Pick DeepSeek R1 for open-weight reasoning model or transparent chain-of-thought. Pick MiMo-V2.5-Pro for complex software engineering (top-ranked on swe-bench pro) or long-horizon autonomous tasks (1,000+ tool calls). On a tight budget at scale, MiMo-V2.5-Pro is the value pick.
DeepSeek R1 (DeepSeek) and MiMo-V2.5-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-V2.5-Pro is xiaomi's flagship agentic model — autonomous, long-horizon software engineering at a fraction of frontier cost. They diverge most on price and context window — each quantified below from the models' real specs.
Key differences
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-V2.5-Pro holds 7.8× more — 1M (~1,500 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-V2.5-Pro is the newer model by about 15 months (released April 22, 2026), usually meaning fresher training data and capabilities.
Specifications
Spec
DeepSeek R1
MiMo-V2.5-Pro
Provider
DeepSeek (China)
Xiaomi (China)
Released
January 2025
April 22, 2026
Context window
128K (~192 pages)
1M (~1,500 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, code
SWE-Bench Verified
Not published
Not published
MRCR v2 @ 1M
Not published
Not published
Who wins what
Open-weight reasoning model: DeepSeek R1 — A core design strength of DeepSeek R1.
Transparent chain-of-thought: DeepSeek R1 — A core design strength of DeepSeek R1.
Low cost: DeepSeek R1 — A core design strength of DeepSeek R1.
Complex software engineering (top-ranked on SWE-bench Pro): MiMo-V2.5-Pro — A core design strength of MiMo-V2.5-Pro.
Long-horizon autonomous tasks (1,000+ tool calls): MiMo-V2.5-Pro — A core design strength of MiMo-V2.5-Pro.
Strong on GDPVal and ClawEval: MiMo-V2.5-Pro — A core design strength of MiMo-V2.5-Pro.
Lowest cost at scale: MiMo-V2.5-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-V2.5-Pro — Its 1M window is about 7.8× larger, fitting roughly 1,500 pages in one prompt.
Which should you pick?
A cost-sensitive startup shipping high volume: MiMo-V2.5-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-V2.5-Pro — Larger 1M 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 complex software engineering (top-ranked on swe-bench pro): MiMo-V2.5-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: 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-V2.5-Pro: where it fits
Xiaomi's flagship agentic model — autonomous, long-horizon software engineering at a fraction of frontier cost. Released April 22, 2026 by Xiaomi, it is built for complex software engineering (top-ranked on SWE-bench Pro), long-horizon autonomous tasks (1,000+ tool calls), strong on GDPVal and ClawEval, and agent-framework integration.
Its trade-offs: benchmark rankings are largely vendor-stated, and limited Western adoption and tooling. 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-V2.5-Pro overlap enough that the right pick depends on your specific job. MiMo-V2.5-Pro costs less per token; MiMo-V2.5-Pro holds the larger context; and each leads in its own area — DeepSeek R1 for open-weight reasoning model, MiMo-V2.5-Pro for complex software engineering (top-ranked on swe-bench pro). Rather than crowning one, run the same hard task through both once and let the results decide.
Frequently asked questions
Is DeepSeek R1 or MiMo-V2.5-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-V2.5-Pro leans toward complex software engineering (top-ranked on swe-bench pro), and that positioning usually predicts which feels better on your codebase.
Which is cheaper, DeepSeek R1 or MiMo-V2.5-Pro?
MiMo-V2.5-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-V2.5-Pro — 1M vs 128K, about 7.8× larger. Useful only if the model actually reasons over the full window, which not all do.
Can I use both DeepSeek R1 and MiMo-V2.5-Pro together?
Yes — a multi-model platform like LumiChats gives you DeepSeek R1, MiMo-V2.5-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-V2.5-Pro?
MiMo-V2.5-Pro — released April 22, 2026, about 15 months after DeepSeek R1.
