Model comparison
GLM-5.2 vs MiMo-V2.5-Pro
Head-to-head evidence from 28 shared benchmark results across 6 categories. Overall scores shown here use the public BenchAlign v5 ranking lane.
Public leaderboard positions: GLM-5.2 #37 (Estimated); MiMo-V2.5-Pro #14 (Supported). Intervals and evidence labels describe ranking uncertainty, not a guarantee for a specific workload.
Evidence parity. GLM-5.2 and MiMo-V2.5-Pro share 28 comparable benchmark results. 3 of 8 categories are comparable. 15 results are unique to GLM-5.2; 3 to MiMo-V2.5-Pro.
Updated July 23, 2026- Shared results
- 28
- GLM-5.2 only
- 15
- MiMo-V2.5-Pro only
- 3
- Comparable categories
- 3 / 8
Pick MiMo-V2.5-Pro if you want the stronger benchmark profile. GLM-5.2 only becomes the better choice if agentic is the priority.
Confidence note. This is a partial-evidence comparison with 28 shared benchmark results across 6 evidence categories; 3 of 8 categories currently have scoreable aggregates for both models. Treat the verdict as directional until coverage is more balanced.
Why this result
MiMo-V2.5-Pro is clearly ahead on the BenchAlign aggregate, 70.19 to 63.96. The gap is large enough that you do not need to squint at the spreadsheet to see the difference.
Category breakdown
Exact category averages are shown below. Not measured means BenchLM does not have enough sourced public coverage for that model and category.
| Category | GLM-5.2 | Δ | MiMo-V2.5-Pro |
|---|---|---|---|
| Agentic | GLM-5.281.0 | Margin← 12.6 | MiMo-V2.5-Pro68.4 |
| Knowledge | GLM-5.259.6 | Margin← 11.6 | MiMo-V2.5-Pro48.0 |
| Coding | GLM-5.262.1 | Margin← 4.9 | MiMo-V2.5-Pro57.2 |
| Math | GLM-5.295.9 | MarginNo overlap | MiMo-V2.5-ProNot measured |
Decisive benchmark drivers
The largest measured benchmark gaps in this matchup, with exact reported values.
More
- Source ↗
Terminal-Bench 2.0
AgenticA 81%B 68.4%Winner: GLM-5.2Δ 12.6Terminal-Bench 2.0: GLM-5.2 scored 81%; MiMo-V2.5-Pro scored 68.4%. GLM-5.2 wins this benchmark. - Source ↗
HLE
KnowledgeA 54.7%B 48%Winner: GLM-5.2Δ 6.7HLE: GLM-5.2 scored 54.7%; MiMo-V2.5-Pro scored 48%. GLM-5.2 wins this benchmark. - Source ↗
SWE-bench Pro
CodingA 62.1%B 57.2%Winner: GLM-5.2Δ 4.9SWE-bench Pro: GLM-5.2 scored 62.1%; MiMo-V2.5-Pro scored 57.2%. GLM-5.2 wins this benchmark.
Operational comparison
Runtime and commercial metrics are compared only when both models have a complete sourced value.
| Metric | GLM-5.2 | MiMo-V2.5-Pro | Comparison |
|---|---|---|---|
| Input / output priceUSD per 1M tokens | GLM-5.2$1.4 input / $4.4 output | MiMo-V2.5-ProNot available | A complete price comparison is not available. |
| Generation speedtokens per second | GLM-5.2Not available | MiMo-V2.5-ProNot available | A complete speed comparison is not available. |
| First-answer latencyseconds to first token | GLM-5.2Not available | MiMo-V2.5-ProNot available | A complete latency comparison is not available. |
| Context windowmaximum listed tokens | GLM-5.21M | MiMo-V2.5-Pro1M | Listed context windows are equal. |
Benchmark Deep Dive
AgenticGLM-5.2 wins20 benchmarks
| Benchmark | GLM-5.2 | MiMo-V2.5-Pro | Result |
|---|---|---|---|
| Terminal-Bench 2.0Source | 81% | 68.4% | GLM-5.2 leads |
| MCP AtlasSource | 76.8% | — | Not comparable |
| ToolathlonSource | 48.2% | — | Not comparable |
| AA Agentic IndexSource | 43.1% | 29.1% | GLM-5.2 leads |
| τ²-bench resultsSource | 99.1% | 94.2% | GLM-5.2 leads |
