DeepSeek V4-Pro vs MiMo-V2.5
DeepSeek · China | Xiaomi · China · Updated June 2026
Quick verdict
Pick DeepSeek V4-Pro for open-weight 1.6t moe (~49b active) — deepseek's largest, self-hostable or 1m-token context with up to 384k output tokens. Pick MiMo-V2.5 for native omnimodal — strong image and video understanding or very low cost (~half the inference of the pro tier). On a tight budget at scale, MiMo-V2.5 is the value pick.
DeepSeek V4-Pro (DeepSeek) and MiMo-V2.5 (Xiaomi) are two of the models people most often weigh against each other in 2026. DeepSeek V4-Pro is deepSeek's 1.6-trillion-parameter open-weight model at $0.435/$0.87 — strong open-weight coding and a 1M context at a fraction of flagship prices. MiMo-V2.5 is xiaomi's cheap omnimodal model — Pro-level agentic perception across image and video at a fraction of the cost. Their biggest split is price, and the breakdown below shows exactly how that plays out for your workload.
Key differences at a glance
- ▸Price: MiMo-V2.5 is about 4.7× cheaper on input ($0.14/$0.28 per 1M tokens vs $0.66/$1.98 per 1M tokens) — meaningful once you are processing millions of tokens a month.
- ▸Context window: both advertise 1M (~1,500 pages). Tie on paper — test on your own long inputs, since usable recall varies by model.
Side-by-side specs
| Spec | DeepSeek V4-Pro | MiMo-V2.5 |
|---|---|---|
| Provider | DeepSeek (China) | Xiaomi (China) |
| Released | April 24, 2026 | April 22, 2026 |
| Context window | 1M (~1,500 pages) | 1M (~1,500 pages) |
| Price (in/out) | $0.66/$1.98 per 1M tokens | $0.14/$0.28 per 1M tokens |
| Open weight? | Yes — self-hostable | Yes — self-hostable |
| Modalities | text, code | text, image, audio, video, code |
| SWE-Bench Verified | Not published | Not published |
| MRCR v2 @ 1M | Not published | Not published |
Who wins what
Open-weight 1.6T MoE (~49B active) — DeepSeek's largest, self-hostable
DeepSeek V4-Pro
DeepSeek's 1.6-trillion-parameter open-weight model at $0.435/$0.87 — strong open-weight coding and a 1M context at a fraction of flagship prices — and it is the newer of the two.
1M-token context with up to 384K output tokens
DeepSeek V4-Pro
DeepSeek V4-Pro lists 1M-token context with up to 384K output tokens among its strengths; MiMo-V2.5 does not.
Permanent low pricing at $0.435/$0.87 per million, set May 2026
DeepSeek V4-Pro
DeepSeek V4-Pro lists permanent low pricing at $0.435/$0.87 per million, set May 2026 among its strengths; MiMo-V2.5 does not.
Native omnimodal — strong image and video understanding
MiMo-V2.5
DeepSeek V4-Pro is comparatively weak here — text and code only — no image, audio or video
Very low cost (~half the inference of the Pro tier)
MiMo-V2.5
At $0.14/$0.28 per 1M tokens it undercuts DeepSeek V4-Pro ($0.66/$1.98 per 1M tokens), and that gap compounds at volume.
Agent-framework integration
MiMo-V2.5
Xiaomi's cheap omnimodal model — Pro-level agentic perception across image and video at a fraction of the cost — and it runs cheaper at $0.14/$0.28 per 1M tokens.
Lowest cost at scale
MiMo-V2.5
At $0.14/$0.28 per 1M tokens, it is the cheaper of the two — the gap dominates the bill on high-volume workloads.
Which should you pick?
A cost-sensitive startup shipping high volume
→ MiMo-V2.5
At $0.14/$0.28 per 1M tokens it undercuts DeepSeek V4-Pro, and on millions of tokens that margin decides the monthly bill.
Anyone whose priority is open-weight 1.6t moe (~49b active) — deepseek's largest, self-hostable
→ DeepSeek V4-Pro
It is specifically built for that.
Anyone whose priority is native omnimodal — strong image and video understanding
→ MiMo-V2.5
That is its strongest area.
DeepSeek V4-Pro: where it fits
DeepSeek's 1.6-trillion-parameter open-weight model at $0.435/$0.87 — strong open-weight coding and a 1M context at a fraction of flagship prices. Released April 24, 2026 by DeepSeek, it is built for open-weight 1.6T MoE (~49B active) — DeepSeek's largest, self-hostable, 1M-token context with up to 384K output tokens, permanent low pricing at $0.435/$0.87 per million, set May 2026, and sources place it near the top of open-weight coding, around 80 on SWE-Bench Verified.
Its trade-offs are real: independent SWE-Bench Verified placement is inconsistent across sources, pro and Pro-Max variants are quoted with different scores, text and code only — no image, audio or video, and overlaps DeepSeek V4 and V3.2 already in this comparison. At $0.66 in / $1.98 out per million tokens, it sits in the budget price band.
MiMo-V2.5: where it fits
Xiaomi's cheap omnimodal model — Pro-level agentic perception across image and video at a fraction of the cost. Released April 22, 2026 by Xiaomi, it is built for native omnimodal — strong image and video understanding, very low cost (~half the inference of the Pro tier), agent-framework integration, and 1M context for full documents in one pass.
Its trade-offs: not the deepest reasoning tier (see V2.5-Pro), and limited Western tooling and support. At $0.14 in / $0.28 out per million tokens, it sits in the budget price band.
The bottom line for this matchup
DeepSeek V4-Pro and MiMo-V2.5 overlap enough that the right pick depends on your specific job. MiMo-V2.5 costs less per token; and each leads in its own area — DeepSeek V4-Pro for open-weight 1.6t moe (~49b active) — deepseek's largest, self-hostable, MiMo-V2.5 for native omnimodal — strong image and video understanding. Rather than crowning one, run the same hard task through both once and let the results decide.
Want both DeepSeek V4-Pro and MiMo-V2.5 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 V4-Pro or MiMo-V2.5 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 V4-Pro leans toward open-weight 1.6t moe (~49b active) — deepseek's largest, self-hostable while MiMo-V2.5 leans toward native omnimodal — strong image and video understanding, and that positioning usually predicts which feels better on your codebase.
Which is cheaper, DeepSeek V4-Pro or MiMo-V2.5?
MiMo-V2.5 is cheaper — $0.66/$1.98 per 1M tokens vs $0.14/$0.28 per 1M tokens, roughly 4.7× apart on input.
Which has the bigger context window?
Both advertise 1M (~1,500 pages). Remember advertised ≠ usable: recall typically degrades before the ceiling.
Can I use both DeepSeek V4-Pro and MiMo-V2.5 together?
Yes — a multi-model platform like LumiChats gives you DeepSeek V4-Pro, MiMo-V2.5 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 V4-Pro or MiMo-V2.5?
DeepSeek V4-Pro — released April 24, 2026, about 2 days after MiMo-V2.5.
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.