DeepSeek R1 vs MiMo-V2.5-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-V2.5-Pro for complex software engineering (top-ranked on swe-bench pro) or long-horizon autonomous tasks (1,000+ tool calls). On a tight budget at scale, MiMo-V2.5-Pro is the value pick.
DeepSeek R1 (DeepSeek) and MiMo-V2.5-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-V2.5-Pro is xiaomi's flagship agentic model — autonomous, long-horizon software engineering at a fraction of frontier cost. 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-V2.5-Pro holds 7.8× more — 1M (~1,500 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-V2.5-Pro is the newer model by about 15 months (released April 22, 2026), usually meaning fresher training data and capabilities.
Side-by-side specs
Spec
DeepSeek R1
MiMo-V2.5-Pro
Provider
DeepSeek (China)
Xiaomi (China)
Released
January 2025
April 22, 2026
Context window
128K (~192 pages)
1M (~1,500 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, code
SWE-Bench Verified
Not published
Not published
MRCR v2 @ 1M
Not published
Not published
Who wins what
Open-weight reasoning model
DeepSeek R1
A core design strength of DeepSeek R1.
Transparent chain-of-thought
DeepSeek R1
A core design strength of DeepSeek R1.
Low cost
DeepSeek R1
A core design strength of DeepSeek R1.
Complex software engineering (top-ranked on SWE-bench Pro)
MiMo-V2.5-Pro
A core design strength of MiMo-V2.5-Pro.
Long-horizon autonomous tasks (1,000+ tool calls)
MiMo-V2.5-Pro
A core design strength of MiMo-V2.5-Pro.
Strong on GDPVal and ClawEval
MiMo-V2.5-Pro
A core design strength of MiMo-V2.5-Pro.
Lowest cost at scale
MiMo-V2.5-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-V2.5-Pro
Its 1M window is about 7.8× larger, fitting roughly 1,500 pages in one prompt.
Which should you pick?
A cost-sensitive startup shipping high volume
→ MiMo-V2.5-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-V2.5-Pro
Larger 1M 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 complex software engineering (top-ranked on swe-bench pro)
→ MiMo-V2.5-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: 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-V2.5-Pro: where it fits
Xiaomi's flagship agentic model — autonomous, long-horizon software engineering at a fraction of frontier cost. Released April 22, 2026 by Xiaomi, it is built for complex software engineering (top-ranked on SWE-bench Pro), long-horizon autonomous tasks (1,000+ tool calls), strong on GDPVal and ClawEval, and agent-framework integration.
Its trade-offs: benchmark rankings are largely vendor-stated, and limited Western adoption and tooling. 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-V2.5-Pro overlap enough that the right pick depends on your specific job. MiMo-V2.5-Pro costs less per token; MiMo-V2.5-Pro holds the larger context; and each leads in its own area — DeepSeek R1 for open-weight reasoning model, MiMo-V2.5-Pro for complex software engineering (top-ranked on swe-bench pro). Rather than crowning one, run the same hard task through both once and let the results decide.
Want both DeepSeek R1 and MiMo-V2.5-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.
Is DeepSeek R1 or MiMo-V2.5-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-V2.5-Pro leans toward complex software engineering (top-ranked on swe-bench pro), and that positioning usually predicts which feels better on your codebase.
Which is cheaper, DeepSeek R1 or MiMo-V2.5-Pro?
MiMo-V2.5-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-V2.5-Pro — 1M vs 128K, about 7.8× larger. Useful only if the model actually reasons over the full window, which not all do.
Can I use both DeepSeek R1 and MiMo-V2.5-Pro together?
Yes — a multi-model platform like LumiChats gives you DeepSeek R1, MiMo-V2.5-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-V2.5-Pro?
MiMo-V2.5-Pro — released April 22, 2026, about 15 months after DeepSeek R1.
Specifications and benchmarks reflect publicly reported figures as of June 2026 and may change as providers release updates. Always verify on your own workload.