Model comparison
MiniMax M2.5 / M2.5-Lightning vs DeepSeek-V3.2
- Input
- $0.15 / 1M tokens (M2.5); $0.30 / 1M tokens (M2.5-Lightning)
- Output
- $1.20 / 1M tokens (M2.5); $2.40 / 1M tokens (M2.5-Lightning)
- Context
- 205K
- Released
- 2026-02-12
- Input
- $0.30
- Output
- $0.45
- Context
- 128K
- Released
- 2025-12-01
MiniMax M2.5 / M2.5-Lightning scores higher on 3 of the 4 benchmarks both models report (the other leads on 1); MiniMax M2.5 / M2.5-Lightning is cheaper on input tokens ($0.2 vs $0.3 per 1M, 2×); MiniMax M2.5 / M2.5-Lightning has the larger context window (205K vs 128K).
Specs and pricing side by side
| Spec | MiniMax M2.5 / M2.5-Lightning | DeepSeek-V3.2 |
|---|---|---|
| Maker | MiniMax | DeepSeek |
| Released | 2026-02-12 | 2025-12-01 |
| Context window | 205K | 128K |
| Max output | ~131K tokens | 64K |
| Input price | $0.15 / 1M tokens (M2.5); $0.30 / 1M tokens (M2.5-Lightning) | $0.30 |
| Output price | $1.20 / 1M tokens (M2.5); $2.40 / 1M tokens (M2.5-Lightning) | $0.45 |
| Parameters | 229B total / 10B active (MoE) | 685B total / 37B active (MoE) |
| License | Modified MIT (attribution required for commercial use) | MIT |
| Weights | Open weights | Open weightssame |
| Modalities | Text | Textsame |
| Knowledge cutoff | Not disclosed | Not disclosedsame |
Benchmarks both models report
| Benchmark | MiniMax M2.5 / M2.5-Lightning | DeepSeek-V3.2 |
|---|---|---|
| SWE-bench Verified | 80.2% | 70% |
| GPQA Diamond | 85.2% | 82.4% |
| MMLU-Pro | 80.1% | 85% |
| Artificial Analysis Intelligence Index | 42% | 33% |
Scores are as published by each maker or its cited source; harness, reasoning effort and date can differ between rows, so treat small gaps as ties. Sources are listed on each model page.
Which one should you pick?
Pick MiniMax M2.5 / M2.5-Lightning if…
- You care about SWE-bench Verified, GPQA Diamond, Artificial Analysis Intelligence Index (it scores higher on 3 shared benchmarks).
- Cost matters: input tokens cost 2× less ($0.2 vs $0.3 per 1M).
- You need the longer context (205K vs 128K).
- Your use case is: autonomous and semi-autonomous coding agents running across large codebases.
Pick DeepSeek-V3.2 if…
- You care about MMLU-Pro (it scores higher on 1 shared benchmark).
- Your use case is: cost-sensitive agentic workflows that need tool-calling plus reasoning.
FAQ
Which is better, MiniMax M2.5 / M2.5-Lightning or DeepSeek-V3.2?
MiniMax M2.5 / M2.5-Lightning scores higher on 3 of the 4 benchmarks both models report (the other leads on 1); MiniMax M2.5 / M2.5-Lightning is cheaper on input tokens ($0.2 vs $0.3 per 1M, 2×); MiniMax M2.5 / M2.5-Lightning has the larger context window (205K vs 128K). The better pick depends on whether you value benchmark scores, price per token, context length or openness for your workload.
How much cheaper is MiniMax M2.5 / M2.5-Lightning?
MiniMax M2.5 / M2.5-Lightning: $0.15 / 1M tokens (M2.5); $0.30 / 1M tokens (M2.5-Lightning) input, $1.20 / 1M tokens (M2.5); $2.40 / 1M tokens (M2.5-Lightning) output. DeepSeek-V3.2: $0.30 input, $0.45 output (list API prices as published by each maker).
What are the context windows of MiniMax M2.5 / M2.5-Lightning and DeepSeek-V3.2?
MiniMax M2.5 / M2.5-Lightning offers 205K with up to ~131K tokens output; DeepSeek-V3.2 offers 128K with up to 64K output.
Is MiniMax M2.5 / M2.5-Lightning newer than DeepSeek-V3.2?
MiniMax M2.5 / M2.5-Lightning was released 2026-02-12; DeepSeek-V3.2 was released 2025-12-01.