Laguna XS.2 vs MiMo-V2.5
MiMo-V2.5 comes out ahead, 72 to 36 on our weighted score, and it is the cheaper option too.
Poolside
Laguna XS.2
36/100- ECI—
- Price—
- Context262K
- Our pick
Xiaomi
MiMo-V2.5
72/100- ECI—
- Price$0.14 / $0.28
- Context1.05M
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Make it a three-way comparison.
MiMo-V2.5 is our pick
MiMo-V2.5 is the better all-round choice, scoring 72/100 against Laguna XS.2 (36). It leads on inputs & features and context window. The score weighs inputs & features 60%, context window 40%. None of the shared benchmarks cover every model here yet, so capability is left out of this verdict.
- CapabilityNot enough dataNo independent benchmark covers every model here yet
- Lowest priceMiMo-V2.5MiMo-V2.5 $0.175 per 1M tokens (3:1 blend) · Laguna XS.2 unpriced
- Longest contextMiMo-V2.5MiMo-V2.5 1,048,576 · Laguna XS.2 262,144 tokens
- Widest inputsMiMo-V2.5Laguna XS.2: Text · MiMo-V2.5: Text, Images, Audio, Video
- Self-hostingAll open weightsEvery model here can be downloaded and run on your own hardware
| Measure | Weight | Laguna XS.2 | MiMo-V2.5 |
|---|---|---|---|
| Inputs & features | 60% | 35 | 80 |
| Context window | 40% | 37 | 61 |
| Overall | 100% | 36/100 | 72/100 |
Left out because at least one model lacks the data: capability and price. The remaining weights were rescaled.
Every spec in one table
Highlighted cells lead their row. Dashes mean the data is not published.
| Specification | ||
|---|---|---|
| Capability | ||
| Capabilities Index (ECI) | — | — |
| ECI rank | — | — |
| Price per million tokens | ||
| Input | — | $0.14 |
| Output | — | $0.28 |
| Cached input | — | $0.0028 |
| Blended (3:1) | — | $0.175 |
| Long-context rate | — | Same rate |
| Price source | — | Official Xiaomi API |
| Limits | ||
| Context window | 262,144 tokens | 1,048,576 tokens (best) |
| Max output | 32,768 tokens | 131,072 tokens (best) |
| Inputs and features | ||
| Text | Yes | Yes |
| Images | No | Yes |
| PDFs | No | No |
| Audio | No | Yes |
| Video | No | Yes |
| Reasoning | Yes | Yes |
| Tool calling | Yes | Yes |
| Structured output | No | No |
| Availability | ||
| Weights | Open | Open |
| API model ID | — | mimo-v2.5 |
| API providers | 1 | 21 (best) |
| Released | Apr 28, 2026 | Apr 22, 2026 |
| Knowledge cutoff | — | Dec 2024 |
What would a month cost?
Enter your expected volume in millions of tokens. List prices only; caching and batch discounts would lower these.
Laguna XS.2—
MiMo-V2.5$1.96
Which should you choose?
Which is better: Laguna XS.2 or MiMo-V2.5?
MiMo-V2.5 is the better all-round choice, scoring 72/100 against Laguna XS.2 (36). It leads on inputs & features and context window. The score weighs inputs & features 60%, context window 40%. None of the shared benchmarks cover every model here yet, so capability is left out of this verdict.
Which is cheaper, Laguna XS.2 or MiMo-V2.5?
MiMo-V2.5 is cheaper at $0.14 input / $0.28 output per million tokens (official Xiaomi API price). . At a typical mix of three input tokens to one output token, that is $0.175 per million tokens for MiMo-V2.5 versus . Laguna XS.2 has no published per-token price.
Which scores higher on benchmarks?
There is no independent benchmark that covers both models yet. Laguna XS.2 has not been scored yet and MiMo-V2.5 has not been scored yet.
Which is better for coding?
There are no published SWE-bench Verified results for Laguna XS.2 and MiMo-V2.5 yet, so there is no like-for-like coding score. Test both on a sample of your own tasks. Both support tool calling for agent workflows.
Which has the bigger context window?
MiMo-V2.5 has the largest context window at 1,048,576 tokens, against 262,144 for Laguna XS.2. Maximum output per response: Laguna XS.2 up to 32,768, MiMo-V2.5 up to 131,072 tokens.
Which can read images, PDFs, audio or video?
Laguna XS.2 accepts text; MiMo-V2.5 accepts text, images, audio and video. MiMo-V2.5 handles the widest range of inputs.
Are any of these open source?
Yes, both publish their weights, so you can self-host them.
Which is newer?
Laguna XS.2 is the newest, released Apr 28, 2026. MiMo-V2.5 came out Apr 22, 2026. Knowledge cutoff: MiMo-V2.5 Dec 2024.
How do you decide the winner?
Each model gets a 0–100 score on capability (50%, independent benchmark results); price (25%, blended price per million tokens (3 input : 1 output), log scale); inputs & features (15%, image, PDF, audio and video input, tool calling, structured output and reasoning); context window (10%, maximum tokens per request, log scale). Dimensions missing for any model are dropped and the remaining weights rescaled, so every model is judged on the same evidence. Specs and prices come from public model listings and the labs’ own API pages; capability scores come from independent benchmark runs. Data updated Oct 4, 2026.