Model comparison
GLM-5.2 vs MiMo-V2.6-Pro
GLM-5.2 and MiMo-V2.6-Pro score almost the same on the Noometry Index (51.1 vs 50.3), so choose on price, context window or the category you care about most.
Last verified . 18 shared benchmarks.
Summary
- They share 18 benchmarks with published results for both. GLM-5.2 scores higher in 3 categories and MiMo-V2.6-Pro in 6 categories; 7 gaps are clear of the uncertainty.
- The widest gap is in knowledge, where GLM-5.2 leads 57.1 to 43.5.
- The biggest single-benchmark swing is ProofBench: 35% for GLM-5.2 and 70% for MiMo-V2.6-Pro.
- MiMo-V2.6-Pro is cheaper at $0.43 / $0.87 per million input/output tokens, against $1.40 / $4.40 for GLM-5.2.
- MiMo-V2.6-Pro accepts more context: 1.05M tokens versus 1M.
Side by side
| GLM-5.2 | MiMo-V2.6-Pro | |
|---|---|---|
| Provider | Z.ai (Zhipu) | Xiaomi |
| Noometry Index | 51.1 | 50.3 |
| Released | 2026-06-13 | 2026-09-21 |
| Weights | Open | Open |
| Context window | 1M | 1.05M |
| Max output | 131K | 131K |
| Input $ / M tokens | $1.40 | $0.43 |
| Output $ / M tokens | $4.40 | $0.87 |
| Results tracked | 51 | 19 |
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Category by category
Coding MiMo-V2.6-Pro leads
GLM-5.2: 51.3 (#41), MiMo-V2.6-Pro: 55.5 (#23)
| Benchmark | GLM-5.2 | MiMo-V2.6-Pro |
|---|---|---|
| LMArena WebDev | 1603 | 1629 |
| SciCode | 50.5% | 60.9% |
| LMArena Coding | 1485 | 1534 |
| ALE-Bench | 1,047 | 1,158 |
| SWE-bench Verified | 78.7% | — |
| DeepSWE | 43.8% | — |
| FrontierCode | 24.5% | — |
| WeirdML | 70.1% | — |
Agentic & Tool Use MiMo-V2.6-Pro leads
GLM-5.2: 32.4 (#63), MiMo-V2.6-Pro: 37.5 (#35)
| Benchmark | GLM-5.2 | MiMo-V2.6-Pro |
|---|---|---|
| APEX-Agents | 45.2% | 59.5% |
| τ²-bench Banking | 37.1% | — |
| PostTrainBench | 31.7% | — |
| GBAEval | 0% | — |
| Vending-Bench 2 | 8,314 | — |
Reasoning Too close to call
GLM-5.2: 42.3 (#52), MiMo-V2.6-Pro: 43.1 (#50)
| Benchmark | GLM-5.2 | MiMo-V2.6-Pro |
|---|---|---|
| CritPt | 20.9% | 26.6% |
| LMArena Hard Prompts | 1480 | 1512 |
| ARC-AGI-2 | 22.8% | — |
| SimpleBench | 58.8% | — |
| Kagi LLM Benchmark | 62.6% | — |
| NYT Connections (extended) | 74.3% | — |
| ARC-AGI-1 | 77% | — |
| Chess Puzzles | 21% | — |
| EBR-Bench | 9.5% | — |
| Mystery Game Puzzles | 19% | — |
| DTBench | 93.6% | — |
| LMCA | 45.8% | — |
| Surface Evolver Bench | 55.6% | — |
| Epoch Capabilities Index | 151.78 | — |
Math GLM-5.2 leads
GLM-5.2: 55.7 (#43), MiMo-V2.6-Pro: 54.5 (#45)
| Benchmark | GLM-5.2 | MiMo-V2.6-Pro |
|---|---|---|
| ProofBench | 35% | 70% |
| LMArena Math | 1482 | 1494 |
| FrontierMath (Tiers 1-3) | 59.2% | — |
| FrontierMath Tier 4 | 29.3% | — |
| MathArena Final-Answer Competitions | 67.6% | — |
| OTIS Mock AIME 2024-2025 | 86.4% | — |
Knowledge GLM-5.2 leads
GLM-5.2: 57.1 (#40), MiMo-V2.6-Pro: 43.5 (#92)
| Benchmark | GLM-5.2 | MiMo-V2.6-Pro |
|---|---|---|
| LMArena Expert | 1486 | 1543 |
| GPQA Diamond | 91.9% | — |
| SimpleQA Verified | 34.2% | — |
Multimodal Not comparable
GLM-5.2: —, MiMo-V2.6-Pro: 40.8 (#43)
| Benchmark | GLM-5.2 | MiMo-V2.6-Pro |
|---|---|---|
| LMArena Vision | — | 1264 |
Multilingual MiMo-V2.6-Pro leads
GLM-5.2: 55.8 (#26), MiMo-V2.6-Pro: 56.9 (#14)
| Benchmark | GLM-5.2 | MiMo-V2.6-Pro |
|---|---|---|
| LMArena Non-English | 1459 | 1474 |
| LMArena Chinese | 1519 | 1529 |
| LMArena Russian | 1466 | 1480 |
| LMArena French | 1479 | — |
| LMArena German | 1468 | — |
| LMArena Japanese | 1451 | — |
| LMArena Korean | 1445 | — |
| LMArena Spanish | 1477 | — |
Instruction Following MiMo-V2.6-Pro leads
GLM-5.2: 76.9 (#34), MiMo-V2.6-Pro: 78.2 (#12)
| Benchmark | GLM-5.2 | MiMo-V2.6-Pro |
|---|---|---|
| LMArena Instruction Following | 1465 | 1493 |
Long Context Too close to call
GLM-5.2: 45.3 (#43), MiMo-V2.6-Pro: 46.0 (#27)
| Benchmark | GLM-5.2 | MiMo-V2.6-Pro |
|---|---|---|
| LMArena Longer Query | 1479 | 1501 |
Writing & Preference GLM-5.2 leads
GLM-5.2: 70.4 (#21), MiMo-V2.6-Pro: 66.8 (#33)
| Benchmark | GLM-5.2 | MiMo-V2.6-Pro |
|---|---|---|
| LMArena Text | 1470 | 1492 |
| LMArena Creative Writing | 1462 | 1468 |
| LMArena Multi-Turn | 1469 | 1464 |
| EQ-Bench Creative Writing | 1757 | — |
| EQ-Bench 4 | 1222 | — |
Frequently asked questions
Is GLM-5.2 better than MiMo-V2.6-Pro?
GLM-5.2 and MiMo-V2.6-Pro score almost the same on the Noometry Index (51.1 vs 50.3), so choose on price, context window or the category you care about most.
Which is cheaper, GLM-5.2 or MiMo-V2.6-Pro?
MiMo-V2.6-Pro is cheaper. It lists at $0.43 per million input tokens and $0.87 per million output tokens; GLM-5.2 lists at $1.40 and $4.40.
Is GLM-5.2 or MiMo-V2.6-Pro better for coding?
MiMo-V2.6-Pro scores higher on coding benchmarks: 55.5 versus 51.3 in the Noometry coding category.
Which has the bigger context window?
MiMo-V2.6-Pro does, with 1.05M tokens against 1M.
How many benchmarks do GLM-5.2 and MiMo-V2.6-Pro share?
18 benchmarks have published results for both models. GLM-5.2 has 51 scored results on Noometry and MiMo-V2.6-Pro has 19.