Model comparison
GLM-4.5V vs MiMo-V2.5-Pro
MiMo-V2.5-Pro is the stronger model overall, scoring 45.2 to 39.8 on the Noometry Index.
Last verified . 13 shared benchmarks.
Summary
- They share 13 benchmarks with published results for both. GLM-4.5V 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 52.5.
- MiMo-V2.5-Pro is cheaper at $0.43 / $0.87 per million input/output tokens, against $0.60 / $1.80 for GLM-4.5V.
- MiMo-V2.5-Pro accepts more context: 1.05M tokens versus 64K.
Side by side
| GLM-4.5V | MiMo-V2.5-Pro | |
|---|---|---|
| Provider | Z.ai (Zhipu) | Xiaomi |
| Noometry Index | 39.8 | 45.2 |
| Released | 2025-08-11 | 2026-04-22 |
| Weights | Open | Open |
| Context window | 64K | 1.05M |
| Max output | 16K | 131K |
| Input $ / M tokens | $0.60 | $0.43 |
| Output $ / M tokens | $1.80 | $0.87 |
| Results tracked | 15 | 27 |
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Category by category
Coding MiMo-V2.5-Pro leads
GLM-4.5V: 39.5 (#155), MiMo-V2.5-Pro: 47.4 (#60)
| Benchmark | GLM-4.5V | MiMo-V2.5-Pro |
|---|---|---|
| LMArena Coding | 1347 | 1503 |
| LMArena WebDev | — | 1479 |
| SciCode | — | 50.2% |
| ALE-Bench | — | 899.8 |
Reasoning Too close to call
GLM-4.5V: 27.4 (#119), MiMo-V2.5-Pro: 26.8 (#130)
| Benchmark | GLM-4.5V | MiMo-V2.5-Pro |
|---|---|---|
| LMArena Hard Prompts | 1334 | 1488 |
| Kagi LLM Benchmark | 59.8% | — |
| NYT Connections (extended) | — | 34.4% |
| CritPt | — | 4% |
| DTBench | — | 84.5% |
| LMCA | — | 29.5% |
Math MiMo-V2.5-Pro leads
GLM-4.5V: 37.4 (#159), MiMo-V2.5-Pro: 40.0 (#96)
| Benchmark | GLM-4.5V | MiMo-V2.5-Pro |
|---|---|---|
| LMArena Math | 1354 | 1481 |
| ProofBench | — | 22% |
Knowledge MiMo-V2.5-Pro leads
GLM-4.5V: 37.5 (#156), MiMo-V2.5-Pro: 42.2 (#98)
| Benchmark | GLM-4.5V | MiMo-V2.5-Pro |
|---|---|---|
| LMArena Expert | 1353 | 1503 |
Multimodal Not comparable
GLM-4.5V: 34.3 (#92), MiMo-V2.5-Pro: —
| Benchmark | GLM-4.5V | MiMo-V2.5-Pro |
|---|---|---|
| LMArena Vision | 1154 | — |
Multilingual MiMo-V2.5-Pro leads
GLM-4.5V: 44.6 (#177), MiMo-V2.5-Pro: 55.1 (#34)
| Benchmark | GLM-4.5V | MiMo-V2.5-Pro |
|---|---|---|
| LMArena Non-English | 1303 | 1449 |
| LMArena Chinese | 1337 | 1507 |
| LMArena Russian | 1298 | 1450 |
| LMArena Spanish | 1336 | 1471 |
| LMArena French | — | 1488 |
| LMArena German | — | 1458 |
| LMArena Japanese | — | 1412 |
| LMArena Korean | — | 1437 |
Instruction Following MiMo-V2.5-Pro leads
GLM-4.5V: 69.2 (#175), MiMo-V2.5-Pro: 77.5 (#21)
| Benchmark | GLM-4.5V | MiMo-V2.5-Pro |
|---|---|---|
| LMArena Instruction Following | 1311 | 1477 |
Long Context MiMo-V2.5-Pro leads
GLM-4.5V: 39.6 (#171), MiMo-V2.5-Pro: 45.4 (#37)
| Benchmark | GLM-4.5V | MiMo-V2.5-Pro |
|---|---|---|
| LMArena Longer Query | 1304 | 1483 |
Writing & Preference MiMo-V2.5-Pro leads
GLM-4.5V: 52.5 (#170), MiMo-V2.5-Pro: 65.3 (#49)
| Benchmark | GLM-4.5V | MiMo-V2.5-Pro |
|---|---|---|
| LMArena Text | 1333 | 1465 |
| LMArena Creative Writing | 1295 | 1440 |
| LMArena Multi-Turn | 1332 | 1477 |
| EQ-Bench Creative Writing | — | 1493 |
| EQ-Bench 4 | — | 1208 |
Frequently asked questions
Is GLM-4.5V better than MiMo-V2.5-Pro?
MiMo-V2.5-Pro is the stronger model overall, scoring 45.2 to 39.8 on the Noometry Index.
Which is cheaper, GLM-4.5V 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-4.5V lists at $0.60 and $1.80.
Is GLM-4.5V or MiMo-V2.5-Pro better for coding?
MiMo-V2.5-Pro scores higher on coding benchmarks: 47.4 versus 39.5 in the Noometry coding category.
Which has the bigger context window?
MiMo-V2.5-Pro does, with 1.05M tokens against 64K.
How many benchmarks do GLM-4.5V and MiMo-V2.5-Pro share?
13 benchmarks have published results for both models. GLM-4.5V has 15 scored results on Noometry and MiMo-V2.5-Pro has 27.