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Model comparison
Moonshot AI's Kimi K3 against Xiaomi's MiMo-V2.6-Pro: vendor list prices, limits, abilities and the Artificial Analysis indexes side by side - and what OpenSmartRoute does when both are available.
MiMo-V2.6-Pro lists at $0.544 per million tokens blended against $5.17 for Kimi K3 - 9.5x less.
Kimi K3 scores 44 on the intelligence index against 30 - 14 points apart.
MiMo-V2.6-Pro reads 1.1M tokens at once, Kimi K3 1.0M.
MiMo-V2.6-Pro was released about 2 months later.
Vendor list prices per million tokens and published limits; indexes are Artificial Analysis composites (0-100).
| Specification | Kimi K3 | MiMo-V2.6-Pro |
|---|---|---|
| Input price / 1M tokens | $0.23 | $0.43 |
| Output price / 1M tokens | $20.0 | $0.87 |
| Blended (3 in : 1 out) | $5.17 | $0.54 |
| Cached input / 1M | $0.22 | $0.004 |
| Context window | 1.0M | 1.1M |
| Max output | 944K | 131K |
| Input | text, image, video | text, image, video, audio |
| Output | text | text |
| Tool calls | ||
| Structured output | ||
| Reasoning | ||
| Open weights | ||
| Intelligence index | 44 | 30 |
| Coding index | 76 | - |
| Agentic index | 50 | - |
| Released | Jul 16, 2026 | Sep 21, 2026 |
| Available on this deployment |
List price times tokens for three typical workloads; your mix of input and output decides which model's pricing suits you.
| Workload | Kimi K3 | MiMo-V2.6-Pro | Difference |
|---|---|---|---|
| Support chat20M tokens in, 5M out a month - a help desk answering a few thousand conversations. | $105 | $13.05 | $91.57 less on MiMo-V2.6-Pro |
| Document summaries100M in, 5M out - long inputs, short answers. | $123 | $47.85 | $75.25 less on MiMo-V2.6-Pro |
| Coding assistant60M in, 20M out - a team's editor assistant, output-heavy. | $414 | $43.50 | $370 less on MiMo-V2.6-Pro |
MiMo-V2.6-Pro takes the short and general requests - at $0.544 blended it is the default - and Kimi K3 the ones whose complexity or quality floor rules the cheaper model out. The split is per request, not per app, and every decision carries the scores for both.
# targets.yaml - both models as routing targets (metadata.model links each to the catalogue entry)
targets:
- { id: mimo-v2.6-pro, kind: llm, metadata: { model: xiaomi/mimo-v2.6-pro } }
- { id: kimi-k3, kind: llm, metadata: { model: moonshotai/kimi-k3 } }
# rules.yaml - the cheaper model by default, the stronger one when the request is hard
rules:
- name: simple-requests-stay-cheap
when: { max_complexity: 0.45 }
prefer: [mimo-v2.6-pro]
weight: 0.8
- name: hard-requests-escalate
when: { min_complexity: 0.45 }
prefer: [kimi-k3]
weight: 0.8Every Moonshot AI and Xiaomi model, with prices, is on the vendor pages; the rankings show what the router actually picks.