Model comparison
GLM-5.1 vs MiMo-V2.5
Head-to-head evidence from 6 shared benchmark results across 3 categories. Overall scores shown here use the public BenchAlign v5 ranking lane.
Public leaderboard positions: GLM-5.1 #18 (Supported); MiMo-V2.5 #62 (Estimated). Intervals and evidence labels describe ranking uncertainty, not a guarantee for a specific workload.
Evidence parity. GLM-5.1 and MiMo-V2.5 share 6 comparable benchmark results. 2 of 8 categories are comparable. 30 results are unique to GLM-5.1; 5 to MiMo-V2.5.
Updated July 21, 2026- Shared results
- 6
- GLM-5.1 only
- 30
- MiMo-V2.5 only
- 5
- Comparable categories
- 2 / 8
Pick GLM-5.1 if you want the stronger benchmark profile. MiMo-V2.5 only becomes the better choice if agentic is the priority or you need the larger 1M context window.
Confidence note. This is a partial-evidence comparison with 6 shared benchmark results across 3 evidence categories; 2 of 8 categories currently have scoreable aggregates for both models. Treat the verdict as directional until coverage is more balanced.
Why this result
GLM-5.1 is clearly ahead on the BenchAlign aggregate, 67.74 to 58.62. The gap is large enough that you do not need to squint at the spreadsheet to see the difference.
GLM-5.1's sharpest advantage is in coding, where it averages 61.3 against 56.1. The single biggest benchmark swing on the page is Terminal-Bench 2.0, 63.5% to 65.8%. MiMo-V2.5 does hit back in agentic, so the answer changes if that is the part of the workload you care about most.
MiMo-V2.5 gives you the larger context window at 1M, compared with 203K for GLM-5.1.
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-5.1 | Δ | MiMo-V2.5 |
|---|---|---|---|
| Coding | GLM-5.161.3 | Margin← 5.2 | MiMo-V2.556.1 |
| Agentic | GLM-5.165.4 | Margin→ 0.4 | MiMo-V2.565.8 |
| Knowledge | GLM-5.152.3 | MarginNo overlap | MiMo-V2.5Not measured |
| Math | GLM-5.162.0 | MarginNo overlap | MiMo-V2.5Not measured |
| Multimodal | GLM-5.1Not measured | MarginNo overlap | MiMo-V2.579.0 |
Decisive benchmark drivers
The largest measured benchmark gaps in this matchup, with exact reported values.
More
- Source ↗
Terminal-Bench 2.0
AgenticA 63.5%B 65.8%Winner: MiMo-V2.5Δ 2.3Terminal-Bench 2.0: GLM-5.1 scored 63.5%; MiMo-V2.5 scored 65.8%. MiMo-V2.5 wins this benchmark. - Source ↗
SWE-bench Pro
CodingA 58.4%B 56.1%Winner: GLM-5.1Δ 2.3SWE-bench Pro: GLM-5.1 scored 58.4%; MiMo-V2.5 scored 56.1%. GLM-5.1 wins this benchmark.
Operational comparison
Runtime and commercial metrics are compared only when both models have a complete sourced value.
| Metric | GLM-5.1 | MiMo-V2.5 | Comparison |
|---|---|---|---|
| Input / output priceUSD per 1M tokens | GLM-5.1$1.4 input / $4.4 output | MiMo-V2.5Not available | A complete price comparison is not available. |
| Generation speedtokens per second | GLM-5.1Not available | MiMo-V2.5Not available | A complete speed comparison is not available. |
| First-answer latencyseconds to first token | GLM-5.1Not available | MiMo-V2.5Not available | A complete latency comparison is not available. |
| Context windowmaximum listed tokens | GLM-5.1203K | MiMo-V2.51M | MiMo-V2.5 lists the larger context window. |
Benchmark Deep Dive
AgenticMiMo-V2.5 wins13 benchmarks
| Benchmark | GLM-5.1 | MiMo-V2.5 | Result |
|---|---|---|---|
| Terminal-Bench 2.0Source | 63.5% | 65.8% | MiMo-V2.5 leads |
| BrowseCompSource | 68% | — | Not comparable |
| τ³-bench resultsSource | 70.6% | — | Not comparable |
| MCP AtlasSource | 71.8% | — | Not comparable |
| CyberGymSource | 68.7% | — | Not comparable |
| Claw-EvalSource | 62.3% | 62.3% | Tie |
| AA Agentic IndexSource | 29.9% | — | Not comparable |
| τ²-bench resultsSource | 97.7% | — | Not comparable |
| GDPval-AASource | 37.8% | — | Not comparable |
| Gert LabsSource | 60.11% | 46.89% | GLM-5.1 leads |
| GDPval-AASource | 1257 | — | Not comparable |
| ResearchClawBenchSource | 18.2% | 16.9% | GLM-5.1 leads |
| MM-ClawBenchSource | — | 23.8% | Not comparable |
CodingGLM-5.1 wins7 benchmarks
| Benchmark | GLM-5.1 | MiMo-V2.5 | Result |
|---|---|---|---|
| SWE-bench ProSource | 58.4% | 56.1% | GLM-5.1 leads |
| NL2RepoSource | 42.7% | — | Not comparable |
| SWE-RebenchSource | 62.7% | — | Not comparable |
| Vibe Code BenchSource | 31.46% | — | Not comparable |
| AA Coding IndexSource | 55.8% | — | Not comparable |
| AA-SciCodeSource | 43.8% | — | Not comparable |
| Terminal-Bench 2.0Source | — | 65.8% | Not comparable |
Reasoning2 benchmarks
Knowledge8 benchmarks
| Benchmark | GLM-5.1 | MiMo-V2.5 | Result |
|---|---|---|---|
| GPQA-DSource | 86.2% | — | Not comparable |
| HLESource | 52.3% | — | Not comparable |
| Artificial Analysis Intelligence IndexSource | 40.2% | — | Not comparable |
| AA-GPQA DiamondSource | 86.8% | — | Not comparable |
| AA-HLESource | 28.0% | — | Not comparable |
| AA-Omniscience IndexSource | 1.9% | — | Not comparable |
| AA-Omniscience AccuracySource | 24.2% | — | Not comparable |
| AA-Omniscience Hallucination RateSource | 29.4% | — | Not comparable |
Math6 benchmarks
Multimodal4 benchmarks
Inst. Following1 benchmarks
| Benchmark | GLM-5.1 | MiMo-V2.5 | Result |
|---|---|---|---|
| AA-IFBenchSource | 76.3% | — | Not comparable |
Frequently Asked Questions (3)
Which is better, GLM-5.1 or MiMo-V2.5?
GLM-5.1 is ahead on BenchLM's BenchAlign leaderboard, 67.74 to 58.62. The biggest single separator in this matchup is Terminal-Bench 2.0, where the scores are 63.5% and 65.8%.
Which is better for coding, GLM-5.1 or MiMo-V2.5?
GLM-5.1 has the edge for coding in this comparison, averaging 61.3 versus 56.1. Inside this category, SWE-bench Pro is the benchmark that creates the most daylight between them.
Which is better for agentic tasks, GLM-5.1 or MiMo-V2.5?
MiMo-V2.5 has the edge for agentic tasks in this comparison, averaging 65.8 versus 65.4. Inside this category, Gert Labs is the benchmark that creates the most daylight between them.
Self-host vs API cost
Estimates at 50,000 req/day · 1000 tokens/req average.
Related Comparisons
Explore More
Choose a model with this week’s evidence
Join 2,000+ readers for ranking moves, pricing changes, and the claims that still need proof.
One email each week. Unsubscribe anytime.