Model comparison
GLM-4.6 vs MAI-Thinking-1
Head-to-head evidence from 0 shared benchmark results across 0 categories. Overall scores shown here use the public BenchAlign v5 ranking lane.
Public leaderboard positions: GLM-4.6 #85 (Supported); MAI-Thinking-1 unranked (Not scored). Intervals and evidence labels describe ranking uncertainty, not a guarantee for a specific workload.
Evidence parity. GLM-4.6 and MAI-Thinking-1 share 0 comparable benchmark results. 1 of 8 categories are comparable. 14 results are unique to GLM-4.6; 13 to MAI-Thinking-1.
Updated July 23, 2026- Shared results
- 0
- GLM-4.6 only
- 14
- MAI-Thinking-1 only
- 13
- Comparable categories
- 1 / 8
Treat this as a split decision. GLM-4.6 makes more sense if its workflow fits your team better; 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 0 shared benchmark results across 0 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-4.6 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 200K for GLM-4.6.
Operational comparison
Runtime and commercial metrics are compared only when both models have a complete sourced value.
| Metric | GLM-4.6 | MAI-Thinking-1 | Comparison |
|---|---|---|---|
| Input / output priceUSD per 1M tokens | GLM-4.6Not available | MAI-Thinking-1Not available | A complete price comparison is not available. |
| Generation speedtokens per second | GLM-4.6Not available | MAI-Thinking-1Not available | A complete speed comparison is not available. |
| First-answer latencyseconds to first token | GLM-4.6Not available | MAI-Thinking-1Not available | A complete latency comparison is not available. |
| Context windowmaximum listed tokens | GLM-4.6200K | MAI-Thinking-1256K | MAI-Thinking-1 lists the larger context window. |
Benchmark Deep Dive
Agentic2 benchmarks
Coding5 benchmarks
Reasoning3 benchmarks
Knowledge10 benchmarks
| Benchmark | GLM-4.6 | MAI-Thinking-1 | Result |
|---|---|---|---|
| Artificial Analysis Intelligence IndexSource | 23.0% | — | Not comparable |
| AA-GPQA DiamondSource | 63.2% | — | Not comparable |
| AA-HLESource | 5.2% | — | Not comparable |
| AA-Omniscience IndexSource | -31.6% | — | Not comparable |
| AA-Omniscience AccuracySource | 20.8% | — | Not comparable |
| AA-Omniscience Hallucination RateSource | 66.1% | — | Not comparable |
| GPQASource | — | 84.2% | Not comparable |
| GPQA-DSource | — | 84.2% | Not comparable |
| MMLU-ProSource | — | 85% | Not comparable |
| SimpleQASource | — | 31% | Not comparable |
MathMAI-Thinking-1 wins5 benchmarks
Frequently Asked Questions (2)
Which is better, GLM-4.6 or MAI-Thinking-1?
GLM-4.6 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 math, GLM-4.6 or MAI-Thinking-1?
MAI-Thinking-1 has the edge for math in this comparison, averaging 89.7 versus 3.4. GLM-4.6 stays close enough that the answer can still flip depending on your workload.
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