Model comparison
GLM-5.2 vs MiMo-V2-Omni
Head-to-head evidence from 11 shared benchmark results across 5 categories. Overall scores shown here use the public BenchAlign v5 ranking lane.
Public leaderboard positions: GLM-5.2 #37 (Estimated); MiMo-V2-Omni #40 (Supported). Intervals and evidence labels describe ranking uncertainty, not a guarantee for a specific workload.
Evidence parity. GLM-5.2 and MiMo-V2-Omni share 11 comparable benchmark results. 1 of 8 categories are comparable. 32 results are unique to GLM-5.2; 3 to MiMo-V2-Omni.
Updated July 23, 2026- Shared results
- 11
- GLM-5.2 only
- 32
- MiMo-V2-Omni only
- 3
- Comparable categories
- 1 / 8
Pick GLM-5.2 if you want the stronger benchmark profile. MiMo-V2-Omni only becomes the better choice if coding is the priority.
Confidence note. This is a partial-evidence comparison with 11 shared benchmark results across 5 evidence categories; 1 of 8 categories currently have scoreable aggregates for both models. Treat the verdict as directional until coverage is more balanced.
Why this result
GLM-5.2 has the cleaner BenchAlign overall profile here, landing at 63.96 versus 63.15. It is a real lead, but still close enough that category-level strengths matter more than the headline number.
GLM-5.2 gives you the larger context window at 1M, compared with 262K for MiMo-V2-Omni.
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-Omni |
|---|---|---|---|
| Coding | GLM-5.262.1 | Margin→ 12.7 | MiMo-V2-Omni74.8 |
| Agentic | GLM-5.281.0 | MarginNo overlap | MiMo-V2-OmniNot measured |
| Knowledge | GLM-5.259.6 | MarginNo overlap | MiMo-V2-OmniNot measured |
| Math | GLM-5.295.9 | MarginNo overlap | MiMo-V2-OmniNot measured |
Operational comparison
Runtime and commercial metrics are compared only when both models have a complete sourced value.
| Metric | GLM-5.2 | MiMo-V2-Omni | Comparison |
|---|---|---|---|
| Input / output priceUSD per 1M tokens | GLM-5.2$1.4 input / $4.4 output | MiMo-V2-OmniNot available | A complete price comparison is not available. |
| Generation speedtokens per second | GLM-5.2Not available | MiMo-V2-OmniNot available | A complete speed comparison is not available. |
| First-answer latencyseconds to first token | GLM-5.2Not available | MiMo-V2-OmniNot available | A complete latency comparison is not available. |
| Context windowmaximum listed tokens | GLM-5.21M | MiMo-V2-Omni262K | GLM-5.2 lists the larger context window. |
Benchmark Deep Dive
Agentic18 benchmarks
| Benchmark | GLM-5.2 | MiMo-V2-Omni | Result |
|---|---|---|---|
| Terminal-Bench 2.0Source | 81% | — | Not comparable |
| MCP AtlasSource | 76.8% | — | Not comparable |
| ToolathlonSource | 48.2% | — | Not comparable |
| AA Agentic IndexSource | 43.1% | — | Not comparable |
| τ²-bench resultsSource | 99.1% | 91.2% | GLM-5.2 leads |
| GDPval-AASource | 50.7% | — | Not comparable |
| GDPval-AASource | 1514 | — | Not comparable |
| APEX-Agents-AASource | 33.7% | — | Not comparable |
| ResearchClawBenchSource | 20.7% | — | Not comparable |
| AA BriefcaseSource | 1260 | — | Not comparable |
| AA AutomationBenchSource | 27.8% | — | Not comparable |
| AA EnterpriseOps-GymSource | 42.7% | — | Not comparable |
| AA Harvey LABSource | 91.0% | — | Not comparable |
| AA ITBenchSource | 42.7% | — | Not comparable |
| AA Tau3 BankingSource | 26.8% | — | Not comparable |
| terminalBenchHardSource | 50.8% | — | Not comparable |
| aaTerminalBench21Source | 77.9% | — | Not comparable |
| Claw-EvalSource | — | 45.2% | Not comparable |
CodingMiMo-V2-Omni wins8 benchmarks
| Benchmark | GLM-5.2 | MiMo-V2-Omni | Result |
|---|---|---|---|
| SWE-bench ProSource | 62.1% | — | Not comparable |
| NL2RepoSource | 48.9% | — | Not comparable |
| Terminal-Bench 2.0Source | 81.0% | — | Not comparable |
| ProgramBenchSource | 63.7% | — | Not comparable |
| cursorBench32Source | 55.0% | — | Not comparable |
| AA Coding IndexSource | 68.8% | — | Not comparable |
| AA-SciCodeSource | 50.5% | 36.7% | GLM-5.2 leads |
| SWE-bench VerifiedSource | — | 74.8% | Not comparable |
Reasoning2 benchmarks
Knowledge11 benchmarks
| Benchmark | GLM-5.2 | MiMo-V2-Omni | Result |
|---|---|---|---|
| GPQASource | 91.2% | — | Not comparable |
| GPQA-DSource | 91.2% | — | Not comparable |
| HLESource | 54.7% | — | Not comparable |
| HLE w/o toolsSource | 40.5% | — | Not comparable |
| Artificial Analysis Intelligence IndexSource | 51.1% | 35.0% | GLM-5.2 leads |
| AA-GPQA DiamondSource | 89.5% | 82.8% | GLM-5.2 leads |
| AA-HLESource | 40.1% | 19.9% | GLM-5.2 leads |
| AA-Omniscience IndexSource | 4.0% | -17.4% | GLM-5.2 leads |
| AA-Omniscience AccuracySource | 25.1% | 18.7% | GLM-5.2 leads |
| AA-Omniscience Hallucination RateSource | 28.1% | 44.4% | GLM-5.2 leads |
| AA Openness IndexSource | 44.4% | — | Not comparable |
Math4 benchmarks
Multimodal2 benchmarks
Inst. Following1 benchmarks
| Benchmark | GLM-5.2 | MiMo-V2-Omni | Result |
|---|---|---|---|
| AA-IFBenchSource | 73.3% | 53.5% | GLM-5.2 leads |
Frequently Asked Questions (2)
Which is better, GLM-5.2 or MiMo-V2-Omni?
GLM-5.2 is ahead on BenchLM's BenchAlign leaderboard, 63.96 to 63.15.
Which is better for coding, GLM-5.2 or MiMo-V2-Omni?
MiMo-V2-Omni has the edge for coding in this comparison, averaging 74.8 versus 62.1. Inside this category, AA-SciCode is the benchmark that creates the most daylight between them.
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