Pick GPT-4.1 Mini for very cheap high-volume text work at $0.40 in / $1.60 out per million tokens or instruction following above its weight class — 84.1% on ifeval, beating gpt-4o. Pick MiMo-V2.5 for native omnimodal — strong image and video understanding or very low cost (~half the inference of the pro tier). Choose MiMo-V2.5 if you need self-hosting or data privacy; GPT-4.1 Mini if you want a managed API.
GPT-4.1 Mini (OpenAI, US) and MiMo-V2.5 (Xiaomi, China) line up two different AI ecosystems against each other — a comparison that is as much about cost philosophy and openness as raw capability. GPT-4.1 Mini is a cheap, fast 1M-context workhorse with strong instruction following but weak coding — already retired from ChatGPT. MiMo-V2.5 is xiaomi's cheap omnimodal model — Pro-level agentic perception across image and video at a fraction of the cost. They diverge most on price, context window and open vs. closed weights — each quantified below from the models' real specs.
Key differences
Price: MiMo-V2.5 is about 2.9× cheaper on input ($0.14/$0.28 per 1M tokens vs $0.4/$1.6 per 1M tokens) — meaningful once you are processing millions of tokens a month.
Context window: 1M vs 1M — within a few percent of each other, so treat this as a tie and test on your own long inputs, since usable recall varies by model.
Recency: MiMo-V2.5 is the newer model by about 12 months (released April 22, 2026), usually meaning fresher training data and capabilities.
Ecosystem: this is a US-vs-China matchup — they differ in pricing philosophy, data-residency options, and tooling ecosystems, not only benchmarks.
Specifications
Spec
GPT-4.1 Mini
MiMo-V2.5
Provider
OpenAI (US)
Xiaomi (China)
Released
April 14, 2025
April 22, 2026
Context window
1M (~1,571 pages)
1M (~1,500 pages)
Price (in/out)
$0.4/$1.6 per 1M tokens
$0.14/$0.28 per 1M tokens
Open weight?
No — API only
Yes — self-hostable
Modalities
text, image, code
text, image, audio, video, code
SWE-Bench Verified
23.6%
Not published
MRCR v2 @ 1M
Not published
Not published
Who wins what
Very cheap high-volume text work at $0.40 in / $1.60 out per million tokens: GPT-4.1 Mini — GPT-4.1 Mini lists very cheap high-volume text work at $0.40 in / $1.60 out per million tokens among its strengths; MiMo-V2.5 does not.
Instruction following above its weight class — 84.1% on IFEval, beating GPT-4o: GPT-4.1 Mini — GPT-4.1 Mini lists instruction following above its weight class — 84.1% on IFEval, beating GPT-4o among its strengths; MiMo-V2.5 does not.
Multi-turn coherence for its tier — 35.8% on MultiChallenge, roughly 1.8x GPT-4o mini: GPT-4.1 Mini — GPT-4.1 Mini lists multi-turn coherence for its tier — 35.8% on MultiChallenge, roughly 1.8x GPT-4o mini among its strengths; MiMo-V2.5 does not.
Native omnimodal — strong image and video understanding: 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.
Very low cost (~half the inference of the Pro tier): MiMo-V2.5 — At $0.14/$0.28 per 1M tokens it undercuts GPT-4.1 Mini ($0.4/$1.6 per 1M tokens), and that gap compounds at volume.
Agent-framework integration: MiMo-V2.5 — GPT-4.1 Mini is comparatively weak here — weak at agentic coding — its 23.6% on SWE-Bench Verified sits below GPT-4o's 33.2%
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 GPT-4.1 Mini, and on millions of tokens that margin decides the monthly bill.
Someone analysing very long documents or codebases: GPT-4.1 Mini — Larger 1M window fits more in one prompt.
A team with data-privacy or self-hosting needs: MiMo-V2.5 — Open weights let you run it on your own hardware; GPT-4.1 Mini is API-only.
Anyone whose priority is very cheap high-volume text work at $0.40 in / $1.60 out per million tokens: GPT-4.1 Mini — 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.
An enterprise with regional data-residency rules: GPT-4.1 Mini or MiMo-V2.5 — Origin (US vs China) affects where data is processed and which compliance regime applies — check the provider's terms for your region.
GPT-4.1 Mini: where it fits
A cheap, fast 1M-context workhorse with strong instruction following but weak coding — already retired from ChatGPT. Released April 14, 2025 by OpenAI, it is built for very cheap high-volume text work at $0.40 in / $1.60 out per million tokens, instruction following above its weight class — 84.1% on IFEval, beating GPT-4o, multi-turn coherence for its tier — 35.8% on MultiChallenge, roughly 1.8x GPT-4o mini, and a full 1M context at flat pricing, with no long-context premium.
