Model comparison
GLM-5 vs Mistral Medium
GLM-5 is the stronger model overall, scoring 46.1 to 36.3 on the Noometry Index.
Last verified . 24 shared benchmarks.
Mistral AISummary
- They share 24 benchmarks with published results for both. GLM-5 scores higher in 9 categories and Mistral Medium in 0 categories; 9 gaps are clear of the uncertainty.
- The widest gap is in knowledge, where GLM-5 leads 52.3 to 25.0.
- The biggest single-benchmark swing is OTIS Mock AIME 2024-2025: 80% for GLM-5 and 32.2% for Mistral Medium.
- GLM-5 is cheaper at $1 / $3.20 per million input/output tokens, against $1.50 / $7.50 for Mistral Medium.
- Mistral Medium accepts more context: 262K tokens versus 205K.
Side by side
| GLM-5 | Mistral Medium | |
|---|---|---|
| Provider | Z.ai (Zhipu) | Mistral AI |
| Noometry Index | 46.1 | 36.3 |
| Released | 2026-02-11 | 2023-12-11 |
| Weights | Open | Open |
| Context window | 205K | 262K |
| Max output | 131K | 262K |
| Input $ / M tokens | $1 | $1.50 |
| Output $ / M tokens | $3.20 | $7.50 |
| Results tracked | 45 | 36 |
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Category by category
Coding GLM-5 leads
GLM-5: 49.0 (#52), Mistral Medium: 34.2 (#243)
| Benchmark | GLM-5 | Mistral Medium |
|---|---|---|
| WeirdML | 48.2% | 43.7% |
| LMArena Coding | 1461 | 1434 |
| ALE-Bench | 765.62 | 763.98 |
| SWE-bench Verified | 72.1% | — |
| FrontierCode | — | 8% |
| SWE-bench Verified (bash only) | 72.8% | — |
| LMArena WebDev | 1434 | — |
| SWE-bench Multilingual | 69.7% | — |
| SciCode | — | 40.2% |
Agentic & Tool Use GLM-5 leads
GLM-5: 31.1 (#71), Mistral Medium: 28.3 (#90)
| Benchmark | GLM-5 | Mistral Medium |
|---|---|---|
| Terminal-Bench | 52.4% | — |
| Berkeley Function Calling Leaderboard | — | 37.7% |
| τ²-bench Airline | 82.5% | — |
| τ²-bench Banking | 9.8% | — |
| τ²-bench Retail | 73.7% | — |
| τ²-bench Telecom | 86.8% | — |
| Vending-Bench 2 | 4,432 | — |
Reasoning GLM-5 leads
GLM-5: 27.6 (#116), Mistral Medium: 24.0 (#167)
| Benchmark | GLM-5 | Mistral Medium |
|---|---|---|
| Kagi LLM Benchmark | 75% | 50% |
| LMArena Hard Prompts | 1452 | 1426 |
| ARC-AGI-2 | 4.9% | — |
| SimpleBench | 53.2% | — |
| NYT Connections (extended) | 74.8% | — |
| ARC-AGI-1 | 44.7% | — |
| CritPt | — | 0% |
| Chess Puzzles | 10% | — |
| DTBench | — | 75.5% |
| LMCA | — | 26.1% |
| Surface Evolver Bench | — | 26.9% |
| Epoch Capabilities Index | 145.83 | — |
| ForecastBench | 61 | — |
Math GLM-5 leads
GLM-5: 46.4 (#71), Mistral Medium: 28.1 (#245)
| Benchmark | GLM-5 | Mistral Medium |
|---|---|---|
| OTIS Mock AIME 2024-2025 | 80% | 32.2% |
| LMArena Math | 1440 | 1408 |
| FrontierMath (Feb 2025 set) | 16.4% | 0.3% |
| MathArena Final-Answer Competitions | 65.7% | — |
| ProofBench | — | 9% |
| MATH Level 5 | — | 81.6% |
| FrontierMath Tier 4 (v1) | 2.1% | — |
Knowledge GLM-5 leads
GLM-5: 52.3 (#64), Mistral Medium: 25.0 (#265)
| Benchmark | GLM-5 | Mistral Medium |
|---|---|---|
| GPQA Diamond | 87.8% | 59.5% |
| Vectara Hallucination Rate | 10.1% | 22.7% |
| LMArena Expert | 1454 | 1408 |
| Humanity's Last Exam | — | 4.5% |
Multimodal Not comparable
GLM-5: —, Mistral Medium: 35.3 (#88)
| Benchmark | GLM-5 | Mistral Medium |
|---|---|---|
| LMArena Vision | — | 1172 |
Multilingual GLM-5 leads
GLM-5: 53.7 (#58), Mistral Medium: 52.1 (#91)
| Benchmark | GLM-5 | Mistral Medium |
|---|---|---|
| LMArena Non-English | 1430 | 1408 |
| LMArena Chinese | 1511 | 1447 |
| LMArena French | 1455 | 1459 |
| LMArena German | 1445 | 1432 |
| LMArena Japanese | 1416 | 1378 |
| LMArena Korean | 1423 | 1380 |
| LMArena Russian | 1436 | 1411 |
| LMArena Spanish | 1454 | 1433 |
Instruction Following GLM-5 leads
GLM-5: 75.2 (#67), Mistral Medium: 73.7 (#116)
| Benchmark | GLM-5 | Mistral Medium |
|---|---|---|
| LMArena Instruction Following | 1428 | 1398 |
Long Context GLM-5 leads
GLM-5: 44.7 (#60), Mistral Medium: 42.9 (#114)
| Benchmark | GLM-5 | Mistral Medium |
|---|---|---|
| LMArena Longer Query | 1446 | 1406 |
| CL-bench | 18.7% | — |
Writing & Preference GLM-5 leads
GLM-5: 66.0 (#38), Mistral Medium: 60.0 (#103)
| Benchmark | GLM-5 | Mistral Medium |
|---|---|---|
| LMArena Text | 1446 | 1424 |
| LMArena Creative Writing | 1439 | 1391 |
| LMArena Multi-Turn | 1456 | 1418 |
| Short-Story Creative Writing | — | 77.3% |
| EQ-Bench Creative Writing | 1601 | — |
Frequently asked questions
Is GLM-5 better than Mistral Medium?
GLM-5 is the stronger model overall, scoring 46.1 to 36.3 on the Noometry Index.
Which is cheaper, GLM-5 or Mistral Medium?
GLM-5 is cheaper. It lists at $1 per million input tokens and $3.20 per million output tokens; Mistral Medium lists at $1.50 and $7.50.
Is GLM-5 or Mistral Medium better for coding?
GLM-5 scores higher on coding benchmarks: 49.0 versus 34.2 in the Noometry coding category.
Which has the bigger context window?
Mistral Medium does, with 262K tokens against 205K.
How many benchmarks do GLM-5 and Mistral Medium share?
24 benchmarks have published results for both models. GLM-5 has 45 scored results on Noometry and Mistral Medium has 36.