AI model comparison
MiMo-V2.5-Pro vs DeepSeek V3.2
Pricing, context window, benchmarks, and features compared side by side. Or skip the guesswork and send one prompt to both.
Xiaomi
MiMo-V2.5-Pro
MiMo-V2.5-Pro is Xiaomi’s flagship model, delivering strong performance in general agentic capabilities, complex software engineering, and long-horizon tasks, with top rankings on benchmarks such as ClawEval, GDPVal, and SWE-bench Pro.
MiMo-V2.5-Pro is scheduled to be retired on October 21, 2026. Consider MiMo-V2.6-Pro instead.
- Input / 1M
- $0.44
- Output / 1M
- $0.87
- Context
- 1.05M
DeepSeek
DeepSeek V3.2
DeepSeek-V3.2 is a large language model designed to harmonize high computational efficiency with strong reasoning and agentic tool-use performance.
- Input / 1M
- $0.26
- Output / 1M
- $0.80
- Context
- 164K
At a glance
Quick verdict
How the two models stack up on the things people ask about most.
Lower price
DeepSeek V3.2
1.4x cheaper for a typical chat
Higher intelligence score
MiMo-V2.5-Pro
26 vs 21.5 on Artificial Analysis
Larger context window
MiMo-V2.5-Pro
1.05M vs 164K tokens
Newer release
MiMo-V2.5-Pro
Released April 22, 2026
Benchmarks
Benchmark scores
Independent scores from Artificial Analysis. Higher is better.
Intelligence index
DeepSeek V3.221.5Coding index
DeepSeek V3.244.2Agentic index
DeepSeek V3.2Not availablePricing
MiMo-V2.5-Pro vs DeepSeek V3.2 API pricing
Per-token API rates. Cheaper option highlighted.
| Metric | DeepSeek V3.2 | |
|---|---|---|
| Input tokensPer 1M tokens | $0.44 | $0.26 |
| Output tokensPer 1M tokens | $0.87 | $0.80 |
| Cached input (read)Per 1M tokens | $0.00 | $0.14 |
| Cache writePer 1M tokens | Not available | Not available |
What it costs in practice
Estimated cost per 1,000 requests at standard rates. Coding and long-document figures also show the cost when the input is already cached.
Chat message
2K in, 500 out
DeepSeek V3.2$0.92Coding task
30K in, 4K out
DeepSeek V3.2$10.97$7.40 cachedLong document summary
150K in, 2K out
DeepSeek V3.2$40.45$22.60 cachedSpecs
Context window and capabilities
How much each model can read, how much it can write, and what it accepts as input.
| Metric | DeepSeek V3.2 | |
|---|---|---|
| Context window | 1.05M tokens | 164K tokens |
| Max output | 131K tokens | 147K tokens |
| Input types | Text | Text |
| Output types | Text | Text |
| Reasoning effort levels | Not available | Not available |
| Default reasoning effort | Not available | Not available |
| Release date | April 22, 2026 | December 1, 2025 |
Features
Supported features
API features available for each model.
| Metric | DeepSeek V3.2 | |
|---|---|---|
| Tool calling | Supported | Supported |
| Structured outputs | Supported | Supported |
| JSON mode | Supported | Supported |
| Reasoning | Supported | Supported |
| Temperature | Supported | Supported |
| Stop sequences | Supported | Supported |
| Deterministic seed | Supported | Supported |
| Verbosity control | Not supported | Not supported |
Keep exploring
More on these models
Other head-to-heads, the full model page, and the alternatives list for each model.
- MiMo-V2.5-Pro vs DeepSeek V4 Flash 0423
- MiMo-V2.5-Pro vs Hy3
- MiMo-V2.5-Pro vs MiniMax M3
- MiMo-V2.5-Pro vs Gemini 3 Flash Preview
- MiMo-V2.5-Pro vs Solar Mini 4
- MiMo-V2.5-Pro vs Solar Pro 4
- MiMo-V2.5-Pro vs DeepSeek V4 Pro 0423
- MiMo-V2.5-Pro vs MiMo-V2.5
- MiMo-V2.5-Pro vs Inkling Small
- MiMo-V2.5-Pro vs Qwen3.7 Plus
- MiMo-V2.5-Pro vs Ling 3.0 Flash VL
DeepSeek V3.2View full model details- DeepSeek V3.2 vs DeepSeek V4 Flash 0423
- DeepSeek V3.2 vs Hy3
- DeepSeek V3.2 vs Solar Mini 4
- DeepSeek V3.2 vs DeepSeek V4 Pro 0423
- DeepSeek V3.2 vs MiMo-V2.5
- DeepSeek V3.2 vs Gemini 3.5 Flash Lite
- DeepSeek V3.2 vs Qwen3.6 35B A3B
- DeepSeek V3.2 vs GPT-5 Mini
- DeepSeek V3.2 vs Ling 3.0 Flash
- DeepSeek V3.2 vs GPT-5.4 Nano
- DeepSeek V3.2 vs Step 3.7 Flash
- DeepSeek V3.2 vs Ling 3.0 Flash VL
- DeepSeek V3.2 vs MiniMax M2.7
- DeepSeek V3.2 vs MiniMax M2.5
- DeepSeek V3.2 vs Ling 3.0 Flash Fin
- DeepSeek V3.2 vs MiniMax M2.1
- DeepSeek V3.2 vs GPT-5.1-Codex-Mini
- DeepSeek V3.2 vs Qwen3.5-35B-A3B
- DeepSeek V3.2 vs LongCat 2.0
- DeepSeek V3.2 vs DeepSeek V3.2 Exp
- DeepSeek V3.2 vs DeepSeek V3.1 Terminus
Our take
DeepSeek V3.2 is 1.4x cheaper for a typical chat. MiMo-V2.5-Pro scores higher on the Artificial Analysis Intelligence Index (26 vs 21.5). MiMo-V2.5-Pro has the larger context window (1.05M vs 164K tokens). The right pick depends on your workload, so the quickest way to settle it is to send the same prompt to both and compare.
FAQ
Frequently asked questions
Is MiMo-V2.5-Pro or DeepSeek V3.2 cheaper?
DeepSeek V3.2 is cheaper for a typical chat (2K input tokens and 500 output tokens). DeepSeek V3.2 costs $0.26 per 1M input tokens and $0.80 per 1M output tokens, while MiMo-V2.5-Pro costs $0.44 per 1M input tokens and $0.87 per 1M output tokens.
Which has a bigger context window, MiMo-V2.5-Pro or DeepSeek V3.2?
MiMo-V2.5-Pro supports up to 1.05M tokens of context, compared with 164K for DeepSeek V3.2.
Is MiMo-V2.5-Pro smarter than DeepSeek V3.2?
On the Artificial Analysis Intelligence Index, MiMo-V2.5-Pro scores 26 and DeepSeek V3.2 scores 21.5, putting MiMo-V2.5-Pro ahead. Benchmarks don't capture everything, so the best test is running your own prompts through both.
Can I use MiMo-V2.5-Pro and DeepSeek V3.2 at the same time?
Yes. Shortcut Chat sends one prompt to multiple models at once, so you can see MiMo-V2.5-Pro and DeepSeek V3.2 answer side by side and keep the better response.
Why choose? Ask both.
Send one prompt to MiMo-V2.5-Pro and DeepSeek V3.2 at the same time. Compare the answers side by side and keep the best one.