MiMo-V2.5-Pro APIOPEN WEIGHTS1M context
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....
Pricing & specs mirror our live pricing as of July 2026 (pay-as-you-go).
What is 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 pricing
Pay-as-you-go on DataLLM Lab — these are our live list prices (identical to the pricing page):
| Model | Input / 1M | Output / 1M | Cache read | Cache write | Context |
|---|---|---|---|---|---|
| MiMo-V2.5-Pro | $0.43 | $0.87 | $0.0036 | — | 1M |
On output price, MiMo-V2.5-Pro is cheaper than 64% of the 309 models in the catalog. It is served by 5 providers; the best combined rate at our last snapshot was ≈ $0.43 / $0.87 per 1M via Xiaomi, with upstream quantizations fp8.
What MiMo-V2.5-Pro costs per month
| Workload | Tokens in / out (monthly) | Est. cost |
|---|---|---|
| Support chatbot | 40M / 12M | $27.84 |
| RAG / knowledge base | 200M / 20M | $104 |
| Coding agent | 80M / 25M | $56.55 |
| Batch extraction | 150M / 8M | $72.21 |
| Content generation | 20M / 40M | $43.50 |
Estimate your own monthly cost
Cost = input price × input volume + output price × output volume. The same five workloads run on every model page, so any two compare directly.
MiMo-V2.5-Pro vs alternatives
| Model | Input / 1M | Output / 1M | Context | Our test |
|---|---|---|---|---|
| MiMo-V2.5-Pro | $0.43 | $0.87 | 1M | — |
| MiMo-V2.5 | $0.10 | $0.28 | 1M | — |
| DeepSeek V4 Pro | $0.43 | $0.87 | 1M | 8/9 |
| Qwen3 VL 235B A22B Instruct | $0.20 | $0.88 | 262K | — |
| Llama 3.1 Euryale 70B v2.2 | $0.85 | $0.85 | 131K | — |
Specs
| Model ID | xiaomi/mimo-v2.5-pro |
| Modality | text->text (input: text) |
| Context window | 1,048,576 tokens |
| Max output | 131,072 tokens |
| Tool / function calling | ✅ Yes |
| Structured output (JSON) | ✅ Yes |
| Released | 2026-04-22 |
| Open weights | ✅ XiaomiMiMo/MiMo-V2.5-Pro · 102.6K downloads / 689 likes (30d) |
How to call MiMo-V2.5-Pro
from openai import OpenAI
client = OpenAI(base_url="https://api.datallmlab.com/v1", api_key="YOUR_DATALLM_LAB_KEY")
resp = client.chat.completions.create(
model="xiaomi/mimo-v2.5-pro",
messages=[{"role": "user", "content": "Hello"}],
# supports tools=[...] and tool_choice
)
print(resp.choices[0].message.content)curl https://api.datallmlab.com/v1/chat/completions \
-H "Authorization: Bearer YOUR_KEY" \
-H "Content-Type: application/json" \
-d '{"model":"xiaomi/mimo-v2.5-pro","messages":[{"role":"user","content":"Hello"}]}'import OpenAI from "openai";
const client = new OpenAI({ baseURL: "https://api.datallmlab.com/v1", apiKey: process.env.DATALLM_KEY });
const r = await client.chat.completions.create({
model: "xiaomi/mimo-v2.5-pro",
messages: [{ role: "user", content: "Hello" }],
});
console.log(r.choices[0].message.content);The same key routes MiMo-V2.5-Pro and 300+ other models — switch models by changing one string. How OpenAI-compatible APIs work.
Prompting tips for MiMo-V2.5-Pro
- State the goal, not every step. MiMo-V2.5-Pro reasons internally — give it the objective, constraints and success criteria and let it plan the approach; over-scripting each step tends to lower quality. Turn effort up for hard problems.
- Huge 1M context — but anchor the ask. You can paste whole documents or codebases; models attend most to the start and end, so put the key instruction at the top and restate it after long inputs.
- Give it real tools. Pass a
tools=[...]schema instead of asking it to "pretend" — let MiMo-V2.5-Pro emit tool calls, execute them, and feed results back for the next turn. - Constrain JSON with a schema. Use
response_format/ structured outputs rather than "reply in JSON" to get valid, parseable objects every time.
Tips are derived from MiMo-V2.5-Pro's actual capabilities — context window, tool & JSON support, modality and price tier — not generic advice.
Open-source tools for MiMo-V2.5-Pro
Popular open-source projects for running and building with MiMo-V2.5-Pro — star counts pulled from GitHub (July 2026).
Listed by GitHub stars; inclusion is by ecosystem relevance (inference engines, agent frameworks and SDKs), not affiliation. Stars change — see each repo for current numbers.
Migrating to MiMo-V2.5-Pro
Coming from OpenAI or another gateway? On an OpenAI-compatible setup the only changes are base_url → https://api.datallmlab.com/v1 and model → xiaomi/mimo-v2.5-pro. Messages, streaming, tool calls and the rest of your code stay the same. Routing & failover guide.
Self-host or use the API?
MiMo-V2.5-Pro ships open weights (XiaomiMiMo/MiMo-V2.5-Pro, ~102.6K downloads and 689 likes in the last 30 days), with community quantizations (fp8) for smaller GPUs, so you can run it yourself. Most teams still use the API: no GPU to provision or keep warm, no inference ops, and instant access across 5 providers with automatic failover. Self-host when data residency or fixed per-token economics matter most.
Rate limits & reliability
Rate limits here are the DataLLM Lab gateway's, not the upstream vendor's. On 429 (rate limited) or 503 (provider busy), retry with exponential backoff; because MiMo-V2.5-Pro is served by 5 providers, requests can fail over to a healthy one automatically. See the error-code guide and failover setup.
Related reading
Call MiMo-V2.5-Pro with one key
300+ models behind one OpenAI-compatible endpoint — better prices, better uptime, no subscriptions.
Get an API keyCompare pricingFrequently asked questions
What is 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.... It accepts text input with a 1M-token context window and was released on 2026-04-22. On DataLLM Lab it is callable through one OpenAI-compatible endpoint.
How much does MiMo-V2.5-Pro cost?
On DataLLM Lab it is $0.43 per 1M input tokens and $0.87 per 1M output tokens, with cached input at $0.0036/1M — cheaper than about 64% of the 309-model catalog on output price. Pay-as-you-go, no subscription.
What is the context window of MiMo-V2.5-Pro?
1M tokens, with up to 131K max output tokens.
Is MiMo-V2.5-Pro open source?
Yes — open weights are published on Hugging Face (XiaomiMiMo/MiMo-V2.5-Pro), with about 102.6K downloads and 689 likes in the last 30 days. You can self-host it or call it via DataLLM Lab.
How do I call the MiMo-V2.5-Pro API?
Point any OpenAI SDK at https://api.datallmlab.com/v1 and set model to "xiaomi/mimo-v2.5-pro". One DataLLM Lab key routes this model and 300+ others; no code changes beyond the base URL and model string.
What are good alternatives to MiMo-V2.5-Pro?
Close options by price and capability include MiMo-V2.5, DeepSeek V4 Pro, Qwen3 VL 235B A22B Instruct — all callable with the same DataLLM Lab key.