Pick MiMo-V2.5 for native omnimodal — strong image and video understanding or very low cost (~half the inference of the pro tier). Pick Mistral Medium 3 for strong cost-to-capability at $0.40/$2.00 or general reasoning, coding and multimodal tasks. Choose MiMo-V2.5 if you need self-hosting or data privacy; Mistral Medium 3 if you want a managed API.
MiMo-V2.5 (Xiaomi, China) and Mistral Medium 3 (Mistral AI, France) line up two different AI ecosystems against each other — a comparison that is as much about cost philosophy and openness as raw capability. MiMo-V2.5 is xiaomi's cheap omnimodal model — Pro-level agentic perception across image and video at a fraction of the cost. Mistral Medium 3 is mistral's mid-tier model at $0.40/$2.00 — efficient general capability with a 128K window, below the 1M-context frontier tier. 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/$2 per 1M tokens) — meaningful once you are processing millions of tokens a month.
Context window: MiMo-V2.5 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 is the newer model by about 12 months (released April 22, 2026), usually meaning fresher training data and capabilities.
Ecosystem: this is a China-vs-France matchup — they differ in pricing philosophy, data-residency options, and tooling ecosystems, not only benchmarks.
Specifications
Spec
MiMo-V2.5
Mistral Medium 3
Provider
Xiaomi (China)
Mistral AI (France)
Released
April 22, 2026
May 7, 2025
Context window
1M (~1,500 pages)
128K (~192 pages)
Price (in/out)
$0.14/$0.28 per 1M tokens
$0.4/$2 per 1M tokens
Open weight?
Yes — self-hostable
No — API only
Modalities
text, image, audio, video, code
text, image, code
SWE-Bench Verified
Not published
Not published
MRCR v2 @ 1M
Not published
Not published
Who wins what
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 Mistral Medium 3 ($0.4/$2 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 carries the larger 1M context.
Strong cost-to-capability at $0.40/$2.00: Mistral Medium 3 — Mistral Medium 3 lists strong cost-to-capability at $0.40/$2.00 among its strengths; MiMo-V2.5 does not.
General reasoning, coding and multimodal tasks: Mistral Medium 3 — MiMo-V2.5 is comparatively weak here — not the deepest reasoning tier (see V2.5-Pro)
Efficient mid-tier deployment for production workloads: Mistral Medium 3 — Mistral Medium 3 lists efficient mid-tier deployment for production workloads among its strengths; MiMo-V2.5 does not.
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.
Largest single-prompt input: MiMo-V2.5 — Its 1M window is about 7.8× larger than Mistral Medium 3's 128K, fitting roughly 1,500 pages in one prompt.
Which should you pick?
A cost-sensitive startup shipping high volume: MiMo-V2.5 — At $0.14/$0.28 per 1M tokens it undercuts Mistral Medium 3, and on millions of tokens that margin decides the monthly bill.
Someone analysing very long documents or codebases: MiMo-V2.5 — 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; Mistral Medium 3 is API-only.
Anyone whose priority is native omnimodal — strong image and video understanding: MiMo-V2.5 — It is specifically built for that.
Anyone whose priority is strong cost-to-capability at $0.40/$2.00: Mistral Medium 3 — That is its strongest area.
An enterprise with regional data-residency rules: Mistral Medium 3 or MiMo-V2.5 — Origin (China vs France) affects where data is processed and which compliance regime applies — check the provider's terms for your region.
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 are real: 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.
Mistral Medium 3: where it fits
Mistral's mid-tier model at $0.40/$2.00 — efficient general capability with a 128K window, below the 1M-context frontier tier. Released May 7, 2025 by Mistral AI, it is built for strong cost-to-capability at $0.40/$2.00, general reasoning, coding and multimodal tasks, efficient mid-tier deployment for production workloads, and text and image input.
Its trade-offs: a 128K context — smaller than the 1M-window flagships here, no published SWE-Bench Verified score, a mid-tier model, not a frontier reasoner, and proprietary, unlike Mistral's open-weight releases. At $0.4 in / $2 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. Mistral Medium 3 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 MiMo-V2.5 or Mistral Medium 3 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, MiMo-V2.5 leans toward native omnimodal — strong image and video understanding while Mistral Medium 3 leans toward strong cost-to-capability at $0.40/$2.00, and that positioning usually predicts which feels better on your codebase.
Which is cheaper, MiMo-V2.5 or Mistral Medium 3?
MiMo-V2.5 is open-weight, so self-hosting means no per-token fee (you pay for hardware instead), while Mistral Medium 3 is API-metered at $0.4/$2 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?
MiMo-V2.5 — 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 MiMo-V2.5 and Mistral Medium 3 together?
Yes — a multi-model platform like LumiChats gives you MiMo-V2.5, Mistral Medium 3 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, MiMo-V2.5 or Mistral Medium 3?
MiMo-V2.5 — released April 22, 2026, about 12 months after Mistral Medium 3.
