Model comparison
GLM-5.1 vs Mistral Large 4
GLM-5.1 is the stronger model overall, scoring 47.8 to 43.1 on the Noometry Index. Mistral Large 4 costs 2.1× less per token, which makes it the better buy when GLM-5.1's lead doesn't matter for your workload.
Last verified . 15 shared benchmarks.
Mistral AISummary
- They share 15 benchmarks with published results for both. GLM-5.1 scores higher in 8 categories and Mistral Large 4 in 0 categories; 7 gaps are clear of the uncertainty.
- The widest gap is in knowledge, where GLM-5.1 leads 54.9 to 36.6.
- The biggest single-benchmark swing is NYT Connections (extended): 77.7% for GLM-5.1 and 27.4% for Mistral Large 4.
- Mistral Large 4 is cheaper at $0.68 / $2.09 per million input/output tokens, against $1.40 / $4.40 for GLM-5.1.
- Mistral Large 4 accepts more context: 1.05M tokens versus 200K.
- GLM-5.1 has downloadable open weights; the other is API-only.
Side by side
| GLM-5.1 | Mistral Large 4 | |
|---|---|---|
| Provider | Z.ai (Zhipu) | Mistral AI |
| Noometry Index | 47.8 | 43.1 |
| Released | 2026-04-07 | 2026-10-06 |
| Weights | Open | Proprietary |
| Context window | 200K | 1.05M |
| Max output | 131K | 262K |
| Input $ / M tokens | $1.40 | $0.68 |
| Output $ / M tokens | $4.40 | $2.09 |
| Results tracked | 41 | 15 |
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Category by category
Coding Too close to call
GLM-5.1: 48.7 (#55), Mistral Large 4: 48.6 (#57)
| Benchmark | GLM-5.1 | Mistral Large 4 |
|---|---|---|
| LMArena WebDev | 1508 | 1541 |
| LMArena Coding | 1485 | 1475 |
| SWE-bench Verified | 74.2% | — |
| SciCode | 43.8% | — |
| WeirdML | 57.1% | — |
| ALE-Bench | 887.1 | — |
Agentic & Tool Use Not comparable
GLM-5.1: 24.9 (#113), Mistral Large 4: —
| Benchmark | GLM-5.1 | Mistral Large 4 |
|---|---|---|
| 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 Large 4: 22.5 (#192)
| Benchmark | GLM-5.1 | Mistral Large 4 |
|---|---|---|
| NYT Connections (extended) | 77.7% | 27.4% |
| LMArena Hard Prompts | 1472 | 1444 |
| SimpleBench | 55.1% | — |
| CritPt | 4.6% | — |
| Chess Puzzles | 19% | — |
| Thematic Generalization | 69.8% | — |
| Epoch Capabilities Index | 149.84 | — |
Math GLM-5.1 leads
GLM-5.1: 49.7 (#60), Mistral Large 4: 40.4 (#91)
| Benchmark | GLM-5.1 | Mistral Large 4 |
|---|---|---|
| LMArena Math | 1473 | 1488 |
| 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: 54.9 (#50), Mistral Large 4: 36.6 (#166)
| Benchmark | GLM-5.1 | Mistral Large 4 |
|---|---|---|
| SimpleQA Verified | 34% | 20% |
| LMArena Expert | 1476 | 1447 |
| GPQA Diamond | 89.9% | — |
Multilingual GLM-5.1 leads
GLM-5.1: 55.0 (#36), Mistral Large 4: 52.6 (#82)
| Benchmark | GLM-5.1 | Mistral Large 4 |
|---|---|---|
| LMArena Non-English | 1447 | 1415 |
| LMArena Chinese | 1515 | 1491 |
| LMArena Russian | 1454 | 1414 |
| LMArena French | 1474 | — |
| LMArena German | 1465 | — |
| LMArena Japanese | 1434 | — |
| LMArena Korean | 1418 | — |
| LMArena Spanish | 1469 | — |
Instruction Following GLM-5.1 leads
GLM-5.1: 76.3 (#42), Mistral Large 4: 75.0 (#76)
| Benchmark | GLM-5.1 | Mistral Large 4 |
|---|---|---|
| LMArena Instruction Following | 1451 | 1424 |
Long Context GLM-5.1 leads
GLM-5.1: 44.9 (#53), Mistral Large 4: 43.6 (#89)
| Benchmark | GLM-5.1 | Mistral Large 4 |
|---|---|---|
| LMArena Longer Query | 1466 | 1429 |
Writing & Preference GLM-5.1 leads
GLM-5.1: 66.9 (#31), Mistral Large 4: 60.4 (#97)
| Benchmark | GLM-5.1 | Mistral Large 4 |
|---|---|---|
| LMArena Text | 1461 | 1427 |
| LMArena Creative Writing | 1453 | 1361 |
| LMArena Multi-Turn | 1472 | 1424 |
| EQ-Bench Creative Writing | 1592 | — |
Frequently asked questions
Is GLM-5.1 better than Mistral Large 4?
GLM-5.1 is the stronger model overall, scoring 47.8 to 43.1 on the Noometry Index. Mistral Large 4 costs 2.1× 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 Large 4?
Mistral Large 4 is cheaper. It lists at $0.68 per million input tokens and $2.09 per million output tokens; GLM-5.1 lists at $1.40 and $4.40.
Is GLM-5.1 or Mistral Large 4 better for coding?
They score almost the same on coding (48.7 vs 48.6); test both on your own repository before choosing.
Which has the bigger context window?
Mistral Large 4 does, with 1.05M tokens against 200K.
How many benchmarks do GLM-5.1 and Mistral Large 4 share?
15 benchmarks have published results for both models. GLM-5.1 has 41 scored results on Noometry and Mistral Large 4 has 15.