Model comparison
GLM-5.1 vs MAI-Thinking-1
Head-to-head evidence from 5 shared benchmark results across 4 categories. Overall scores shown here use the public BenchAlign v5 ranking lane.
Public leaderboard positions: GLM-5.1 #18 (Supported); MAI-Thinking-1 unranked (Not scored). Intervals and evidence labels describe ranking uncertainty, not a guarantee for a specific workload.
Evidence parity. GLM-5.1 and MAI-Thinking-1 share 5 comparable benchmark results. 4 of 8 categories are comparable. 31 results are unique to GLM-5.1; 8 to MAI-Thinking-1.
Updated July 23, 2026- Shared results
- 5
- GLM-5.1 only
- 31
- MAI-Thinking-1 only
- 8
- Comparable categories
- 4 / 8
Treat this as a split decision. GLM-5.1 makes more sense if agentic is the priority; MAI-Thinking-1 is the better fit if mathematics is the priority or you need the larger 256K context window.
Confidence note. This is a partial-evidence comparison with 5 shared benchmark results across 4 evidence categories; 4 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 and MAI-Thinking-1 finish on the same BenchAlign overall score, so this is less about a single winner and more about where the edge shows up. The BenchAlign headline says tie; the benchmark table is where the real choice happens.
MAI-Thinking-1 gives you the larger context window at 256K, 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 | MAI-Thinking-1 |
|---|---|---|---|
| Math | GLM-5.162.0 | Margin→ 27.7 | MAI-Thinking-189.7 |
| Knowledge | GLM-5.152.3 | Margin→ 20.2 | MAI-Thinking-172.5 |
| Agentic | GLM-5.165.4 | Margin← 19.4 | MAI-Thinking-146.0 |
| Coding | GLM-5.161.3 | Margin→ 4.2 | MAI-Thinking-165.5 |
| Inst. Following | GLM-5.1Not measured | MarginNo overlap | MAI-Thinking-185.0 |
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 46%Winner: GLM-5.1Δ 17.5Terminal-Bench 2.0: GLM-5.1 scored 63.5%; MAI-Thinking-1 scored 46%. GLM-5.1 wins this benchmark. - Source ↗
SWE-bench Pro
CodingA 58.4%B 52.8%Winner: GLM-5.1Δ 5.6SWE-bench Pro: GLM-5.1 scored 58.4%; MAI-Thinking-1 scored 52.8%. GLM-5.1 wins this benchmark. - Source ↗
HMMT Feb 2026
MathA 82.6%B 84.9%Winner: MAI-Thinking-1Δ 2.3HMMT Feb 2026: GLM-5.1 scored 82.6%; MAI-Thinking-1 scored 84.9%. MAI-Thinking-1 wins this benchmark. - Source ↗
AIME26
MathA 95.3%B 94.5%Winner: GLM-5.1Δ 0.8AIME26: GLM-5.1 scored 95.3%; MAI-Thinking-1 scored 94.5%. 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 | MAI-Thinking-1 | Comparison |
|---|---|---|---|
| Input / output priceUSD per 1M tokens | GLM-5.1$1.4 input / $4.4 output | MAI-Thinking-1Not available | A complete price comparison is not available. |
| Generation speedtokens per second | GLM-5.1Not available | MAI-Thinking-1Not available | A complete speed comparison is not available. |
| First-answer latencyseconds to first token | GLM-5.1Not available | MAI-Thinking-1Not available | A complete latency comparison is not available. |
| Context windowmaximum listed tokens | GLM-5.1203K | MAI-Thinking-1256K | MAI-Thinking-1 lists the larger context window. |
Benchmark Deep Dive
AgenticGLM-5.1 wins12 benchmarks
| Benchmark | GLM-5.1 | MAI-Thinking-1 | Result |
|---|---|---|---|
| Terminal-Bench 2.0Source | 63.5% | 46% | GLM-5.1 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% | — | Not comparable |
| AA Agentic IndexSource | 29.9% | — | Not comparable |
| τ²-bench resultsSource | 97.7% | — | Not comparable |
| GDPval-AASource | 37.8% | — | Not comparable |
| Gert LabsSource | 60.11% | — | Not comparable |
| GDPval-AASource | 1257 | — | Not comparable |
| ResearchClawBenchSource | 18.2% | — | Not comparable |
CodingMAI-Thinking-1 wins8 benchmarks
| Benchmark | GLM-5.1 | MAI-Thinking-1 | Result |
|---|---|---|---|
| SWE-bench ProSource | 58.4% | 52.8% | 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 |
| SWE-bench VerifiedSource | — | 73.5% | Not comparable |
| Terminal-Bench 2.0Source | — | 46.0% | Not comparable |
Reasoning3 benchmarks
KnowledgeMAI-Thinking-1 wins11 benchmarks
| Benchmark | GLM-5.1 | MAI-Thinking-1 | Result |
|---|---|---|---|
| GPQA-DSource | 86.2% | 84.2% | GLM-5.1 leads |
| 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 |
| GPQASource | — | 84.2% | Not comparable |
| MMLU-ProSource | — | 85% | Not comparable |
| SimpleQASource | — | 31% | Not comparable |
MathMAI-Thinking-1 wins7 benchmarks
| Benchmark | GLM-5.1 | MAI-Thinking-1 | Result |
|---|---|---|---|
| AIME26Source | 95.3% | 94.5% | GLM-5.1 leads |
| HMMT Nov 2025Source | 94.0% | — | Not comparable |
| HMMT Feb 2026Source | 82.6% | 84.9% | MAI-Thinking-1 leads |
| MMAnswerBenchSource | 83.8% | — | Not comparable |
| FrontierMath v2 (Tiers 1-3)Source | 33.448% | — | Not comparable |
| FrontierMath v2 (Tier 4)Source | 12.500% | — | Not comparable |
| AIME 2025Source | — | 97% | Not comparable |
Multimodal1 benchmarks
| Benchmark | GLM-5.1 | MAI-Thinking-1 | Result |
|---|---|---|---|
| Design Arena WebsiteSource | 1305 | — | Not comparable |
Frequently Asked Questions (5)
Which is better, GLM-5.1 or MAI-Thinking-1?
GLM-5.1 and MAI-Thinking-1 are tied on the BenchAlign overall score, so the right pick depends on which category matters most for your use case.
Which is better for knowledge tasks, GLM-5.1 or MAI-Thinking-1?
MAI-Thinking-1 has the edge for knowledge tasks in this comparison, averaging 72.5 versus 52.3. Inside this category, GPQA-D is the benchmark that creates the most daylight between them.
Which is better for coding, GLM-5.1 or MAI-Thinking-1?
MAI-Thinking-1 has the edge for coding in this comparison, averaging 65.5 versus 61.3. Inside this category, SWE-bench Pro is the benchmark that creates the most daylight between them.
Which is better for math, GLM-5.1 or MAI-Thinking-1?
MAI-Thinking-1 has the edge for math in this comparison, averaging 89.7 versus 62. Inside this category, HMMT Feb 2026 is the benchmark that creates the most daylight between them.
Which is better for agentic tasks, GLM-5.1 or MAI-Thinking-1?
GLM-5.1 has the edge for agentic tasks in this comparison, averaging 65.4 versus 46. Inside this category, Terminal-Bench 2.0 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.
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