MiMo-V2.5 vs Mistral Medium 3
Xiaomi · China | Mistral AI · France · Updated June 2026
Quick verdict
Pick MiMo-V2.5 for native omnimodal — strong image and video understanding or very low cost (~half the inference of the pro tier). Pick Mistral Medium 3 for strong cost-to-capability at $0.40/$2.00 or general reasoning, coding and multimodal tasks. Choose MiMo-V2.5 if you need self-hosting or data privacy; Mistral Medium 3 if you want a managed API.
MiMo-V2.5 (Xiaomi, China) and Mistral Medium 3 (Mistral AI, France) line up two different AI ecosystems against each other — a comparison that is as much about cost philosophy and openness as raw capability. MiMo-V2.5 is xiaomi's cheap omnimodal model — Pro-level agentic perception across image and video at a fraction of the cost. Mistral Medium 3 is mistral's mid-tier model at $0.40/$2.00 — efficient general capability with a 128K window, below the 1M-context frontier tier. 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/$2 per 1M tokens) — meaningful once you are processing millions of tokens a month.
▸Context window: MiMo-V2.5 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 is the newer model by about 12 months (released April 22, 2026), usually meaning fresher training data and capabilities.
▸Ecosystem: this is a China-vs-France matchup — they differ in pricing philosophy, data-residency options, and tooling ecosystems, not only benchmarks.
Side-by-side specs
Spec
MiMo-V2.5
Mistral Medium 3
Provider
Xiaomi (China)
Mistral AI (France)
Released
April 22, 2026
May 7, 2025
Context window
1M (~1,500 pages)
128K (~192 pages)
Price (in/out)
$0.14/$0.28 per 1M tokens
$0.4/$2 per 1M tokens
Open weight?
Yes — self-hostable
No — API only
Modalities
text, image, audio, video, code
text, image, code
SWE-Bench Verified
Not published
Not published
MRCR v2 @ 1M
Not published
Not published
Who wins what
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 Mistral Medium 3 ($0.4/$2 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 carries the larger 1M context.
Strong cost-to-capability at $0.40/$2.00
Mistral Medium 3
Mistral Medium 3 lists strong cost-to-capability at $0.40/$2.00 among its strengths; MiMo-V2.5 does not.
General reasoning, coding and multimodal tasks
Mistral Medium 3
MiMo-V2.5 is comparatively weak here — not the deepest reasoning tier (see V2.5-Pro)
Efficient mid-tier deployment for production workloads
Mistral Medium 3
Mistral Medium 3 lists efficient mid-tier deployment for production workloads among its strengths; MiMo-V2.5 does not.
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.
Largest single-prompt input
MiMo-V2.5
Its 1M window is about 7.8× larger than Mistral Medium 3's 128K, fitting roughly 1,500 pages in one prompt.
Which should you pick?
A cost-sensitive startup shipping high volume
→ MiMo-V2.5
At $0.14/$0.28 per 1M tokens it undercuts Mistral Medium 3, and on millions of tokens that margin decides the monthly bill.
Someone analysing very long documents or codebases
→ MiMo-V2.5
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; Mistral Medium 3 is API-only.
Anyone whose priority is native omnimodal — strong image and video understanding
→ MiMo-V2.5
It is specifically built for that.
Anyone whose priority is strong cost-to-capability at $0.40/$2.00
→ Mistral Medium 3
That is its strongest area.
An enterprise with regional data-residency rules
→ Mistral Medium 3 or MiMo-V2.5
Origin (China vs France) affects where data is processed and which compliance regime applies — check the provider's terms for your region.
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 are real: 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.
Mistral Medium 3: where it fits
Mistral's mid-tier model at $0.40/$2.00 — efficient general capability with a 128K window, below the 1M-context frontier tier. Released May 7, 2025 by Mistral AI, it is built for strong cost-to-capability at $0.40/$2.00, general reasoning, coding and multimodal tasks, efficient mid-tier deployment for production workloads, and text and image input.
Its trade-offs: a 128K context — smaller than the 1M-window flagships here, no published SWE-Bench Verified score, a mid-tier model, not a frontier reasoner, and proprietary, unlike Mistral's open-weight releases. At $0.4 in / $2 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. Mistral Medium 3 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 MiMo-V2.5 and Mistral Medium 3 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 MiMo-V2.5 or Mistral Medium 3 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, MiMo-V2.5 leans toward native omnimodal — strong image and video understanding while Mistral Medium 3 leans toward strong cost-to-capability at $0.40/$2.00, and that positioning usually predicts which feels better on your codebase.
Which is cheaper, MiMo-V2.5 or Mistral Medium 3?
MiMo-V2.5 is open-weight, so self-hosting means no per-token fee (you pay for hardware instead), while Mistral Medium 3 is API-metered at $0.4/$2 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?
MiMo-V2.5 — 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 MiMo-V2.5 and Mistral Medium 3 together?
Yes — a multi-model platform like LumiChats gives you MiMo-V2.5, Mistral Medium 3 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, MiMo-V2.5 or Mistral Medium 3?
MiMo-V2.5 — released April 22, 2026, about 12 months after Mistral Medium 3.
Specifications and benchmarks reflect publicly reported figures as of June 2026 and may change as providers release updates. Always verify on your own workload.