DeepSeek R1 vs MiMo-V2.6-Pro
DeepSeek · China | Xiaomi · China · Updated June 2026
Quick verdict
Pick DeepSeek R1 for open-weight reasoning model or transparent chain-of-thought. Pick MiMo-V2.6-Pro for natively omnimodal — text, image, video and audio in one model family, not bolted-on modality adapters or 1.02 trillion total parameters, 42b active per token (sparse moe), mit-licensed and self-hostable. On a tight budget at scale, MiMo-V2.6-Pro is the value pick.
DeepSeek R1 (DeepSeek) and MiMo-V2.6-Pro (Xiaomi) are two of the models people most often weigh against each other in 2026. DeepSeek R1 is the open-weight reasoning model that reset price expectations in early 2025. MiMo-V2.6-Pro is xiaomi's flagship omnimodal model — 1.02T parameters, native text/image/video/audio, MIT-licensed, released September 22, 2026. They diverge most on price and context window — each quantified below from the models' real specs.
Key differences at a glance
- ▸Price: nearly identical — $0.55/$2.19 per 1M tokens vs $0.435/$0.87 per 1M tokens. Cost will not be the deciding factor here.
- ▸Context window: MiMo-V2.6-Pro holds 8.2× more — 1M tokens (~1,573 pages) vs 128K (~192 pages). But effective recall usually fades long before the advertised ceiling, so the bigger number only helps if the model reasons over it.
- ▸Recency: MiMo-V2.6-Pro is the newer model by about 20 months (released September 22, 2026), usually meaning fresher training data and capabilities.
Side-by-side specs
| Spec | DeepSeek R1 | MiMo-V2.6-Pro |
|---|---|---|
| Provider | DeepSeek (China) | Xiaomi (China) |
| Released | January 2025 | September 22, 2026 |
| Context window | 128K (~192 pages) | 1M tokens (~1,573 pages) |
| Price (in/out) | $0.55/$2.19 per 1M tokens | $0.435/$0.87 per 1M tokens |
| Open weight? | Yes — self-hostable | Yes — self-hostable |
| Modalities | text, code | text, image, video, audio |
| SWE-Bench Verified | Not published | Not published |
| MRCR v2 @ 1M | Not published | Not published |
Who wins what
Open-weight reasoning model
DeepSeek R1
MiMo-V2.6-Pro is comparatively weak here — an Artificial Analysis Index score of 46 trails several established frontier models
Transparent chain-of-thought
DeepSeek R1
DeepSeek R1 lists transparent chain-of-thought among its strengths; MiMo-V2.6-Pro does not.
Low cost
DeepSeek R1
DeepSeek R1 lists low cost among its strengths; MiMo-V2.6-Pro does not.
Natively omnimodal — text, image, video and audio in one model family, not bolted-on modality adapters
MiMo-V2.6-Pro
DeepSeek R1 is comparatively weak here — discontinued - no longer offered as a standalone model via DeepSeek's API as of mid-2026; the legacy alias that used to point to it stopped working July 24, 2026
1.02 trillion total parameters, 42B active per token (sparse MoE), MIT-licensed and self-hostable
MiMo-V2.6-Pro
Its 1M tokens window holds about 8.2× more than DeepSeek R1's 128K in a single prompt.
Reported Artificial Analysis Intelligence Index score of 46
MiMo-V2.6-Pro
Xiaomi's flagship omnimodal model — 1.02T parameters, native text/image/video/audio, MIT-licensed, released September 22, 2026 — and it runs cheaper at $0.435/$0.87 per 1M tokens.
Lowest cost at scale
MiMo-V2.6-Pro
At $0.435/$0.87 per 1M tokens, it is the cheaper of the two — the gap dominates the bill on high-volume workloads.
Largest single-prompt input
MiMo-V2.6-Pro
Its 1M tokens window is about 8.2× larger than DeepSeek R1's 128K, fitting roughly 1,573 pages in one prompt.
Which should you pick?
A cost-sensitive startup shipping high volume
→ MiMo-V2.6-Pro
At $0.435/$0.87 per 1M tokens it undercuts DeepSeek R1, and on millions of tokens that margin decides the monthly bill.
