MiMo-V2.5-Pro vs Qwen 3.8-Max
Xiaomi · China | Alibaba · China · Updated June 2026
Quick verdict
Pick MiMo-V2.5-Pro for complex software engineering (top-ranked on swe-bench pro) or long-horizon autonomous tasks (1,000+ tool calls). Pick Qwen 3.8-Max for near-frontier quality at value pricing — artificial analysis intelligence index 58 or large 1m-token context with multimodal input (text, image, video). Choose MiMo-V2.5-Pro if you need self-hosting or data privacy; Qwen 3.8-Max if you want a managed API.
MiMo-V2.5-Pro (Xiaomi) and Qwen 3.8-Max (Alibaba) are two of the models people most often weigh against each other in 2026. MiMo-V2.5-Pro is xiaomi's flagship agentic model — autonomous, long-horizon software engineering at a fraction of frontier cost. Qwen 3.8-Max is alibaba's flagship mixture-of-experts model — near-frontier on independent tests (AA Index 58) at a fraction of US-flagship pricing, with open weights promised but not yet shipped. 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-Pro is about 4.6× cheaper on input ($0.435/$0.87 per 1M tokens vs $2/$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: Qwen 3.8-Max is the newer model by about 3 months (released August 3, 2026), usually meaning fresher training data and capabilities.
Side-by-side specs
| Spec | MiMo-V2.5-Pro | Qwen 3.8-Max |
|---|---|---|
| Provider | Xiaomi (China) | Alibaba (China) |
| Released | April 22, 2026 | August 3, 2026 |
| Context window | 1M (~1,500 pages) | 1M (~1,573 pages) |
| Price (in/out) | $0.435/$0.87 per 1M tokens | $2/$6 per 1M tokens |
| Open weight? | Yes — self-hostable | No — API only |
| Modalities | text, image, video, code | text, image, video, code |
| SWE-Bench Verified | Not published | Not published |
| MRCR v2 @ 1M | Not published | Not published |
Who wins what
Complex software engineering (top-ranked on SWE-bench Pro)
MiMo-V2.5-Pro
Qwen 3.8-Max is comparatively weak here — flashier coding/agentic benchmarks (e.g. Terminal-Bench 86.6) are Alibaba's own, not independently reproduced
Long-horizon autonomous tasks (1,000+ tool calls)
MiMo-V2.5-Pro
Xiaomi's flagship agentic model — autonomous, long-horizon software engineering at a fraction of frontier cost — and it runs cheaper at $0.435/$0.87 per 1M tokens.
Strong on GDPVal and ClawEval
MiMo-V2.5-Pro
Xiaomi's flagship agentic model — autonomous, long-horizon software engineering at a fraction of frontier cost — and its weights are open while Qwen 3.8-Max is API-only.
Near-frontier quality at value pricing — Artificial Analysis Intelligence Index 58
Qwen 3.8-Max
Alibaba's flagship mixture-of-experts model — near-frontier on independent tests (AA Index 58) at a fraction of US-flagship pricing, with open weights promised but not yet shipped — and it is the newer of the two.
Large 1M-token context with multimodal input (text, image, video)
Qwen 3.8-Max
MiMo-V2.5-Pro is comparatively weak here — benchmark rankings are largely vendor-stated
Mixture-of-experts design: ~2.4T total parameters (Alibaba-reported), a fraction active per token
Qwen 3.8-Max
Qwen 3.8-Max lists mixture-of-experts design: ~2.4T total parameters (Alibaba-reported), a fraction active per token among its strengths; MiMo-V2.5-Pro does not.
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.
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 Qwen 3.8-Max, and on millions of tokens that margin decides the monthly bill.
Someone analysing very long documents or codebases
→ Qwen 3.8-Max
Larger 1M window fits more in one prompt.
A team with data-privacy or self-hosting needs
→ MiMo-V2.5-Pro
Open weights let you run it on your own hardware; Qwen 3.8-Max is API-only.
Anyone whose priority is complex software engineering (top-ranked on swe-bench pro)
→ MiMo-V2.5-Pro
It is specifically built for that.
Anyone whose priority is near-frontier quality at value pricing — artificial analysis intelligence index 58
→ Qwen 3.8-Max
That is its strongest area.
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 are real: 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.
Qwen 3.8-Max: where it fits
Alibaba's flagship mixture-of-experts model — near-frontier on independent tests (AA Index 58) at a fraction of US-flagship pricing, with open weights promised but not yet shipped. Released August 3, 2026 by Alibaba, it is built for near-frontier quality at value pricing — Artificial Analysis Intelligence Index 58, large 1M-token context with multimodal input (text, image, video), mixture-of-experts design: ~2.4T total parameters (Alibaba-reported), a fraction active per token, and $2/$6 per million tokens — far below US flagships like Claude Opus 5 and GPT-5.6 Sol.
Its trade-offs: open weights were announced for release but had not shipped as of mid-August 2026 — a closed API for now, active-parameter count is not officially disclosed by Alibaba, flashier coding/agentic benchmarks (e.g. Terminal-Bench 86.6) are Alibaba's own, not independently reproduced, and trails the very top models (Opus 5, Fable 5, GPT-5.6 Sol) on independent tests. At $2 in / $6 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-Pro gives you weights you control — self-host it, fine-tune it, keep data in-house, pay only for hardware. Qwen 3.8-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-Pro and Qwen 3.8-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-Pro or Qwen 3.8-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-Pro leans toward complex software engineering (top-ranked on swe-bench pro) while Qwen 3.8-Max leans toward near-frontier quality at value pricing — artificial analysis intelligence index 58, and that positioning usually predicts which feels better on your codebase.
Which is cheaper, MiMo-V2.5-Pro or Qwen 3.8-Max?
MiMo-V2.5-Pro is open-weight, so self-hosting means no per-token fee (you pay for hardware instead), while Qwen 3.8-Max is API-metered at $2/$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 MiMo-V2.5-Pro and Qwen 3.8-Max together?
Yes — a multi-model platform like LumiChats gives you MiMo-V2.5-Pro, Qwen 3.8-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-Pro or Qwen 3.8-Max?
Qwen 3.8-Max — released August 3, 2026, about 3 months after MiMo-V2.5-Pro.
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.