Model comparison
GLM-5.3-Flash vs Mistral Small 3
GLM-5.3-Flash is the stronger model overall, scoring 49.6 to 30.9 on the Noometry Index. Mistral Small 3 costs 4.1× less per token, which makes it the better buy when GLM-5.3-Flash's lead doesn't matter for your workload.
Last verified . 20 shared benchmarks.
Mistral AISummary
- They share 20 benchmarks with published results for both. GLM-5.3-Flash scores higher in 8 categories and Mistral Small 3 in 0 categories; 8 gaps are clear of the uncertainty.
- The widest gap is in math, where GLM-5.3-Flash leads 53.1 to 15.3.
- The biggest single-benchmark swing is OTIS Mock AIME 2024-2025: 93.9% for GLM-5.3-Flash and 6.7% for Mistral Small 3.
- Mistral Small 3 is cheaper at $0.05 / $0.08 per million input/output tokens, against $0.15 / $0.50 for GLM-5.3-Flash.
- GLM-5.3-Flash accepts more context: 1M tokens versus 33K.
Side by side
| GLM-5.3-Flash | Mistral Small 3 | |
|---|---|---|
| Provider | Z.ai (Zhipu) | Mistral AI |
| Noometry Index | 49.6 | 30.9 |
| Released | 2026-08-20 | 2025-01-30 |
| Weights | Open | Open |
| Context window | 1M | 33K |
| Max output | 131K | 16K |
| Input $ / M tokens | $0.15 | $0.05 |
| Output $ / M tokens | $0.50 | $0.08 |
| Results tracked | 36 | 24 |
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Category by category
Coding GLM-5.3-Flash leads
GLM-5.3-Flash: 53.7 (#26), Mistral Small 3: 36.0 (#203)
| Benchmark | GLM-5.3-Flash | Mistral Small 3 |
|---|---|---|
| LMArena Coding | 1506 | 1246 |
| DeepSWE | 63.4% | — |
| FrontierCode | 31.8% | — |
| LMArena WebDev | 1614 | — |
| SciCode | 51.6% | — |
| BigCodeBench Instruct | — | 45.3% |
| BigCodeBench Complete | — | 50.4% |
| ALE-Bench | 303.55 | — |
Agentic & Tool Use Not comparable
GLM-5.3-Flash: 34.3 (#41), Mistral Small 3: —
| Benchmark | GLM-5.3-Flash | Mistral Small 3 |
|---|---|---|
| APEX-Agents | 52.8% | — |
| GDP.pdf | 14% | — |
Reasoning GLM-5.3-Flash leads
GLM-5.3-Flash: 31.7 (#69), Mistral Small 3: 18.2 (#269)
| Benchmark | GLM-5.3-Flash | Mistral Small 3 |
|---|---|---|
| Chess Puzzles | 14% | 0% |
| LMArena Hard Prompts | 1490 | 1233 |
| Epoch Capabilities Index | 151.9 | 127.06 |
| CritPt | 15.4% | — |
| Mystery Game Puzzles | 8% | — |
| Surface Evolver Bench | 52.5% | — |
| Bench to the Future 3 | 0.15 | — |
Math GLM-5.3-Flash leads
GLM-5.3-Flash: 53.1 (#38), Mistral Small 3: 15.3 (#290)
| Benchmark | GLM-5.3-Flash | Mistral Small 3 |
|---|---|---|
| OTIS Mock AIME 2024-2025 | 93.9% | 6.7% |
| LMArena Math | 1499 | 1240 |
| FrontierMath (Tiers 1-3) | 55.8% | — |
| FrontierMath Tier 4 | 17.1% | — |
| ProofBench | 21% | — |
Knowledge GLM-5.3-Flash leads
GLM-5.3-Flash: 58.4 (#33), Mistral Small 3: 25.0 (#258)
| Benchmark | GLM-5.3-Flash | Mistral Small 3 |
|---|---|---|
| GPQA Diamond | 90.2% | 47.3% |
| LMArena Expert | 1512 | 1202 |
| Confabulations | — | 25.2% |
Multimodal Not comparable
GLM-5.3-Flash: 42.6 (#25), Mistral Small 3: —
| Benchmark | GLM-5.3-Flash | Mistral Small 3 |
|---|---|---|
| LMArena Vision | 1304 | — |
Multilingual GLM-5.3-Flash leads
GLM-5.3-Flash: 56.2 (#24), Mistral Small 3: 37.5 (#231)
| Benchmark | GLM-5.3-Flash | Mistral Small 3 |
|---|---|---|
| LMArena Non-English | 1462 | 1198 |
| LMArena Chinese | 1529 | 1204 |
| LMArena French | 1495 | 1202 |
| LMArena German | 1457 | 1211 |
| LMArena Japanese | 1420 | 1111 |
| LMArena Korean | 1443 | 1188 |
| LMArena Russian | 1472 | 1216 |
| LMArena Spanish | 1471 | — |
Instruction Following GLM-5.3-Flash leads
GLM-5.3-Flash: 77.8 (#17), Mistral Small 3: 63.9 (#224)
| Benchmark | GLM-5.3-Flash | Mistral Small 3 |
|---|---|---|
| LMArena Instruction Following | 1480 | 1214 |
Long Context GLM-5.3-Flash leads
GLM-5.3-Flash: 45.3 (#41), Mistral Small 3: 37.8 (#206)
| Benchmark | GLM-5.3-Flash | Mistral Small 3 |
|---|---|---|
| LMArena Longer Query | 1479 | 1246 |
Writing & Preference GLM-5.3-Flash leads
GLM-5.3-Flash: 65.4 (#49), Mistral Small 3: 32.4 (#275)
| Benchmark | GLM-5.3-Flash | Mistral Small 3 |
|---|---|---|
| LMArena Text | 1471 | 1234 |
| LMArena Creative Writing | 1440 | 1195 |
| LMArena Multi-Turn | 1471 | 1217 |
| EQ-Bench Creative Writing | — | 707 |
Frequently asked questions
Is GLM-5.3-Flash better than Mistral Small 3?
GLM-5.3-Flash is the stronger model overall, scoring 49.6 to 30.9 on the Noometry Index. Mistral Small 3 costs 4.1× less per token, which makes it the better buy when GLM-5.3-Flash's lead doesn't matter for your workload.
Which is cheaper, GLM-5.3-Flash or Mistral Small 3?
Mistral Small 3 is cheaper. It lists at $0.05 per million input tokens and $0.08 per million output tokens; GLM-5.3-Flash lists at $0.15 and $0.50.
Is GLM-5.3-Flash or Mistral Small 3 better for coding?
GLM-5.3-Flash scores higher on coding benchmarks: 53.7 versus 36.0 in the Noometry coding category.
Which has the bigger context window?
GLM-5.3-Flash does, with 1M tokens against 33K.
How many benchmarks do GLM-5.3-Flash and Mistral Small 3 share?
20 benchmarks have published results for both models. GLM-5.3-Flash has 36 scored results on Noometry and Mistral Small 3 has 24.