Someone analysing very long documents or codebases
→ MiMo-V2.6-Pro
Larger 1M tokens window fits more in one prompt.
Anyone whose priority is open-weight reasoning model
→ DeepSeek R1
It is specifically built for that.
Anyone whose priority is natively omnimodal — text, image, video and audio in one model family, not bolted-on modality adapters
→ MiMo-V2.6-Pro
That is its strongest area.
DeepSeek R1: where it fits
The open-weight reasoning model that reset price expectations in early 2025. Released January 2025 by DeepSeek, it is built for open-weight reasoning model, transparent chain-of-thought, low cost, and strong maths and code.
Its trade-offs are real: discontinued - no longer offered as a standalone model via DeepSeek's API as of mid-2026; the legacy alias that used to point to it stopped working July 24, 2026, older than V4, smaller 128K context, and text/code focused. At $0.55 in / $2.19 out per million tokens, it sits in the budget price band.
MiMo-V2.6-Pro: where it fits
Xiaomi's flagship omnimodal model — 1.02T parameters, native text/image/video/audio, MIT-licensed, released September 22, 2026. Released September 22, 2026 by Xiaomi, it is built for natively omnimodal — text, image, video and audio in one model family, not bolted-on modality adapters, 1.02 trillion total parameters, 42B active per token (sparse MoE), MIT-licensed and self-hostable, reported Artificial Analysis Intelligence Index score of 46, and a separate 'UltraSpeed' variant reportedly delivers up to 20x faster output than Pro at similar quality for high-throughput use cases.
Its trade-offs: first-generation omnimodal release from Xiaomi's MiMo line — benchmark claims are largely Xiaomi's own reporting, not yet widely independently verified, an Artificial Analysis Index score of 46 trails several established frontier models, and no official API pricing from Xiaomi directly — the listed price reflects third-party inference providers (e.g. OpenRouter), which can change independently of Xiaomi's own terms. At $0.435 in / $0.87 out per million tokens, it sits in the budget price band.
The bottom line for this matchup
DeepSeek R1 and MiMo-V2.6-Pro overlap enough that the right pick depends on your specific job. MiMo-V2.6-Pro costs less per token; MiMo-V2.6-Pro holds the larger context; and each leads in its own area — DeepSeek R1 for open-weight reasoning model, MiMo-V2.6-Pro for natively omnimodal — text, image, video and audio in one model family, not bolted-on modality adapters. Rather than crowning one, run the same hard task through both once and let the results decide.
Want both DeepSeek R1 and MiMo-V2.6-Pro without two subscriptions? LumiChats gives you these plus 40+ models under one ₹69/day pass (about $1/day) — draft with one, cross-check with the other.
See pricingFrequently asked questions
Is DeepSeek R1 or MiMo-V2.6-Pro better for coding?
Public SWE-Bench figures are not available for either model, so the honest test is your own repository — run an identical real bug through both. By design, DeepSeek R1 leans toward open-weight reasoning model while MiMo-V2.6-Pro leans toward natively omnimodal — text, image, video and audio in one model family, not bolted-on modality adapters, and that positioning usually predicts which feels better on your codebase.
Which is cheaper, DeepSeek R1 or MiMo-V2.6-Pro?
MiMo-V2.6-Pro is cheaper — $0.55/$2.19 per 1M tokens vs $0.435/$0.87 per 1M tokens, roughly 1.3× apart on input.
Which has the bigger context window?
MiMo-V2.6-Pro — 1M tokens vs 128K, about 8.2× larger. Useful only if the model actually reasons over the full window, which not all do.
Can I use both DeepSeek R1 and MiMo-V2.6-Pro together?
Yes — a multi-model platform like LumiChats gives you DeepSeek R1, MiMo-V2.6-Pro and 40+ others under one ₹69/day pass (about $1/day), so you can draft with one and cross-check with the other instead of buying two subscriptions.
Which is newer, DeepSeek R1 or MiMo-V2.6-Pro?
MiMo-V2.6-Pro — released September 22, 2026, about 20 months after DeepSeek R1.
Related comparisons
Specifications and benchmarks reflect publicly reported figures as of June 2026 and may change as providers release updates. Always verify on your own workload.