Its trade-offs are real: weak at agentic coding — its 23.6% on SWE-Bench Verified sits below GPT-4o's 33.2%, retired from ChatGPT in February 2026, and OpenAI's own docs now point users to GPT-5 mini instead, and a June 2024 knowledge cutoff, now roughly two years stale, and no reasoning mode. At $0.4 in / $1.6 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
The defining split here is open vs. closed. MiMo-V2.5 gives you weights you control — self-host it, fine-tune it, keep data in-house, pay only for hardware. GPT-4.1 Mini gives you a managed, always-updated API with no infrastructure to run. Teams with GPUs, privacy requirements, or huge volume often favour the open model; teams that want zero ops and the latest capabilities favour the closed one. Capability is close enough that this operational question, not the benchmark, usually decides it.
Frequently asked questions
Is GPT-4.1 Mini or MiMo-V2.5 better for coding?
Public SWE-Bench figures are not available for MiMo-V2.5, so the honest test is your own repository — run an identical real bug through both. By design, GPT-4.1 Mini leans toward very cheap high-volume text work at $0.40 in / $1.60 out per million tokens 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, GPT-4.1 Mini or MiMo-V2.5?
MiMo-V2.5 is open-weight, so self-hosting means no per-token fee (you pay for hardware instead), while GPT-4.1 Mini is API-metered at $0.4/$1.6 per 1M tokens. For most teams without GPUs, the API model is cheaper to start; at very high volume, self-hosting can win.
Which has the bigger context window?
Effectively neither — 1M vs 1M is a difference of a few percent. Remember advertised ≠ usable: recall typically degrades before the ceiling.
Can I use both GPT-4.1 Mini and MiMo-V2.5 together?
Yes — a multi-model platform like LumiChats gives you GPT-4.1 Mini, 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, GPT-4.1 Mini or MiMo-V2.5?
MiMo-V2.5 — released April 22, 2026, about 12 months after GPT-4.1 Mini.
GPT-4.1 Mini vs MiMo-V2.5
OpenAI · US | Xiaomi · China · Updated June 2026
Quick verdict
Pick GPT-4.1 Mini for very cheap high-volume text work at $0.40 in / $1.60 out per million tokens or instruction following above its weight class — 84.1% on ifeval, beating gpt-4o. Pick MiMo-V2.5 for native omnimodal — strong image and video understanding or very low cost (~half the inference of the pro tier). Choose MiMo-V2.5 if you need self-hosting or data privacy; GPT-4.1 Mini if you want a managed API.
GPT-4.1 Mini (OpenAI, US) and MiMo-V2.5 (Xiaomi, China) line up two different AI ecosystems against each other — a comparison that is as much about cost philosophy and openness as raw capability. GPT-4.1 Mini is a cheap, fast 1M-context workhorse with strong instruction following but weak coding — already retired from ChatGPT. MiMo-V2.5 is xiaomi's cheap omnimodal model — Pro-level agentic perception across image and video at a fraction of the cost. They diverge most on price, context window and open vs. closed weights — each quantified below from the models' real specs.
Key differences at a glance
▸Price: MiMo-V2.5 is about 2.9× cheaper on input ($0.14/$0.28 per 1M tokens vs $0.4/$1.6 per 1M tokens) — meaningful once you are processing millions of tokens a month.
▸Context window: 1M vs 1M — within a few percent of each other, so treat this as a tie and test on your own long inputs, since usable recall varies by model.
▸Recency: MiMo-V2.5 is the newer model by about 12 months (released April 22, 2026), usually meaning fresher training data and capabilities.
▸Ecosystem: this is a US-vs-China matchup — they differ in pricing philosophy, data-residency options, and tooling ecosystems, not only benchmarks.
Side-by-side specs
Spec
GPT-4.1 Mini
MiMo-V2.5
Provider
OpenAI (US)
Xiaomi (China)
Released
April 14, 2025
April 22, 2026
Context window
1M (~1,571 pages)
1M (~1,500 pages)
Price (in/out)
$0.4/$1.6 per 1M tokens
$0.14/$0.28 per 1M tokens
Open weight?
No — API only
Yes — self-hostable
Modalities
text, image, code
text, image, audio, video, code
SWE-Bench Verified
23.6%
Not published
MRCR v2 @ 1M
Not published
Not published
Who wins what
Very cheap high-volume text work at $0.40 in / $1.60 out per million tokens
GPT-4.1 Mini
GPT-4.1 Mini lists very cheap high-volume text work at $0.40 in / $1.60 out per million tokens among its strengths; MiMo-V2.5 does not.
