Model comparison
GLM-5.1 vs Mistral Small 3.1
GLM-5.1 is the stronger model overall, scoring 47.8 to 31.7 on the Noometry Index. Mistral Small 3.1 costs 5.3× less per token, which makes it the better buy when GLM-5.1's lead doesn't matter for your workload.
Last verified . 22 shared benchmarks.
Mistral AISummary
- They share 22 benchmarks with published results for both. GLM-5.1 scores higher in 8 categories and Mistral Small 3.1 in 0 categories; 8 gaps are clear of the uncertainty.
- The widest gap is in math, where GLM-5.1 leads 49.7 to 14.7.
- The biggest single-benchmark swing is OTIS Mock AIME 2024-2025: 93.3% for GLM-5.1 and 3.9% for Mistral Small 3.1.
- Mistral Small 3.1 is cheaper at $0.35 / $0.56 per million input/output tokens, against $1.40 / $4.40 for GLM-5.1.
- GLM-5.1 accepts more context: 200K tokens versus 128K.
Side by side
| GLM-5.1 | Mistral Small 3.1 | |
|---|---|---|
| Provider | Z.ai (Zhipu) | Mistral AI |
| Noometry Index | 47.8 | 31.7 |
| Released | 2026-04-07 | 2025-03-17 |
| Weights | Open | Open |
| Context window | 200K | 128K |
| Max output | 131K | 102K |
| Input $ / M tokens | $1.40 | $0.35 |
| Output $ / M tokens | $4.40 | $0.56 |
| Results tracked | 41 | 28 |
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Category by category
Coding GLM-5.1 leads
GLM-5.1: 48.7 (#55), Mistral Small 3.1: 38.3 (#179)
| Benchmark | GLM-5.1 | Mistral Small 3.1 |
|---|---|---|
| LMArena Coding | 1485 | 1309 |
| SWE-bench Verified | 74.2% | — |
| LMArena WebDev | 1508 | — |
| SciCode | 43.8% | — |
| WeirdML | 57.1% | — |
| ALE-Bench | 887.1 | — |
Agentic & Tool Use Not comparable
GLM-5.1: 24.9 (#113), Mistral Small 3.1: —
| Benchmark | GLM-5.1 | Mistral Small 3.1 |
|---|---|---|
| APEX-Agents | 40.9% | — |
| ExploitBench | 18.1% | — |
| GBAEval | 0% | — |
| Vending-Bench 2 | 5,634 | — |
Reasoning GLM-5.1 leads
GLM-5.1: 39.1 (#60), Mistral Small 3.1: 19.7 (#254)
| Benchmark | GLM-5.1 | Mistral Small 3.1 |
|---|---|---|
| Chess Puzzles | 19% | 1% |
| LMArena Hard Prompts | 1472 | 1278 |
| Epoch Capabilities Index | 149.84 | 127.48 |
| SimpleBench | 55.1% | — |
| NYT Connections (extended) | 77.7% | — |
| CritPt | 4.6% | — |
| Thematic Generalization | 69.8% | — |
Math GLM-5.1 leads
GLM-5.1: 49.7 (#60), Mistral Small 3.1: 14.7 (#301)
| Benchmark | GLM-5.1 | Mistral Small 3.1 |
|---|---|---|
| OTIS Mock AIME 2024-2025 | 93.3% | 3.9% |
| LMArena Math | 1473 | 1262 |
| FrontierMath (Tiers 1-3) | 36.8% | — |
| MathArena Final-Answer Competitions | 67.1% | — |
| ProofBench | 22.2% | — |
| Omni-MATH | — | 24.8% |
| FrontierMath (Feb 2025 set) | 33.4% | — |
| FrontierMath Tier 4 (v1) | 12.5% | — |
Knowledge GLM-5.1 leads
GLM-5.1: 54.9 (#50), Mistral Small 3.1: 22.6 (#271)
| Benchmark | GLM-5.1 | Mistral Small 3.1 |
|---|---|---|
| GPQA Diamond | 89.9% | 41.9% |
| LMArena Expert | 1476 | 1257 |
| SimpleQA Verified | 34% | — |
| MMLU-Pro | — | 61% |
| GPQA (HELM) | — | 39.2% |
Multimodal Not comparable
GLM-5.1: —, Mistral Small 3.1: 33.2 (#99)
| Benchmark | GLM-5.1 | Mistral Small 3.1 |
|---|---|---|
| LMArena Vision | — | 1136 |
Multilingual GLM-5.1 leads
GLM-5.1: 55.0 (#36), Mistral Small 3.1: 41.2 (#209)
| Benchmark | GLM-5.1 | Mistral Small 3.1 |
|---|---|---|
| LMArena Non-English | 1447 | 1255 |
| LMArena Chinese | 1515 | 1253 |
| LMArena French | 1474 | 1273 |
| LMArena German | 1465 | 1266 |
| LMArena Japanese | 1434 | 1208 |
| LMArena Korean | 1418 | 1206 |
| LMArena Russian | 1454 | 1263 |
| LMArena Spanish | 1469 | 1283 |
Instruction Following GLM-5.1 leads
GLM-5.1: 76.3 (#42), Mistral Small 3.1: 63.6 (#230)
| Benchmark | GLM-5.1 | Mistral Small 3.1 |
|---|---|---|
| LMArena Instruction Following | 1451 | 1264 |
| IFEval | — | 75% |
Long Context GLM-5.1 leads
GLM-5.1: 44.9 (#53), Mistral Small 3.1: 39.5 (#178)
| Benchmark | GLM-5.1 | Mistral Small 3.1 |
|---|---|---|
| LMArena Longer Query | 1466 | 1299 |
Writing & Preference GLM-5.1 leads
GLM-5.1: 66.9 (#31), Mistral Small 3.1: 37.0 (#259)
| Benchmark | GLM-5.1 | Mistral Small 3.1 |
|---|---|---|
| LMArena Text | 1461 | 1277 |
| LMArena Creative Writing | 1453 | 1253 |
| EQ-Bench Creative Writing | 1592 | 761 |
| LMArena Multi-Turn | 1472 | 1270 |
| WildBench | — | 78.8% |
Frequently asked questions
Is GLM-5.1 better than Mistral Small 3.1?
GLM-5.1 is the stronger model overall, scoring 47.8 to 31.7 on the Noometry Index. Mistral Small 3.1 costs 5.3× less per token, which makes it the better buy when GLM-5.1's lead doesn't matter for your workload.
Which is cheaper, GLM-5.1 or Mistral Small 3.1?
Mistral Small 3.1 is cheaper. It lists at $0.35 per million input tokens and $0.56 per million output tokens; GLM-5.1 lists at $1.40 and $4.40.
Is GLM-5.1 or Mistral Small 3.1 better for coding?
GLM-5.1 scores higher on coding benchmarks: 48.7 versus 38.3 in the Noometry coding category.
Which has the bigger context window?
GLM-5.1 does, with 200K tokens against 128K.
How many benchmarks do GLM-5.1 and Mistral Small 3.1 share?
22 benchmarks have published results for both models. GLM-5.1 has 41 scored results on Noometry and Mistral Small 3.1 has 28.