Model comparison
GLM-5 vs Mistral Small 3.2
GLM-5 is the stronger model overall, scoring 45.9 to 30.8 on the Noometry Index. Mistral Small 3.2 costs 12× less per token, which makes it the better buy when GLM-5's lead doesn't matter for your workload.
Last verified . 6 shared benchmarks.
Mistral AISummary
- They share 6 benchmarks with published results for both. GLM-5 scores higher in 4 categories and Mistral Small 3.2 in 0 categories; 4 gaps are clear of the uncertainty.
- The widest gap is in knowledge, where GLM-5 leads 52.2 to 26.8.
- The biggest single-benchmark swing is OTIS Mock AIME 2024-2025: 80% for GLM-5 and 30.3% for Mistral Small 3.2.
- Mistral Small 3.2 is cheaper at $0.0938 / $0.25 per million input/output tokens, against $1 / $3.20 for GLM-5.
- Mistral Small 3.2 accepts more context: 256K tokens versus 205K.
Side by side
| GLM-5 | Mistral Small 3.2 | |
|---|---|---|
| Provider | Z.ai (Zhipu) | Mistral AI |
| Noometry Index | 45.9 | 30.8 |
| Released | 2026-02-11 | 2025-06-20 |
| Weights | Open | Open |
| Context window | 205K | 256K |
| Max output | 131K | 16K |
| Input $ / M tokens | $1 | $0.0938 |
| Output $ / M tokens | $3.20 | $0.25 |
| Results tracked | 45 | 6 |
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Category by category
Coding Not comparable
GLM-5: 49.0 (#47), Mistral Small 3.2: —
| Benchmark | GLM-5 | Mistral Small 3.2 |
|---|---|---|
| SWE-bench Verified | 72.1% | — |
| SWE-bench Verified (bash only) | 72.8% | — |
| LMArena WebDev | 1434 | — |
| SWE-bench Multilingual | 69.7% | — |
| WeirdML | 48.2% | — |
| LMArena Coding | 1461 | — |
| ALE-Bench | 765.62 | — |
Agentic & Tool Use Not comparable
GLM-5: 30.9 (#65), Mistral Small 3.2: —
| Benchmark | GLM-5 | Mistral Small 3.2 |
|---|---|---|
| Terminal-Bench | 52.4% | — |
| 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 (#100), Mistral Small 3.2: 17.5 (#282)
| Benchmark | GLM-5 | Mistral Small 3.2 |
|---|---|---|
| Kagi LLM Benchmark | 75% | 40.4% |
| Chess Puzzles | 10% | 1% |
| Epoch Capabilities Index | 145.84 | 131.73 |
| ARC-AGI-2 | 4.9% | — |
| SimpleBench | 53.2% | — |
| NYT Connections (extended) | 74.8% | — |
| ARC-AGI-1 | 44.7% | — |
| LMArena Hard Prompts | 1451 | — |
| ForecastBench | 61 | — |
Math GLM-5 leads
GLM-5: 44.8 (#66), Mistral Small 3.2: 24.9 (#251)
| Benchmark | GLM-5 | Mistral Small 3.2 |
|---|---|---|
| OTIS Mock AIME 2024-2025 | 80% | 30.3% |
| MathArena Final-Answer Competitions | 65.7% | — |
| LMArena Math | 1440 | — |
| FrontierMath (Feb 2025 set) | 16.4% | — |
| FrontierMath Tier 4 (v1) | 2.1% | — |
Knowledge GLM-5 leads
GLM-5: 52.2 (#59), Mistral Small 3.2: 26.8 (#249)
| Benchmark | GLM-5 | Mistral Small 3.2 |
|---|---|---|
| GPQA Diamond | 87.8% | 49.1% |
| Vectara Hallucination Rate | 10.1% | — |
| LMArena Expert | 1454 | — |
Multilingual Not comparable
GLM-5: 53.9 (#57), Mistral Small 3.2: —
| Benchmark | GLM-5 | Mistral Small 3.2 |
|---|---|---|
| LMArena Non-English | 1430 | — |
| LMArena Chinese | 1511 | — |
| LMArena French | 1455 | — |
| LMArena German | 1445 | — |
| LMArena Japanese | 1416 | — |
| LMArena Korean | 1421 | — |
| LMArena Russian | 1436 | — |
| LMArena Spanish | 1452 | — |
Instruction Following Not comparable
GLM-5: 75.4 (#64), Mistral Small 3.2: —
| Benchmark | GLM-5 | Mistral Small 3.2 |
|---|---|---|
| LMArena Instruction Following | 1427 | — |
Long Context Not comparable
GLM-5: 44.6 (#58), Mistral Small 3.2: —
| Benchmark | GLM-5 | Mistral Small 3.2 |
|---|---|---|
| CL-bench | 18.7% | — |
| LMArena Longer Query | 1446 | — |
Writing & Preference GLM-5 leads
GLM-5: 66.2 (#38), Mistral Small 3.2: 45.1 (#219)
| Benchmark | GLM-5 | Mistral Small 3.2 |
|---|---|---|
| EQ-Bench Creative Writing | 1601 | 1255 |
| LMArena Text | 1446 | — |
| LMArena Creative Writing | 1438 | — |
| LMArena Multi-Turn | 1456 | — |
Frequently asked questions
Is GLM-5 better than Mistral Small 3.2?
GLM-5 is the stronger model overall, scoring 45.9 to 30.8 on the Noometry Index. Mistral Small 3.2 costs 12× less per token, which makes it the better buy when GLM-5's lead doesn't matter for your workload.
Which is cheaper, GLM-5 or Mistral Small 3.2?
Mistral Small 3.2 is cheaper. It lists at $0.0938 per million input tokens and $0.25 per million output tokens; GLM-5 lists at $1 and $3.20.
Which has the bigger context window?
Mistral Small 3.2 does, with 256K tokens against 205K.
How many benchmarks do GLM-5 and Mistral Small 3.2 share?
6 benchmarks have published results for both models. GLM-5 has 45 scored results on Noometry and Mistral Small 3.2 has 6.