Model comparison
GLM-5 vs MiMo-V2-Pro
GLM-5 is the stronger model overall, scoring 45.9 to 42.4 on the Noometry Index. MiMo-V2-Pro costs 2.9× less per token, which makes it the better buy when GLM-5's lead doesn't matter for your workload.
Last verified . 21 shared benchmarks.
Summary
- They share 21 benchmarks with published results for both. GLM-5 scores higher in 7 categories and MiMo-V2-Pro in 1 category; 7 gaps are clear of the uncertainty.
- The widest gap is in knowledge, where GLM-5 leads 52.2 to 40.8.
- The biggest single-benchmark swing is NYT Connections (extended): 74.8% for GLM-5 and 25.8% for MiMo-V2-Pro.
- MiMo-V2-Pro is cheaper at $0.43 / $0.87 per million input/output tokens, against $1 / $3.20 for GLM-5.
- MiMo-V2-Pro accepts more context: 1.05M tokens versus 205K.
- GLM-5 has downloadable open weights; the other is API-only.
Side by side
| GLM-5 | MiMo-V2-Pro | |
|---|---|---|
| Provider | Z.ai (Zhipu) | Xiaomi |
| Noometry Index | 45.9 | 42.4 |
| Released | 2026-02-11 | 2026-03-18 |
| Weights | Open | Proprietary |
| Context window | 205K | 1.05M |
| Max output | 131K | 131K |
| Input $ / M tokens | $1 | $0.43 |
| Output $ / M tokens | $3.20 | $0.87 |
| Results tracked | 45 | 23 |
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Category by category
Coding GLM-5 leads
GLM-5: 49.0 (#47), MiMo-V2-Pro: 43.4 (#76)
| Benchmark | GLM-5 | MiMo-V2-Pro |
|---|---|---|
| LMArena WebDev | 1434 | 1433 |
| LMArena Coding | 1461 | 1476 |
| ALE-Bench | 765.62 | 785.17 |
| SWE-bench Verified | 72.1% | — |
| SWE-bench Verified (bash only) | 72.8% | — |
| SWE-bench Multilingual | 69.7% | — |
| WeirdML | 48.2% | — |
Agentic & Tool Use Not comparable
GLM-5: 30.9 (#65), MiMo-V2-Pro: —
| Benchmark | GLM-5 | MiMo-V2-Pro |
|---|---|---|
| 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), MiMo-V2-Pro: 21.3 (#200)
| Benchmark | GLM-5 | MiMo-V2-Pro |
|---|---|---|
| NYT Connections (extended) | 74.8% | 25.8% |
| LMArena Hard Prompts | 1451 | 1457 |
| ARC-AGI-2 | 4.9% | — |
| SimpleBench | 53.2% | — |
| Kagi LLM Benchmark | 75% | — |
| ARC-AGI-1 | 44.7% | — |
| Chess Puzzles | 10% | — |
| Thematic Generalization | — | 45.9% |
| Epoch Capabilities Index | 145.84 | — |
| ForecastBench | 61 | — |
Math GLM-5 leads
GLM-5: 44.8 (#66), MiMo-V2-Pro: 36.7 (#104)
| Benchmark | GLM-5 | MiMo-V2-Pro |
|---|---|---|
| LMArena Math | 1440 | 1447 |
| 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: 52.2 (#59), MiMo-V2-Pro: 40.8 (#106)
| Benchmark | GLM-5 | MiMo-V2-Pro |
|---|---|---|
| LMArena Expert | 1454 | 1479 |
| GPQA Diamond | 87.8% | — |
| Vectara Hallucination Rate | 10.1% | — |
Multilingual GLM-5 leads
GLM-5: 53.9 (#57), MiMo-V2-Pro: 52.9 (#77)
| Benchmark | GLM-5 | MiMo-V2-Pro |
|---|---|---|
| LMArena Non-English | 1430 | 1416 |
| LMArena Chinese | 1511 | 1455 |
| LMArena French | 1455 | 1470 |
| LMArena German | 1445 | 1417 |
| LMArena Japanese | 1416 | 1366 |
| LMArena Korean | 1421 | 1401 |
| LMArena Russian | 1436 | 1427 |
| LMArena Spanish | 1452 | 1458 |
Instruction Following Too close to call
GLM-5: 75.4 (#64), MiMo-V2-Pro: 76.2 (#46)
| Benchmark | GLM-5 | MiMo-V2-Pro |
|---|---|---|
| LMArena Instruction Following | 1427 | 1444 |
Long Context GLM-5 leads
GLM-5: 44.6 (#58), MiMo-V2-Pro: 41.5 (#133)
| Benchmark | GLM-5 | MiMo-V2-Pro |
|---|---|---|
| CL-bench | 18.7% | 15.7% |
| LMArena Longer Query | 1446 | 1455 |
| CL-bench Life | — | 6.9% |
Writing & Preference GLM-5 leads
GLM-5: 66.2 (#38), MiMo-V2-Pro: 62.9 (#67)
| Benchmark | GLM-5 | MiMo-V2-Pro |
|---|---|---|
| LMArena Text | 1446 | 1436 |
| LMArena Creative Writing | 1438 | 1415 |
| LMArena Multi-Turn | 1456 | 1456 |
| EQ-Bench Creative Writing | 1601 | — |
Frequently asked questions
Is GLM-5 better than MiMo-V2-Pro?
GLM-5 is the stronger model overall, scoring 45.9 to 42.4 on the Noometry Index. MiMo-V2-Pro costs 2.9× 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 MiMo-V2-Pro?
MiMo-V2-Pro is cheaper. It lists at $0.43 per million input tokens and $0.87 per million output tokens; GLM-5 lists at $1 and $3.20.
Is GLM-5 or MiMo-V2-Pro better for coding?
GLM-5 scores higher on coding benchmarks: 49.0 versus 43.4 in the Noometry coding category.
Which has the bigger context window?
MiMo-V2-Pro does, with 1.05M tokens against 205K.
How many benchmarks do GLM-5 and MiMo-V2-Pro share?
21 benchmarks have published results for both models. GLM-5 has 45 scored results on Noometry and MiMo-V2-Pro has 23.