Intelligence
36 scoreXiaomi · Flagships Analysis
MiMo-V2-Omni-0327
Intelligence, Performance & Price Analysis
Canonical slug: mimo-v2-omni-0327 · Canonical model registry at build time
Input Price
$0.40 / 1M tokensOutput Price
$2.00 / 1M tokensExecutive Assessment
Routing Verdict & Tradeoffs
Frontier research / complex reasoning
MiMo-V2-Omni-0327 scores 36 (estimated) on the Artificial Analysis Intelligence Index, placing it well above average among other reasoning models in a similar price tier (median: 15). MiMo-V2-Omni-0327 costs $0.40 per 1M input tokens (at the higher end, median: $0.25) and $2.00 per 1M output tokens (at the higher end, median: $0.87), based on the median across providers serving the model.
Reserve this model for the hardest requests; simpler or repetitive work should stay on cheaper routes.
Task Fit Assessment
| Workload | Rating | Notes |
|---|---|---|
| Complex reasoning & agentic workflows | optimal | Intelligence score 36 places this model among top performers. Suitable for multi-step analysis and agentic loops. |
| Cost-sensitive pipelines | viable | Output pricing at $2.00 is premium. Route high-volume simple tasks to cheaper alternatives. |
Cost Pressure Analysis
Medium
Pricing is moderate — input $0.40, output $2.00. Costs accumulate at volume but are manageable for valuable tasks.
Technical Specifications
Architecture and Limits
| Specification | Value | Validation Authority |
|---|---|---|
| Model type | Proprietary | inferred |
| Reasoning | Yes | faq |
| Input modalities | MiMo-V2-Omni-0327 supports text and image input. | faq |
| Output modalities | MiMo-V2-Omni-0327 supports text output. | faq |
| Context window | 260k tokens | faq |
| Open weights / source | No, MiMo-V2-Omni-0327 is proprietary. The model weights are not publicly available. | faq |
| Parameters | MiMo-V2-Omni-0327 is a proprietary model and Xiaomi has not disclosed the model size or parameter count. | faq |
| API availability | Yes, MiMo-V2-Omni-0327 is available via API through 1 provider. | faq |
Evidence charts
Profile visualizations
Charts are the same canonical evidence cards previously published for this slug, contained inside the D18D page grammar.
AA-Omniscience Index
AA-Omniscience Index (higher is better) measures knowledge reliability and hallucination. It rewards correct answers, penalizes hallucinations, and has no penalty for refusing to answer. Scores range from -100 to 100, where 0 means as many correct as incorrect answers, and negative scores mean more incorrect than correct. · Evaluation results measured independently by Artificial Analysis
Chart source and provenance are listed in Methodology & sources below.
- Source:
- Published benchmark dataset
- Retrieval date:
- 2026-07-08
- Methodology:
- Independent test run by Artificial Analysis on dedicated hardware.
Artificial Analysis Intelligence Index by Open Weights / Proprietary
Artificial Analysis Intelligence Index v4.1 incorporates 9 evaluations: GDPval-AA v2, 𝜏³-Banking, Terminal-Bench v2.1, SciCode, Humanity's Last Exam, GPQA Diamond, CritPt, AA-Omniscience, AA-LCR · Evaluation results measured independently by Artificial Analysis
Chart source and provenance are listed in Methodology & sources below.
- Source:
- Published benchmark dataset
- Retrieval date:
- 2026-07-08
- Methodology:
- Independent test run by Artificial Analysis on dedicated hardware.
Artificial Analysis Intelligence Index
Artificial Analysis Intelligence Index v4.1 incorporates 9 evaluations: GDPval-AA v2, 𝜏³-Banking, Terminal-Bench v2.1, SciCode, Humanity's Last Exam, GPQA Diamond, CritPt, AA-Omniscience, AA-LCR · Evaluation results measured independently by Artificial Analysis
Chart source and provenance are listed in Methodology & sources below.
- Source:
- Published benchmark dataset
- Retrieval date:
- 2026-07-08
- Methodology:
- Independent test run by Artificial Analysis on dedicated hardware.
Intelligence
Artificial Analysis Intelligence Index · Higher is better · Evaluation results measured independently by Artificial Analysis
Chart source and provenance are listed in Methodology & sources below.
- Source:
- Published benchmark dataset
- Retrieval date:
- 2026-07-08
- Methodology:
- Independent test run by Artificial Analysis on dedicated hardware.
