MiMo-V2.5 vs Qwen 3.7 Max
Xiaomi · China | Alibaba · China · 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 Qwen 3.7 Max for long-horizon agentic coding (swe-bench pro 60.6, terminal-bench 2.0 69.7) or 1m-token long-document and full-codebase analysis. Choose MiMo-V2.5 if you need self-hosting or data privacy; Qwen 3.7 Max if you want a managed API.
MiMo-V2.5 (Xiaomi) and Qwen 3.7 Max (Alibaba) are two of the models people most often weigh against each other in 2026. MiMo-V2.5 is xiaomi's cheap omnimodal model — Pro-level agentic perception across image and video at a fraction of the cost. Qwen 3.7 Max is alibaba's agent-first frontier model — a 1M-token context and long-horizon coding at about half the cost of US flagships. They diverge most on price and open vs. closed weights — each quantified below from the models' real specs.
Key differences at a glance
- ▸Price: MiMo-V2.5 is about 18× cheaper on input ($0.14/$0.28 per 1M tokens vs $2.5/$7.5 per 1M tokens) — a large enough gap that at scale it can be the single biggest line item in the decision.
- ▸Context window: both advertise 1M (~1,500 pages). Tie on paper — test on your own long inputs, since usable recall varies by model.
- ▸Recency: Qwen 3.7 Max is the newer model by about 28 days (released May 20, 2026), usually meaning fresher training data and capabilities.
Side-by-side specs
| Spec | MiMo-V2.5 | Qwen 3.7 Max |
|---|---|---|
| Provider | Xiaomi (China) | Alibaba (China) |
| Released | April 22, 2026 | May 20, 2026 |
| Context window | 1M (~1,500 pages) | 1M (~1,500 pages) |
| Price (in/out) | $0.14/$0.28 per 1M tokens | $2.5/$7.5 per 1M tokens |
| Open weight? | Yes — self-hostable | No — API only |
| Modalities | text, image, audio, video, code | text, 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
Qwen 3.7 Max is comparatively weak here — text-only — no vision input (the Plus variant adds images)
Very low cost (~half the inference of the Pro tier)
MiMo-V2.5
At $0.14/$0.28 per 1M tokens it undercuts Qwen 3.7 Max ($2.5/$7.5 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.
Long-horizon agentic coding (SWE-Bench Pro 60.6, Terminal-Bench 2.0 69.7)
Qwen 3.7 Max
Alibaba's agent-first frontier model — a 1M-token context and long-horizon coding at about half the cost of US flagships — and it is the newer of the two.
1M-token long-document and full-codebase analysis
Qwen 3.7 Max
Qwen 3.7 Max lists 1M-token long-document and full-codebase analysis among its strengths; MiMo-V2.5 does not.
MCP tool orchestration and multi-hour autonomous runs
Qwen 3.7 Max
Qwen 3.7 Max lists mCP tool orchestration and multi-hour autonomous runs 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.
Which should you pick?
A cost-sensitive startup shipping high volume
→ MiMo-V2.5
At $0.14/$0.28 per 1M tokens it undercuts Qwen 3.7 Max, and on millions of tokens that margin decides the monthly bill.
A team with data-privacy or self-hosting needs
→ MiMo-V2.5
Open weights let you run it on your own hardware; Qwen 3.7 Max 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 long-horizon agentic coding (swe-bench pro 60.6, terminal-bench 2.0 69.7)
→ Qwen 3.7 Max
That is its strongest area.
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.
Qwen 3.7 Max: where it fits
Alibaba's agent-first frontier model — a 1M-token context and long-horizon coding at about half the cost of US flagships. Released May 20, 2026 by Alibaba, it is built for long-horizon agentic coding (SWE-Bench Pro 60.6, Terminal-Bench 2.0 69.7), 1M-token long-document and full-codebase analysis, mCP tool orchestration and multi-hour autonomous runs, and frontier intelligence at roughly half the price of US flagships.
Its trade-offs: text-only — no vision input (the Plus variant adds images), closed-weight, API-only — no self-hosting, trails GPT-5.5 and Claude Opus on the hardest one-shot reasoning, and chinese-jurisdiction data-residency considerations. At $2.5 in / $7.5 out per million tokens, it sits in the mid 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. Qwen 3.7 Max 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 Qwen 3.7 Max 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 MiMo-V2.5 or Qwen 3.7 Max 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 Qwen 3.7 Max leans toward long-horizon agentic coding (swe-bench pro 60.6, terminal-bench 2.0 69.7), and that positioning usually predicts which feels better on your codebase.
Which is cheaper, MiMo-V2.5 or Qwen 3.7 Max?
MiMo-V2.5 is open-weight, so self-hosting means no per-token fee (you pay for hardware instead), while Qwen 3.7 Max is API-metered at $2.5/$7.5 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?
Both advertise 1M (~1,500 pages). Remember advertised ≠ usable: recall typically degrades before the ceiling.
Can I use both MiMo-V2.5 and Qwen 3.7 Max together?
Yes — a multi-model platform like LumiChats gives you MiMo-V2.5, Qwen 3.7 Max 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 Qwen 3.7 Max?
Qwen 3.7 Max — released May 20, 2026, about 28 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.