | — | 68.7% |

## Multimodal

- GLM-5.3-Flash: 42.8 (#27)
- Mistral Small: 33.5 (#96)

| Benchmark | GLM-5.3-Flash | Mistral Small |
|---|---|---|
| LMArena Vision | 1296 | 1142 |

## Multilingual

- GLM-5.3-Flash: 56.0 (#25)
- Mistral Small: 45.5 (#169)

| Benchmark | GLM-5.3-Flash | Mistral Small |
|---|---|---|
| LMArena Non-English | 1462 | 1315 |
| LMArena Chinese | 1527 | 1340 |
| LMArena French | 1496 | 1337 |
| LMArena German | 1470 | 1340 |
| LMArena Japanese | 1429 | 1275 |
| LMArena Korean | 1446 | 1259 |
| LMArena Russian | 1469 | 1324 |
| LMArena Spanish | 1471 | 1346 |

## Instruction Following

- GLM-5.3-Flash: 77.5 (#20)
- Mistral Small: 66.4 (#209)

| Benchmark | GLM-5.3-Flash | Mistral Small |
|---|---|---|
| LMArena Instruction Following | 1478 | 1310 |
| LiveBench Instruction Following | — | 63.7% |

## Long Context

- GLM-5.3-Flash: 45.4 (#39)
- Mistral Small: 40.4 (#156)

| Benchmark | GLM-5.3-Flash | Mistral Small |
|---|---|---|
| LMArena Longer Query | 1482 | 1327 |

## Writing & Preference

- GLM-5.3-Flash: 65.3 (#50)
- Mistral Small: 52.5 (#171)

| Benchmark | GLM-5.3-Flash | Mistral Small |
|---|---|---|
| LMArena Text | 1471 | 1338 |
| LMArena Creative Writing | 1442 | 1305 |
| LMArena Multi-Turn | 1467 | 1344 |
| LiveBench Language | — | 30.5% |

## FAQ

### Is GLM-5.3-Flash better than Mistral Small?

GLM-5.3-Flash is the stronger model overall, scoring 51.8 to 33.4 on the Noometry Index.

### Which is cheaper, GLM-5.3-Flash or Mistral Small?

GLM-5.3-Flash is cheaper. It lists at $0.15 per million input tokens and $0.50 per million output tokens; Mistral Small lists at $0.15 and $0.60.

### Is GLM-5.3-Flash or Mistral Small better for coding?

GLM-5.3-Flash scores higher on coding benchmarks: 53.1 versus 34.0 in the Noometry coding category.

### Which has the bigger context window?

GLM-5.3-Flash does, with 1M tokens against 262K.

### How many benchmarks do GLM-5.3-Flash and Mistral Small share?

23 benchmarks have published results for both models. GLM-5.3-Flash has 40 scored results on Noometry and Mistral Small has 39.