Speed
Output tokens per second · Higher is better · Evaluation results measured independently by Artificial Analysis
Chart source and provenance are listed in Methodology & sources below.
- Source:
- Published benchmark dataset
- Retrieval date:
- 2026-07-08
- Methodology:
- Independent test run by Artificial Analysis on dedicated hardware.
Context Window
Context window: tokens limit · Higher is better · Evaluation results measured independently by Artificial Analysis
Chart source and provenance are listed in Methodology & sources below.
- Source:
- Published benchmark dataset
- Retrieval date:
- 2026-07-08
- Methodology:
- Independent test run by Artificial Analysis on dedicated hardware.
Cost per Intelligence Index Task
Weighted average cost (USD) per Artificial Analysis Intelligence Index task, segmented by token type. Lower is better · Evaluation results measured independently by Artificial Analysis
Chart source and provenance are listed in Methodology & sources below.
- Source:
- Published benchmark dataset
- Retrieval date:
- 2026-07-08
- Methodology:
- Independent test run by Artificial Analysis on dedicated hardware.
Cost per Task
Weighted average cost (USD) per Intelligence Index task · Lower is better · Evaluation results measured independently by Artificial Analysis
Chart source and provenance are listed in Methodology & sources below.
- Source:
- Published benchmark dataset
- Retrieval date:
- 2026-07-08
- Methodology:
- Independent test run by Artificial Analysis on dedicated hardware.
Cost to Run Artificial Analysis Intelligence Index
Cost (USD) to run all evaluations in the Artificial Analysis Intelligence Index · Evaluation results measured independently by Artificial Analysis
Chart source and provenance are listed in Methodology & sources below.
- Source:
- Published benchmark dataset
- Retrieval date:
- 2026-07-08
- Methodology:
- Independent test run by Artificial Analysis on dedicated hardware.
Pricing: Cache Hit, Input, and Output
Price (USD per M Tokens) · Evaluation results measured independently by Artificial Analysis
Chart source and provenance are listed in Methodology & sources below.
- Source:
- Published benchmark dataset
- Retrieval date:
- 2026-07-08
- Methodology:
- Independent test run by Artificial Analysis on dedicated hardware.
Methodology
Methodology & Provenance
This page is rendered from the normalized profile and page JSON for MiMo-V2-Omni-0327.
Benchmark values are preserved as normalized; only layout, disclosure ordering, and typography are adjusted for readability.
Frequently Asked Questions
Model FAQs & Technical Disclosures
MiMo-V2-Omni-0327 was released on March 27, 2026.
MiMo-V2-Omni-0327 was created by Xiaomi.
MiMo-V2-Omni-0327 scores 36 (estimated) on the Artificial Analysis Intelligence Index, placing it well above average among other reasoning models in a similar price tier (median: 15).
MiMo-V2-Omni-0327 costs $0.40 per 1M input tokens (at the higher end, median: $0.25) and $2.00 per 1M output tokens (at the higher end, median: $0.87), based on the median across providers serving the model.
MiMo-V2-Omni-0327 costs $0.40 per 1M input tokens and $2.00 per 1M output tokens (based on the median across providers serving the model). For a blended rate (7:2:1 cache hit/input/output ratio), this is $0.34 per 1M tokens. Pricing may vary by provider.
Yes, MiMo-V2-Omni-0327 is a reasoning model. It uses extended thinking or chain-of-thought reasoning to work through complex problems before providing an answer.
MiMo-V2-Omni-0327 supports text and image input.
MiMo-V2-Omni-0327 supports text output.
Yes, MiMo-V2-Omni-0327 supports image input and can analyze, describe, and answer questions about images.
Yes, MiMo-V2-Omni-0327 is multimodal. It can process text and image input and generate text output.
MiMo-V2-Omni-0327 has a context window of 260k tokens. This determines how much text and conversation history the model can process in a single request.
No, MiMo-V2-Omni-0327 is proprietary. The model weights are not publicly available.
MiMo-V2-Omni-0327 is a proprietary model and Xiaomi has not disclosed the model size or parameter count.
MiMo-V2-Omni-0327 achieves a score of 36 on the Artificial Analysis Intelligence Index. This composite benchmark evaluates models across reasoning, knowledge, mathematics, and coding.
Yes, MiMo-V2-Omni-0327 is available via API through 1 provider.
MiMo-V2-Omni-0327 is available through 1 API provider.