Model comparison
DeepSeek V4 Flash Base vs MAI-Thinking-1
Head-to-head evidence from 2 shared benchmark results across 1 category. Overall scores shown here use the public BenchAlign v5 ranking lane.
Evidence parity. DeepSeek V4 Flash Base and MAI-Thinking-1 share 2 comparable benchmark results. 1 of 8 categories are comparable. 22 results are unique to DeepSeek V4 Flash Base; 11 to MAI-Thinking-1.
Updated July 23, 2026- Shared results
- 2
- DeepSeek V4 Flash Base only
- 22
- MAI-Thinking-1 only
- 11
- Comparable categories
- 1 / 8
Treat this as a split decision. DeepSeek V4 Flash Base makes more sense if you need the larger 1M context window or you would rather avoid the extra latency and token burn of a reasoning model; MAI-Thinking-1 is the better fit if knowledge is the priority or you want the stronger reasoning-first profile.
Confidence note. This is a partial-evidence comparison with 2 shared benchmark results across 1 evidence category; 1 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 Flash Base 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 Flash Base 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 Flash Base 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 Flash Base | Δ | MAI-Thinking-1 |
|---|---|---|---|
| Knowledge | DeepSeek V4 Flash Base56.4 | Margin→ 16.1 | MAI-Thinking-172.5 |
| Agentic | DeepSeek V4 Flash BaseNot measured | MarginNo overlap | MAI-Thinking-146.0 |
| Coding | DeepSeek V4 Flash BaseNot measured | MarginNo overlap | MAI-Thinking-165.5 |
| Reasoning | DeepSeek V4 Flash Base44.7 | MarginNo overlap | MAI-Thinking-1Not measured |
| Math | DeepSeek V4 Flash BaseNot measured | MarginNo overlap | MAI-Thinking-189.7 |
| Inst. Following | DeepSeek V4 Flash BaseNot measured | MarginNo overlap | MAI-Thinking-185.0 |
Decisive benchmark drivers
The largest measured benchmark gaps in this matchup, with exact reported values.
More
- Source ↗
MMLU-Pro
KnowledgeA 68.3%B 85%Winner: MAI-Thinking-1Δ 16.7MMLU-Pro: DeepSeek V4 Flash Base scored 68.3%; MAI-Thinking-1 scored 85%. MAI-Thinking-1 wins this benchmark. - Source ↗
SimpleQA
KnowledgeA 30.1%B 31%Winner: MAI-Thinking-1Δ 0.9SimpleQA: DeepSeek V4 Flash Base scored 30.1%; MAI-Thinking-1 scored 31%. 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 Flash Base | MAI-Thinking-1 | Comparison |
|---|---|---|---|
| Input / output priceUSD per 1M tokens | DeepSeek V4 Flash BaseNot available | MAI-Thinking-1Not available | A complete price comparison is not available. |
| Generation speedtokens per second | DeepSeek V4 Flash BaseNot available | MAI-Thinking-1Not available | A complete speed comparison is not available. |
| First-answer latencyseconds to first token | DeepSeek V4 Flash BaseNot available | MAI-Thinking-1Not available | A complete latency comparison is not available. |
| Context windowmaximum listed tokens | DeepSeek V4 Flash Base1M | MAI-Thinking-1256K | DeepSeek V4 Flash Base lists the larger context window. |
Benchmark Deep Dive
Agentic1 benchmarks
| Benchmark | DeepSeek V4 Flash Base | MAI-Thinking-1 | Result |
|---|---|---|---|
| Terminal-Bench 2.0Source | — | 46% | Not comparable |
Coding5 benchmarks
Reasoning7 benchmarks
| Benchmark | DeepSeek V4 Flash Base | MAI-Thinking-1 | Result |
|---|---|---|---|
| BBHSource | 86.9% | — | Not comparable |
| DROPSource | 88.6% | — | Not comparable |
| HellaSwagSource | 85.7% | — | Not comparable |
| WinoGrandeSource | 79.5% | — | Not comparable |
| CLUEWSCSource | 82.2% | — | Not comparable |
| LongBench v2Source | 44.7% | — | Not comparable |
| Graphwalks BFS 128KSource | — | 90% | Not comparable |
KnowledgeMAI-Thinking-1 wins14 benchmarks
| Benchmark | DeepSeek V4 Flash Base | MAI-Thinking-1 | Result |
|---|---|---|---|
| AGIEvalSource | 82.6% | — | Not comparable |
| MMLUSource | 88.7% | — | Not comparable |
| MMLU-ReduxSource | 89.4% | — | Not comparable |
| MMLU-ProSource | 68.3% | 85% | MAI-Thinking-1 leads |
| MMMLUSource | 88.8% | — | Not comparable |
| C-EvalSource | 92.1% | — | Not comparable |
| CMMLUSource | 90.4% | — | Not comparable |
| MultiLoKoSource | 42.2% | — | Not comparable |
| SimpleQASource | 30.1% | 31% | MAI-Thinking-1 leads |
| SuperGPQASource | 46.5% | — | Not comparable |
| FACTS ParametricSource | 33.9% | — | Not comparable |
| TriviaQASource | 82.8% | — | Not comparable |
| GPQASource | — | 84.2% | Not comparable |
| GPQA-DSource | — | 84.2% | Not comparable |
Math6 benchmarks
Multilingual1 benchmarks
| Benchmark | DeepSeek V4 Flash Base | MAI-Thinking-1 | Result |
|---|---|---|---|
| MGSMSource | 85.7% | — | Not comparable |
Inst. Following1 benchmarks
| Benchmark | DeepSeek V4 Flash Base | MAI-Thinking-1 | Result |
|---|---|---|---|
| IFBenchSource | — | 85% | Not comparable |
Frequently Asked Questions (2)
Which is better, DeepSeek V4 Flash Base or MAI-Thinking-1?
DeepSeek V4 Flash Base 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 Flash Base or MAI-Thinking-1?
MAI-Thinking-1 has the edge for knowledge tasks in this comparison, averaging 72.5 versus 56.4. Inside this category, MMLU-Pro is the benchmark that creates the most daylight between them.
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