Model comparison
GLM-5.1 vs Mistral Medium 3.5
GLM-5.1 is the stronger model overall, scoring 47.6 to 39.6 on the Noometry Index.
Last verified . 19 shared benchmarks.
Mistral AISummary
- They share 19 benchmarks with published results for both. GLM-5.1 scores higher in 8 categories and Mistral Medium 3.5 in 0 categories; 8 gaps are clear of the uncertainty.
- The widest gap is in reasoning, where GLM-5.1 leads 38.2 to 16.6.
- The biggest single-benchmark swing is NYT Connections (extended): 77.7% for GLM-5.1 and 12.9% for Mistral Medium 3.5.
- GLM-5.1 is cheaper at $1.40 / $4.40 per million input/output tokens, against $1.50 / $7.50 for Mistral Medium 3.5.
- Mistral Medium 3.5 accepts more context: 262K tokens versus 200K.
Side by side
| GLM-5.1 | Mistral Medium 3.5 | |
|---|---|---|
| Provider | Z.ai (Zhipu) | Mistral AI |
| Noometry Index | 47.6 | 39.6 |
| Released | 2026-04-07 | — |
| Weights | Open | Open |
| Context window | 200K | 262K |
| Max output | 131K | 210K |
| Input $ / M tokens | $1.40 | $1.50 |
| Output $ / M tokens | $4.40 | $7.50 |
| Results tracked | 41 | 22 |
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Category by category
Coding GLM-5.1 leads
GLM-5.1: 48.5 (#52), Mistral Medium 3.5: 35.7 (#208)
| Benchmark | GLM-5.1 | Mistral Medium 3.5 |
|---|---|---|
| LMArena WebDev | 1509 | 1263 |
| LMArena Coding | 1486 | 1461 |
| SWE-bench Verified | 74.2% | — |
| SciCode | 43.8% | — |
| WeirdML | 57.1% | — |
| ALE-Bench | 887.1 | — |
Agentic & Tool Use Not comparable
GLM-5.1: 24.8 (#106), Mistral Medium 3.5: —
| Benchmark | GLM-5.1 | Mistral Medium 3.5 |
|---|---|---|
| APEX-Agents | 40.9% | — |
| ExploitBench | 18.1% | — |
| GBAEval | 0% | — |
| Vending-Bench 2 | 5,634 | — |
Reasoning GLM-5.1 leads
GLM-5.1: 38.2 (#57), Mistral Medium 3.5: 16.6 (#290)
| Benchmark | GLM-5.1 | Mistral Medium 3.5 |
|---|---|---|
| NYT Connections (extended) | 77.7% | 12.9% |
| LMArena Hard Prompts | 1472 | 1436 |
| Epoch Capabilities Index | 149.86 | 141.42 |
| SimpleBench | 55.1% | — |
| Kagi LLM Benchmark | — | 41.4% |
| CritPt | 4.6% | — |
| Chess Puzzles | 19% | — |
| Thematic Generalization | 69.8% | — |
Math GLM-5.1 leads
GLM-5.1: 49.0 (#48), Mistral Medium 3.5: 36.4 (#113)
| Benchmark | GLM-5.1 | Mistral Medium 3.5 |
|---|---|---|
| LMArena Math | 1472 | 1432 |
| FrontierMath (Tiers 1-3) | 36.8% | — |
| MathArena Final-Answer Competitions | 67.1% | — |
| OTIS Mock AIME 2024-2025 | 93.3% | — |
| ProofBench | 22.2% | — |
| FrontierMath (Feb 2025 set) | 33.4% | — |
| FrontierMath Tier 4 (v1) | 12.5% | — |
Knowledge GLM-5.1 leads
GLM-5.1: 55.0 (#45), Mistral Medium 3.5: 39.3 (#123)
| Benchmark | GLM-5.1 | Mistral Medium 3.5 |
|---|---|---|
| LMArena Expert | 1477 | 1431 |
| GPQA Diamond | 89.9% | — |
| SimpleQA Verified | 34% | — |
Multimodal Not comparable
GLM-5.1: —, Mistral Medium 3.5: 37.6 (#64)
| Benchmark | GLM-5.1 | Mistral Medium 3.5 |
|---|---|---|
| LMArena Vision | — | 1222 |
Multilingual GLM-5.1 leads
GLM-5.1: 55.2 (#34), Mistral Medium 3.5: 52.1 (#93)
| Benchmark | GLM-5.1 | Mistral Medium 3.5 |
|---|---|---|
| LMArena Non-English | 1448 | 1405 |
| LMArena Chinese | 1516 | 1443 |
| LMArena French | 1478 | 1448 |
| LMArena German | 1466 | 1453 |
| LMArena Korean | 1423 | 1387 |
| LMArena Russian | 1453 | 1396 |
| LMArena Spanish | 1467 | 1406 |
| LMArena Japanese | 1436 | — |
Instruction Following GLM-5.1 leads
GLM-5.1: 76.5 (#41), Mistral Medium 3.5: 74.7 (#87)
| Benchmark | GLM-5.1 | Mistral Medium 3.5 |
|---|---|---|
| LMArena Instruction Following | 1451 | 1414 |
Long Context GLM-5.1 leads
GLM-5.1: 44.9 (#51), Mistral Medium 3.5: 43.2 (#101)
| Benchmark | GLM-5.1 | Mistral Medium 3.5 |
|---|---|---|
| LMArena Longer Query | 1467 | 1414 |
Writing & Preference GLM-5.1 leads
GLM-5.1: 67.2 (#29), Mistral Medium 3.5: 58.6 (#113)
| Benchmark | GLM-5.1 | Mistral Medium 3.5 |
|---|---|---|
| LMArena Text | 1462 | 1421 |
| LMArena Creative Writing | 1454 | 1372 |
| LMArena Multi-Turn | 1473 | 1423 |
| EQ-Bench Creative Writing | 1592 | — |
| EQ-Bench 4 | — | 993 |
Frequently asked questions
Is GLM-5.1 better than Mistral Medium 3.5?
GLM-5.1 is the stronger model overall, scoring 47.6 to 39.6 on the Noometry Index.
Which is cheaper, GLM-5.1 or Mistral Medium 3.5?
GLM-5.1 is cheaper. It lists at $1.40 per million input tokens and $4.40 per million output tokens; Mistral Medium 3.5 lists at $1.50 and $7.50.
Is GLM-5.1 or Mistral Medium 3.5 better for coding?
GLM-5.1 scores higher on coding benchmarks: 48.5 versus 35.7 in the Noometry coding category.
Which has the bigger context window?
Mistral Medium 3.5 does, with 262K tokens against 200K.
How many benchmarks do GLM-5.1 and Mistral Medium 3.5 share?
19 benchmarks have published results for both models. GLM-5.1 has 41 scored results on Noometry and Mistral Medium 3.5 has 22.