Model comparison
GLM-5 vs MiniMax-M2.1
GLM-5 is the stronger model overall, scoring 46.1 to 38.9 on the Noometry Index. MiniMax-M2.1 costs 3.0× less per token, which makes it the better buy when GLM-5's lead doesn't matter for your workload.
Last verified . 22 shared benchmarks.
MiniMaxSummary
- They share 22 benchmarks with published results for both. GLM-5 scores higher in 9 categories and MiniMax-M2.1 in 0 categories; 9 gaps are clear of the uncertainty.
- The widest gap is in knowledge, where GLM-5 leads 52.3 to 38.3.
- The biggest single-benchmark swing is NYT Connections (extended): 74.8% for GLM-5 and 11.2% for MiniMax-M2.1.
- MiniMax-M2.1 is cheaper at $0.30 / $1.20 per million input/output tokens, against $1 / $3.20 for GLM-5.
Side by side
| GLM-5 | MiniMax-M2.1 | |
|---|---|---|
| Provider | Z.ai (Zhipu) | MiniMax |
| Noometry Index | 46.1 | 38.9 |
| Released | 2026-02-11 | 2025-12-23 |
| Weights | Open | Open |
| Context window | 205K | 205K |
| Max output | 131K | 131K |
| Input $ / M tokens | $1 | $0.30 |
| Output $ / M tokens | $3.20 | $1.20 |
| Results tracked | 45 | 22 |
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Category by category
Coding GLM-5 leads
GLM-5: 49.0 (#52), MiniMax-M2.1: 40.4 (#143)
| Benchmark | GLM-5 | MiniMax-M2.1 |
|---|---|---|
| LMArena WebDev | 1434 | 1384 |
| LMArena Coding | 1461 | 1421 |
| ALE-Bench | 765.62 | 623.83 |
| SWE-bench Verified | 72.1% | — |
| SWE-bench Verified (bash only) | 72.8% | — |
| SWE-bench Multilingual | 69.7% | — |
| WeirdML | 48.2% | — |
Agentic & Tool Use GLM-5 leads
GLM-5: 31.1 (#71), MiniMax-M2.1: 27.9 (#98)
| Benchmark | GLM-5 | MiniMax-M2.1 |
|---|---|---|
| Terminal-Bench | 52.4% | 36.6% |
| 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), MiniMax-M2.1: 16.6 (#302)
| Benchmark | GLM-5 | MiniMax-M2.1 |
|---|---|---|
| NYT Connections (extended) | 74.8% | 11.2% |
| LMArena Hard Prompts | 1452 | 1411 |
| ARC-AGI-2 | 4.9% | — |
| SimpleBench | 53.2% | — |
| Kagi LLM Benchmark | 75% | — |
| ARC-AGI-1 | 44.7% | — |
| Chess Puzzles | 10% | — |
| Epoch Capabilities Index | 145.83 | — |
| ForecastBench | 61 | — |
Math GLM-5 leads
GLM-5: 46.4 (#71), MiniMax-M2.1: 38.3 (#138)
| Benchmark | GLM-5 | MiniMax-M2.1 |
|---|---|---|
| LMArena Math | 1440 | 1397 |
| MathArena Final-Answer Competitions | 65.7% | — |
| OTIS Mock AIME 2024-2025 | 80% | — |
| FrontierMath (Feb 2025 set) | 16.4% | — |
| FrontierMath Tier 4 (v1) | 2.1% | — |
Knowledge GLM-5 leads
GLM-5: 52.3 (#64), MiniMax-M2.1: 38.3 (#147)
| Benchmark | GLM-5 | MiniMax-M2.1 |
|---|---|---|
| Vectara Hallucination Rate | 10.1% | 11.8% |
| LMArena Expert | 1454 | 1431 |
| GPQA Diamond | 87.8% | — |
Multilingual GLM-5 leads
GLM-5: 53.7 (#58), MiniMax-M2.1: 50.0 (#128)
| Benchmark | GLM-5 | MiniMax-M2.1 |
|---|---|---|
| LMArena Non-English | 1430 | 1378 |
| LMArena Chinese | 1511 | 1430 |
| LMArena French | 1455 | 1404 |
| LMArena German | 1445 | 1381 |
| LMArena Japanese | 1416 | 1287 |
| LMArena Korean | 1423 | 1298 |
| LMArena Russian | 1436 | 1387 |
| LMArena Spanish | 1454 | 1397 |
Instruction Following GLM-5 leads
GLM-5: 75.2 (#67), MiniMax-M2.1: 73.8 (#112)
| Benchmark | GLM-5 | MiniMax-M2.1 |
|---|---|---|
| LMArena Instruction Following | 1428 | 1400 |
Long Context GLM-5 leads
GLM-5: 44.7 (#60), MiniMax-M2.1: 43.2 (#101)
| Benchmark | GLM-5 | MiniMax-M2.1 |
|---|---|---|
| LMArena Longer Query | 1446 | 1416 |
| CL-bench | 18.7% | — |
Writing & Preference GLM-5 leads
GLM-5: 66.0 (#38), MiniMax-M2.1: 58.3 (#120)
| Benchmark | GLM-5 | MiniMax-M2.1 |
|---|---|---|
| LMArena Text | 1446 | 1392 |
| LMArena Creative Writing | 1439 | 1361 |
| LMArena Multi-Turn | 1456 | 1396 |
| EQ-Bench Creative Writing | 1601 | — |
Frequently asked questions
Is GLM-5 better than MiniMax-M2.1?
GLM-5 is the stronger model overall, scoring 46.1 to 38.9 on the Noometry Index. MiniMax-M2.1 costs 3.0× 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 MiniMax-M2.1?
MiniMax-M2.1 is cheaper. It lists at $0.30 per million input tokens and $1.20 per million output tokens; GLM-5 lists at $1 and $3.20.
Is GLM-5 or MiniMax-M2.1 better for coding?
GLM-5 scores higher on coding benchmarks: 49.0 versus 40.4 in the Noometry coding category.
Which has the bigger context window?
Both accept 205K tokens.
How many benchmarks do GLM-5 and MiniMax-M2.1 share?
22 benchmarks have published results for both models. GLM-5 has 45 scored results on Noometry and MiniMax-M2.1 has 22.