Model comparison
DeepSeek V4 Pro vs MAI-Thinking-1
Head-to-head evidence from 9 shared benchmark results across 4 categories. Overall scores shown here use the public BenchAlign v5 ranking lane.
Public leaderboard positions: DeepSeek V4 Pro #46 (Supported); MAI-Thinking-1 unranked (Not scored). Intervals and evidence labels describe ranking uncertainty, not a guarantee for a specific workload.
Evidence parity. DeepSeek V4 Pro and MAI-Thinking-1 share 9 comparable benchmark results. 4 of 8 categories are comparable. 14 results are unique to DeepSeek V4 Pro; 4 to MAI-Thinking-1.
Updated July 23, 2026- Shared results
- 9
- DeepSeek V4 Pro only
- 14
- MAI-Thinking-1 only
- 4
- Comparable categories
- 4 / 8
Treat this as a split decision. DeepSeek V4 Pro makes more sense if agentic is the priority or you need the larger 1M context window; MAI-Thinking-1 is the better fit if mathematics is the priority or you want the stronger reasoning-first profile.
Confidence note. This is a partial-evidence comparison with 9 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
DeepSeek V4 Pro 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 is the reasoning model in the pair, while DeepSeek V4 Pro is not. That usually helps on harder chain-of-thought-heavy tests, but it can also mean more latency and more token spend in real use. DeepSeek V4 Pro gives you the larger context window at 1M, compared with 256K for MAI-Thinking-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 | DeepSeek V4 Pro | Δ | MAI-Thinking-1 |
|---|---|---|---|
| Math | DeepSeek V4 Pro31.7 | Margin→ 58.0 | MAI-Thinking-189.7 |
| Knowledge | DeepSeek V4 Pro41.3 | Margin→ 31.2 | MAI-Thinking-172.5 |
| Agentic | DeepSeek V4 Pro59.1 | Margin← 13.1 | MAI-Thinking-146.0 |
| Coding | DeepSeek V4 Pro65.3 | Margin→ 0.2 | MAI-Thinking-165.5 |
| Inst. Following | DeepSeek V4 ProNot measured | MarginNo overlap | MAI-Thinking-185.0 |
Decisive benchmark drivers
The largest measured benchmark gaps in this matchup, with exact reported values.
More
- Source ↗
HMMT Feb 2026
MathA 31.7%B 84.9%Winner: MAI-Thinking-1Δ 53.2HMMT Feb 2026: DeepSeek V4 Pro scored 31.7%; MAI-Thinking-1 scored 84.9%. MAI-Thinking-1 wins this benchmark. - Source ↗
SimpleQA
KnowledgeA 45%B 31%Winner: DeepSeek V4 ProΔ 14SimpleQA: DeepSeek V4 Pro scored 45%; MAI-Thinking-1 scored 31%. DeepSeek V4 Pro wins this benchmark. - Source ↗
Terminal-Bench 2.0
AgenticA 59.1%B 46%Winner: DeepSeek V4 ProΔ 13.1Terminal-Bench 2.0: DeepSeek V4 Pro scored 59.1%; MAI-Thinking-1 scored 46%. DeepSeek V4 Pro wins this benchmark. - Source ↗
GPQA
KnowledgeA 72.9%B 84.2%Winner: MAI-Thinking-1Δ 11.3GPQA: DeepSeek V4 Pro scored 72.9%; MAI-Thinking-1 scored 84.2%. MAI-Thinking-1 wins this benchmark. - Source ↗
MMLU-Pro
KnowledgeA 82.9%B 85%Winner: MAI-Thinking-1Δ 2.1MMLU-Pro: DeepSeek V4 Pro scored 82.9%; MAI-Thinking-1 scored 85%. MAI-Thinking-1 wins this benchmark.
Operational comparison
Runtime and commercial metrics are compared only when both models have a complete sourced value.
| Metric | DeepSeek V4 Pro | MAI-Thinking-1 | Comparison |
|---|---|---|---|
| Input / output priceUSD per 1M tokens | DeepSeek V4 Pro$0.435 input / $0.87 output | MAI-Thinking-1Not available | A complete price comparison is not available. |
| Generation speedtokens per second | DeepSeek V4 ProNot available | MAI-Thinking-1Not available | A complete speed comparison is not available. |
| First-answer latencyseconds to first token | DeepSeek V4 ProNot available | MAI-Thinking-1Not available | A complete latency comparison is not available. |
| Context windowmaximum listed tokens | DeepSeek V4 Pro1M | MAI-Thinking-1256K | DeepSeek V4 Pro lists the larger context window. |
Benchmark Deep Dive
AgenticDeepSeek V4 Pro wins6 benchmarks
CodingMAI-Thinking-1 wins4 benchmarks
Reasoning3 benchmarks
KnowledgeMAI-Thinking-1 wins6 benchmarks
MathMAI-Thinking-1 wins6 benchmarks
Multimodal1 benchmarks
| Benchmark | DeepSeek V4 Pro | MAI-Thinking-1 | Result |
|---|---|---|---|
| Design Arena WebsiteSource | 1264 | — | Not comparable |
Inst. Following1 benchmarks
| Benchmark | DeepSeek V4 Pro | MAI-Thinking-1 | Result |
|---|---|---|---|
| IFBenchSource | — | 85% | Not comparable |
Frequently Asked Questions (5)
Which is better, DeepSeek V4 Pro or MAI-Thinking-1?
DeepSeek V4 Pro 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, DeepSeek V4 Pro or MAI-Thinking-1?
MAI-Thinking-1 has the edge for knowledge tasks in this comparison, averaging 72.5 versus 41.3. Inside this category, SimpleQA is the benchmark that creates the most daylight between them.
Which is better for coding, DeepSeek V4 Pro or MAI-Thinking-1?
MAI-Thinking-1 has the edge for coding in this comparison, averaging 65.5 versus 65.3. Inside this category, Terminal-Bench 2.0 is the benchmark that creates the most daylight between them.
Which is better for math, DeepSeek V4 Pro or MAI-Thinking-1?
MAI-Thinking-1 has the edge for math in this comparison, averaging 89.7 versus 31.7. Inside this category, HMMT Feb 2026 is the benchmark that creates the most daylight between them.
Which is better for agentic tasks, DeepSeek V4 Pro or MAI-Thinking-1?
DeepSeek V4 Pro has the edge for agentic tasks in this comparison, averaging 59.1 versus 46. Inside this category, Terminal-Bench 2.0 is the benchmark that creates the most daylight between them.
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