Model comparison
GLM-4.5 vs MiMo-V2.5-Pro
MiMo-V2.5-Pro is the stronger model overall, scoring 45.2 to 42.0 on the Noometry Index.
Last verified . 19 shared benchmarks.
Summary
- They share 19 benchmarks with published results for both. GLM-4.5 scores higher in 1 category and MiMo-V2.5-Pro in 7 categories; 7 gaps are clear of the uncertainty.
- The widest gap is in writing & preference, where MiMo-V2.5-Pro leads 65.3 to 57.5.
- MiMo-V2.5-Pro is cheaper at $0.43 / $0.87 per million input/output tokens, against $0.60 / $2.20 for GLM-4.5.
- MiMo-V2.5-Pro accepts more context: 1.05M tokens versus 131K.
Side by side
| GLM-4.5 | MiMo-V2.5-Pro | |
|---|---|---|
| Provider | Z.ai (Zhipu) | Xiaomi |
| Noometry Index | 42.0 | 45.2 |
| Released | 2025-07-27 | 2026-04-22 |
| Weights | Open | Open |
| Context window | 131K | 1.05M |
| Max output | 98K | 131K |
| Input $ / M tokens | $0.60 | $0.43 |
| Output $ / M tokens | $2.20 | $0.87 |
| Results tracked | 27 | 27 |
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Category by category
Coding MiMo-V2.5-Pro leads
GLM-4.5: 41.4 (#125), MiMo-V2.5-Pro: 47.4 (#60)
| Benchmark | GLM-4.5 | MiMo-V2.5-Pro |
|---|---|---|
| LMArena Coding | 1434 | 1503 |
| ALE-Bench | 344.82 | 899.8 |
| SWE-bench Verified (bash only) | 54.2% | — |
| LMArena WebDev | — | 1479 |
| SciCode | — | 50.2% |
| WeirdML | 40.6% | — |
| AlgoTune | 1.52 | — |
Reasoning GLM-4.5 leads
GLM-4.5: 28.6 (#100), MiMo-V2.5-Pro: 26.8 (#130)
| Benchmark | GLM-4.5 | MiMo-V2.5-Pro |
|---|---|---|
| LMArena Hard Prompts | 1429 | 1488 |
| Kagi LLM Benchmark | 57.9% | — |
| NYT Connections (extended) | — | 34.4% |
| CritPt | — | 4% |
| DTBench | — | 84.5% |
| LMCA | — | 29.5% |
Math Too close to call
GLM-4.5: 39.0 (#116), MiMo-V2.5-Pro: 40.0 (#96)
| Benchmark | GLM-4.5 | MiMo-V2.5-Pro |
|---|---|---|
| LMArena Math | 1427 | 1481 |
| ProofBench | — | 22% |
Knowledge MiMo-V2.5-Pro leads
GLM-4.5: 35.9 (#179), MiMo-V2.5-Pro: 42.2 (#98)
| Benchmark | GLM-4.5 | MiMo-V2.5-Pro |
|---|---|---|
| LMArena Expert | 1433 | 1503 |
| Humanity's Last Exam | 8.3% | — |
| Confabulations | 11.3% | — |
Multilingual MiMo-V2.5-Pro leads
GLM-4.5: 52.8 (#77), MiMo-V2.5-Pro: 55.1 (#34)
| Benchmark | GLM-4.5 | MiMo-V2.5-Pro |
|---|---|---|
| LMArena Non-English | 1417 | 1449 |
| LMArena Chinese | 1465 | 1507 |
| LMArena French | 1418 | 1488 |
| LMArena German | 1407 | 1458 |
| LMArena Japanese | 1415 | 1412 |
| LMArena Korean | 1380 | 1437 |
| LMArena Russian | 1414 | 1450 |
| LMArena Spanish | 1454 | 1471 |
Instruction Following MiMo-V2.5-Pro leads
GLM-4.5: 74.1 (#104), MiMo-V2.5-Pro: 77.5 (#21)
| Benchmark | GLM-4.5 | MiMo-V2.5-Pro |
|---|---|---|
| LMArena Instruction Following | 1404 | 1477 |
Long Context MiMo-V2.5-Pro leads
GLM-4.5: 38.2 (#201), MiMo-V2.5-Pro: 45.4 (#37)
| Benchmark | GLM-4.5 | MiMo-V2.5-Pro |
|---|---|---|
| LMArena Longer Query | 1412 | 1483 |
| Fiction.LiveBench | 58.3% | — |
Writing & Preference MiMo-V2.5-Pro leads
GLM-4.5: 57.5 (#127), MiMo-V2.5-Pro: 65.3 (#49)
| Benchmark | GLM-4.5 | MiMo-V2.5-Pro |
|---|---|---|
| LMArena Text | 1430 | 1465 |
| LMArena Creative Writing | 1395 | 1440 |
| EQ-Bench Creative Writing | 1343 | 1493 |
| LMArena Multi-Turn | 1415 | 1477 |
| Short-Story Creative Writing | 73.4% | — |
| EQ-Bench 4 | — | 1208 |
Frequently asked questions
Is GLM-4.5 better than MiMo-V2.5-Pro?
MiMo-V2.5-Pro is the stronger model overall, scoring 45.2 to 42.0 on the Noometry Index.
Which is cheaper, GLM-4.5 or MiMo-V2.5-Pro?
MiMo-V2.5-Pro is cheaper. It lists at $0.43 per million input tokens and $0.87 per million output tokens; GLM-4.5 lists at $0.60 and $2.20.
Is GLM-4.5 or MiMo-V2.5-Pro better for coding?
MiMo-V2.5-Pro scores higher on coding benchmarks: 47.4 versus 41.4 in the Noometry coding category.
Which has the bigger context window?
MiMo-V2.5-Pro does, with 1.05M tokens against 131K.
How many benchmarks do GLM-4.5 and MiMo-V2.5-Pro share?
19 benchmarks have published results for both models. GLM-4.5 has 27 scored results on Noometry and MiMo-V2.5-Pro has 27.