Instruction following above its weight class — 84.1% on IFEval, beating GPT-4o
GPT-4.1 Mini
GPT-4.1 Mini lists instruction following above its weight class — 84.1% on IFEval, beating GPT-4o among its strengths; MiMo-V2.5 does not.
Multi-turn coherence for its tier — 35.8% on MultiChallenge, roughly 1.8x GPT-4o mini
GPT-4.1 Mini
GPT-4.1 Mini lists multi-turn coherence for its tier — 35.8% on MultiChallenge, roughly 1.8x GPT-4o mini among its strengths; MiMo-V2.5 does not.
Native omnimodal — strong image and video understanding
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.
Very low cost (~half the inference of the Pro tier)
MiMo-V2.5
At $0.14/$0.28 per 1M tokens it undercuts GPT-4.1 Mini ($0.4/$1.6 per 1M tokens), and that gap compounds at volume.
Agent-framework integration
MiMo-V2.5
GPT-4.1 Mini is comparatively weak here — weak at agentic coding — its 23.6% on SWE-Bench Verified sits below GPT-4o's 33.2%
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 GPT-4.1 Mini, and on millions of tokens that margin decides the monthly bill.
Someone analysing very long documents or codebases
→ GPT-4.1 Mini
Larger 1M window fits more in one prompt.
A team with data-privacy or self-hosting needs
→ MiMo-V2.5
Open weights let you run it on your own hardware; GPT-4.1 Mini is API-only.
Anyone whose priority is very cheap high-volume text work at $0.40 in / $1.60 out per million tokens
→ GPT-4.1 Mini
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.
An enterprise with regional data-residency rules
→ GPT-4.1 Mini or MiMo-V2.5
Origin (US vs China) affects where data is processed and which compliance regime applies — check the provider's terms for your region.
GPT-4.1 Mini: where it fits
A cheap, fast 1M-context workhorse with strong instruction following but weak coding — already retired from ChatGPT. Released April 14, 2025 by OpenAI, it is built for very cheap high-volume text work at $0.40 in / $1.60 out per million tokens, instruction following above its weight class — 84.1% on IFEval, beating GPT-4o, multi-turn coherence for its tier — 35.8% on MultiChallenge, roughly 1.8x GPT-4o mini, and a full 1M context at flat pricing, with no long-context premium.
Its trade-offs are real: weak at agentic coding — its 23.6% on SWE-Bench Verified sits below GPT-4o's 33.2%, retired from ChatGPT in February 2026, and OpenAI's own docs now point users to GPT-5 mini instead, and a June 2024 knowledge cutoff, now roughly two years stale, and no reasoning mode. At $0.4 in / $1.6 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
The defining split here is open vs. closed. MiMo-V2.5 gives you weights you control — self-host it, fine-tune it, keep data in-house, pay only for hardware. GPT-4.1 Mini gives you a managed, always-updated API with no infrastructure to run. Teams with GPUs, privacy requirements, or huge volume often favour the open model; teams that want zero ops and the latest capabilities favour the closed one. Capability is close enough that this operational question, not the benchmark, usually decides it.
Want both GPT-4.1 Mini 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.
Public SWE-Bench figures are not available for MiMo-V2.5, so the honest test is your own repository — run an identical real bug through both. By design, GPT-4.1 Mini leans toward very cheap high-volume text work at $0.40 in / $1.60 out per million tokens 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, GPT-4.1 Mini or MiMo-V2.5?
MiMo-V2.5 is open-weight, so self-hosting means no per-token fee (you pay for hardware instead), while GPT-4.1 Mini is API-metered at $0.4/$1.6 per 1M tokens. For most teams without GPUs, the API model is cheaper to start; at very high volume, self-hosting can win.
Which has the bigger context window?
Effectively neither — 1M vs 1M is a difference of a few percent. Remember advertised ≠ usable: recall typically degrades before the ceiling.
Can I use both GPT-4.1 Mini and MiMo-V2.5 together?
Yes — a multi-model platform like LumiChats gives you GPT-4.1 Mini, 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, GPT-4.1 Mini or MiMo-V2.5?
MiMo-V2.5 — released April 22, 2026, about 12 months after GPT-4.1 Mini.
Specifications and benchmarks reflect publicly reported figures as of June 2026 and may change as providers release updates. Always verify on your own workload.