| GDPval-AASource | 50.7% | 38.3% | GLM-5.2 leads |
| GDPval-AASource | 1514 | 1265 | GLM-5.2 leads |
| APEX-Agents-AASource | 33.7% | 2.4% | GLM-5.2 leads |
| ResearchClawBenchSource | 20.7% | — | Not comparable |
| AA BriefcaseSource | 1260 | 873 | GLM-5.2 leads |
| AA AutomationBenchSource | 27.8% | — | Not comparable |
| AA EnterpriseOps-GymSource | 42.7% | — | Not comparable |
| AA Harvey LABSource | 91.0% | 73.3% | GLM-5.2 leads |
| AA ITBenchSource | 42.7% | 38.2% | GLM-5.2 leads |
| AA Tau3 BankingSource | 26.8% | — | Not comparable |
| terminalBenchHardSource | 50.8% | 43.2% | GLM-5.2 leads |
| aaTerminalBench21Source | 77.9% | 65.2% | GLM-5.2 leads |
| Claw-EvalSource | — | 63.8% | Not comparable |
| τ³-bench resultsSource | — | 72.9% | Not comparable |
| Gert LabsSource | — | 62.70% | Not comparable |
CodingGLM-5.2 wins7 benchmarks
| Benchmark | GLM-5.2 | MiMo-V2.5-Pro | Result |
|---|---|---|---|
| SWE-bench ProSource | 62.1% | 57.2% | GLM-5.2 leads |
| NL2RepoSource | 48.9% | — | Not comparable |
| Terminal-Bench 2.0Source | 81.0% | 68.4% | GLM-5.2 leads |
| ProgramBenchSource | 63.7% | — | Not comparable |
| cursorBench32Source | 55.0% | — | Not comparable |
| AA Coding IndexSource | 68.8% | 60.2% | GLM-5.2 leads |
| AA-SciCodeSource | 50.5% | 50.2% | GLM-5.2 leads |
Reasoning2 benchmarks
KnowledgeGLM-5.2 wins11 benchmarks
| Benchmark | GLM-5.2 | MiMo-V2.5-Pro | Result |
|---|---|---|---|
| GPQASource | 91.2% | — | Not comparable |
| GPQA-DSource | 91.2% | — | Not comparable |
| HLESource | 54.7% | 48% | GLM-5.2 leads |
| HLE w/o toolsSource | 40.5% | 34% | GLM-5.2 leads |
| Artificial Analysis Intelligence IndexSource | 51.1% | 42.2% | GLM-5.2 leads |
| AA-GPQA DiamondSource | 89.5% | 86.6% | GLM-5.2 leads |
| AA-HLESource | 40.1% | 33.8% | GLM-5.2 leads |
| AA-Omniscience IndexSource | 4.0% | 3.6% | GLM-5.2 leads |
| AA-Omniscience AccuracySource | 25.1% | 22.6% | GLM-5.2 leads |
| AA-Omniscience Hallucination RateSource | 28.1% | 24.5% | MiMo-V2.5-Pro leads |
| AA Openness IndexSource | 44.4% | 38.9% | GLM-5.2 leads |
Math4 benchmarks
Multimodal1 benchmarks
| Benchmark | GLM-5.2 | MiMo-V2.5-Pro | Result |
|---|---|---|---|
| Design Arena WebsiteSource | 1340 | 1298 | GLM-5.2 leads |
Inst. Following1 benchmarks
| Benchmark | GLM-5.2 | MiMo-V2.5-Pro | Result |
|---|---|---|---|
| AA-IFBenchSource | 73.3% | 79.9% | MiMo-V2.5-Pro leads |
Frequently Asked Questions (4)
Which is better, GLM-5.2 or MiMo-V2.5-Pro?
MiMo-V2.5-Pro is ahead on BenchLM's BenchAlign leaderboard, 70.19 to 63.96. The biggest single separator in this matchup is Terminal-Bench 2.0, where the scores are 81% and 68.4%.
Which is better for knowledge tasks, GLM-5.2 or MiMo-V2.5-Pro?
GLM-5.2 has the edge for knowledge tasks in this comparison, averaging 59.6 versus 48. Inside this category, Artificial Analysis Intelligence Index is the benchmark that creates the most daylight between them.
Which is better for coding, GLM-5.2 or MiMo-V2.5-Pro?
GLM-5.2 has the edge for coding in this comparison, averaging 62.1 versus 57.2. Inside this category, Terminal-Bench 2.0 is the benchmark that creates the most daylight between them.
Which is better for agentic tasks, GLM-5.2 or MiMo-V2.5-Pro?
GLM-5.2 has the edge for agentic tasks in this comparison, averaging 81 versus 68.4. Inside this category, AA Briefcase is the benchmark that creates the most daylight between them.
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