Model comparison
DeepSeek V4 Pro Base vs MiniMax M2.7
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: DeepSeek V4 Pro Base unranked (Not scored); MiniMax M2.7 #36 (Supported). Intervals and evidence labels describe ranking uncertainty, not a guarantee for a specific workload.
Evidence parity. DeepSeek V4 Pro Base and MiniMax M2.7 share 0 comparable benchmark results. 0 of 8 categories are comparable. 24 results are unique to DeepSeek V4 Pro Base; 35 to MiniMax M2.7.
Updated July 23, 2026- Shared results
- 0
- DeepSeek V4 Pro Base only
- 24
- MiniMax M2.7 only
- 35
- Comparable categories
- 0 / 8
Benchmark data for DeepSeek V4 Pro Base and MiniMax M2.7 is coming soon on BenchLM.
Confidence note. This is a partial-evidence comparison with 0 shared benchmark results across 0 evidence categories; 0 of 8 categories currently have scoreable aggregates for both models. Treat the verdict as directional until coverage is more balanced.
Why this result
BenchLM has partial data for these models, but not enough overlapping benchmark coverage to produce a fair score-level comparison yet.
DeepSeek V4 Pro Base has the larger context window at 1M, compared with 200K for MiniMax M2.7.
Operational comparison
Runtime and commercial metrics are compared only when both models have a complete sourced value.
| Metric | DeepSeek V4 Pro Base | MiniMax M2.7 | Comparison |
|---|---|---|---|
| Input / output priceUSD per 1M tokens | DeepSeek V4 Pro BaseNot available | MiniMax M2.7$0.3 input / $1.2 output | A complete price comparison is not available. |
| Generation speedtokens per second | DeepSeek V4 Pro BaseNot available | MiniMax M2.745 tok/s | A complete speed comparison is not available. |
| First-answer latencyseconds to first token | DeepSeek V4 Pro BaseNot available | MiniMax M2.72.53 s | A complete latency comparison is not available. |
| Context windowmaximum listed tokens | DeepSeek V4 Pro Base1M | MiniMax M2.7200K | DeepSeek V4 Pro Base lists the larger context window. |
Benchmark Deep Dive
Agentic11 benchmarks
| Benchmark | DeepSeek V4 Pro Base | MiniMax M2.7 | Result |
|---|---|---|---|
| Terminal-Bench 2.0Source | — | 57% | Not comparable |
| τ²-bench resultsSource | — | 84.8% | Not comparable |
| ToolathlonSource | — | 46.3% | Not comparable |
| MLE-Bench LiteSource | — | 66.6% | Not comparable |
| MM-ClawBenchSource | — | 62.7% | Not comparable |
| Claw-EvalSource | — | 48.7% | Not comparable |
| AA Agentic IndexSource | — | 25.6% | Not comparable |
| APEX-Agents-AASource | — | 10.6% | Not comparable |
| GDPval-AASource | — | 32.9% | Not comparable |
| GDPval-AASource | — | 1158 | Not comparable |
| Gert LabsSource | — | 40.40% | Not comparable |
Coding13 benchmarks
| Benchmark | DeepSeek V4 Pro Base | MiniMax M2.7 | Result |
|---|---|---|---|
| BigCodeBenchSource | 59.2% | — | Not comparable |
| HumanEvalSource | 76.8% | — | Not comparable |
| SWE-bench Verified*Source | — | 75.4% | Not comparable |
| SWE-bench ProSource | — | 56.2% | Not comparable |
| SWE-RebenchSource | — | 51.9% | Not comparable |
| SWE MultilingualSource | — | 76.5% | Not comparable |
| Multi-SWE BenchSource | — | 52.7% | Not comparable |
| VIBE-ProSource | — | 55.6% | Not comparable |
| NL2RepoSource | — | 39.8% | Not comparable |
| Vibe Code BenchSource | — | 27.04% | Not comparable |
| React Native EvalsSource | — | 71.4% | Not comparable |
| AA Coding IndexSource | — | 52.6% | Not comparable |
| AA-SciCodeSource | — | 47.0% | Not comparable |
Reasoning8 benchmarks
| Benchmark | DeepSeek V4 Pro Base | MiniMax M2.7 | Result |
|---|---|---|---|
| BBHSource | 87.5% | — | Not comparable |
| DROPSource | 88.7% | — | Not comparable |
| HellaSwagSource | 88.0% | — | Not comparable |
| WinoGrandeSource | 81.5% | — | Not comparable |
| CLUEWSCSource | 85.2% | — | Not comparable |
| LongBench v2Source | 51.5% | — | Not comparable |
| AA-LCRSource | — | 68.7% | Not comparable |
| CritPtSource | — | 0.6% | Not comparable |
Knowledge20 benchmarks
| Benchmark | DeepSeek V4 Pro Base | MiniMax M2.7 | Result |
|---|---|---|---|
| AGIEvalSource | 83.1% | — | Not comparable |
| MMLUSource | 90.1% | — | Not comparable |
| MMLU-ReduxSource | 90.8% | — | Not comparable |
| MMLU-ProSource | 73.5% | — | Not comparable |
| MMMLUSource | 90.3% | — | Not comparable |
| C-EvalSource | 93.1% | — | Not comparable |
| CMMLUSource | 90.8% | — | Not comparable |
| MultiLoKoSource | 51.1% | — | Not comparable |
| SimpleQASource | 55.2% | — | Not comparable |
| SuperGPQASource | 53.9% | — | Not comparable |
| FACTS ParametricSource | 62.6% | — | Not comparable |
| TriviaQASource | 85.6% | — | Not comparable |
| GPQA-DSource | — | 87.0% | Not comparable |
| MMLU-Pro (Arcee)Source | — | 80.8% | Not comparable |
| Artificial Analysis Intelligence IndexSource | — | 38.1% | Not comparable |
| AA-GPQA DiamondSource | — | 87.4% | Not comparable |
| AA-HLESource | — | 28.1% | Not comparable |
| AA-Omniscience IndexSource | — | 0.7% | Not comparable |
| AA-Omniscience AccuracySource | — | 26.1% | Not comparable |
| AA-Omniscience Hallucination RateSource | — | 34.4% | Not comparable |
Math4 benchmarks
Multilingual1 benchmarks
| Benchmark | DeepSeek V4 Pro Base | MiniMax M2.7 | Result |
|---|---|---|---|
| MGSMSource | 84.4% | — | Not comparable |
Multimodal1 benchmarks
| Benchmark | DeepSeek V4 Pro Base | MiniMax M2.7 | Result |
|---|---|---|---|
| Design Arena WebsiteSource | — | 1275 | Not comparable |
Inst. Following1 benchmarks
| Benchmark | DeepSeek V4 Pro Base | MiniMax M2.7 | Result |
|---|---|---|---|
| AA-IFBenchSource | — | 75.7% | Not comparable |
Frequently Asked Questions (3)
Can I compare DeepSeek V4 Pro Base and MiniMax M2.7 on BenchLM yet?
Not fully yet. BenchLM is tracking both models, but the sourced benchmark breakdown for this comparison is still coming soon.
Why does this comparison show “coming soon”?
BenchLM only shows category winners and benchmark-level calls when we have sourced results that can be compared fairly. For these models, the public benchmark coverage is not complete enough yet.
What data is available for DeepSeek V4 Pro Base and MiniMax M2.7 today?
DeepSeek V4 Pro Base: Pricing unavailable MiniMax M2.7: $0.30 input / $1.20 output per 1M tokens Both model pages still include creator, context window, reasoning mode, and other metadata while benchmark coverage fills in.
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